1	TOPOLOGICAL LEARNING FOR IMBALANCED TIME SERIES ANALYSIS
1	TOPOLOGICAL DATA ANALYSIS , TDA , USES ALGEBRAIC TOPOLOGICAL TOOLS TO ANALYZE THE SHAPE OF DATA
1	SUBLEVEL SET FILTRATION IS A WIDELY USED TOOL IN TDA THAT CAPTURES HOMOLOGICAL FEATURES OF DATA AT MULTIPLE SCALES AND SUMMARIZES THE LIFESPAN OF THESE FEATURES IN SUMMARY DIAGRAMS , NAMELY PERSISTENCE DIAGRAMS , PDS , 
1	BY USING SUBLEVEL SET FILTRATION APPROACH AND RANDOM PERSISTENCE DIAGRAM GENERATOR , RPDG , METHOD , WE PROPOSE A GENERAL PIPELINE FOR ANALYZING THE TOPOLOGICAL FEATURES OF IMBALANCED TIME SERIES DATA
1	WE THEN INVESTIGATE THE EFFICACY OF OUR PIPELINE USING FOUR MAIN STOCK MARKET INDICES IN THE US , DOW JONES , S P , NASDAQ COMPOSITE , AND RUSSELL , TO DISTINGUISH BETWEEN STOCK INDICES OBTAINED WITH RECESSIONS AND WITHOUT RECESSIONS
1	APPLIED PROBABILITY DECISION ANALYSIS SOCIETY ARTIFICIAL INTELLIGENCE
1	MY TALK EXPLORES HOW TO AUGMENT DATA OF THE MINORITY GROUP IN IMBALANCED DATA 
2	ON COIN FLIPPING GAMES WITH UNCERTAINTY IN THE PROBABILITY OF HEADS , BEYOND LINEAR KELLY BETTING STRATEGIES
2	IN THIS PAPER WE ROBUSTIFY KELLY S CELEBRATED BETTING STRATEGY FOR A GAME INVOLVING N FLIPS OF A BIASED COIN WITH PROBABILITY OF HEADS P UNLIKE THE CLASSICAL THEORY WITH P BEING PERFECTLY KNOWN , WE ONLY ASSUME THAT A SUBSET P OF , , , IS SPECIFIED FOR THIS PROBABILITY
2	WHEREAS THE CLASSICAL KELLY STRATEGY DEFINES THE SIZE OF ALL WAGERS TO BE THE SAME FIXED FRACTION OF WEALTH ALONG SAMPLE PATHS , OUR MAIN RESULT IS THAT ASSURANCE OF ROBUSTNESS WITH RESPECT TO P DICTATES USE OF A STRATEGY WHICH IS NONLINEAR IN NATURE YET CAN BE COMPUTED EFFICIENTLY
2	TO OUR KNOWLEDGE , NONLINEAR STRATEGIES HAVE NOT BEEN CONSIDERED TO DATE IN THE BODY OF LITERATURE UNDER CONSIDERATION
2	APPLIED PROBABILITY FINANCE 
3	HIGH DIMENSIONAL COVARIANCE ESTIMATION WITH STRUCTURAL INFORMATION
3	WE GENERALISE THE TAPERING ESTIMATORS FOR HIGH DIMENSIONAL COVARIANCE MATRICES TO ALLOW FOR MORE COMPLEX AND PRACTICAL DEPENDENCE STRUCTURE WHILE ALLOWING FOR MEASUREMENT ERRORS IN THE OBSERVATIONS OF THE STRUCTURE SATISFYING VERY WEAK CONDITIONS
3	WE ESTABLISH THE CONVERGENCE RATE OF SUCH ESTIMATORS
3	WE ARGUE THAT IT IS OFTEN BENEFICIAL TO INCLUDE AUXILIARY STRUCTURAL INFORMATION EVEN IF IT IS MEASURED WITH ERRORS
3	APPLIED PROBABILITY FINANCE 
3	A WAY TO INCORPORATE AUXILIARY STRUCTURAL INFORMATION INTO THE ESTIMATION OF COVARIANCE 
4	OPTIMAL AND APPROXIMATE SOLUTIONS TO THE BACKUP SERVER PROBLEM
4	BACKUP SERVERS ARE OFTEN USED IN SERVICE SYSTEMS TO LOWER OPERATING COSTS AND INCREASE RELIABILITY
4	BACKUP SERVERS MAY HAVE A LOWER SERVICE QUALITY OR A SLOWER SERVICE RATE
4	WE ANALYZE A SYSTEM WITH ONE PRIMARY AND ONE BACKUP SERVER AND COMPUTE THE SYSTEM AND INDIVIDUALLY OPTIMAL SERVER SELECTION STRATEGIES
4	WE ALSO COMPARE THE OPTIMAL STRATEGY WITH THE BETTER OF TWO SIMPLE STRATEGIES , USING ONLY THE PRIMARY SERVER OR NEVER WAITING FOR THE PRIMARY SERVER WHEN THE BACKUP SERVER IS IDLE
4	WE DISCUSS WHEN SUCH A SIMPLE STRATEGY IS A GOOD APPROXIMATION
4	FINALLY , WE COMPARE THE INDIVIDUALLY OPTIMAL STRATEGY TO THE SOCIALLY OPTIMAL
4	APPLIED PROBABILITY HEALTH APPLICATIONS SOCIETY OPTIMIZATION , OPT , 
5	MAXIMIZING HEALTHCARE WORKER AVAILABILITY DURING INFECTIOUS DISEASE OUTBREAKS , A NOVEL MDP MODEL AND VALIDATION STUDY
5	HEALTHCARE WORKERS ARE AT INCREASED RISK DURING INFECTIOUS DISEASE OUTBREAKS , WHICH CAN IMPACT THEIR ABILITY TO PROVIDE CARE
5	WE DEVELOP AN MDP MODEL TO OPTIMIZE HEALTHCARE WORKER AVAILABILITY DURING AN OUTBREAK
5	GOING BEYOND THE SEIR FRAMEWORK , OUR MODEL IS PRESCRIPTIVE AND PROVIDES IMPLEMENTABLE STAFFING POLICIES
5	TO VALIDATE THE MODEL , WE FIRST CONDUCT A SIMULATION STUDY AND DEMONSTRATE THE ALIGNMENT OF MODEL RESULTS WITH EXISTING LITERATURE
5	WE THEN PRESENT A CASE STUDY USING REAL WORLD COVID INFECTION AND CONTACT DATA COLLECTED ON CLEMSON UNIVERSITY CAMPUS
5	THESE ANALYSES SHOW THE CREDIBILITY OF THE PROPOSED MODEL AND ALLOW US TO ASSESS THE MODEL S ABILITY TO IMPROVE HEALTHCARE WORKER AVAILABILITY DURING AN OUTBREAK
5	WE ALSO DISCUSS THE POTENTIAL USE OF OUR MDP MODEL TO DEVISE OPTIMAL SCHEDULES FOR HEALTHCARE WORKERS THROUGHOUT DIFFERENT PHASES OF AN OUTBREAK
5	APPLIED PROBABILITY HEALTH APPLICATIONS SOCIETY PANDEMIC MANAGEMENT
6	ONLINE INVENTORY CONTROL WITH PARTIAL BACKORDER
6	WE CONSIDER A SINGLE PRODUCT INVENTORY MODEL WHERE THE UNMET DEMANDS MAY BE EITHER PATIENT AND CHOOSE TO WAIT , BACKORDER , OR LOSE THEIR PATIENCE AND LEAVE , LOST SALE , , WHICH CAN BE TAKEN AS THE HYBRID OF THE CANONICAL LOST SALES AND BACKORDER MODEL
6	WITH PERFECT INFORMATION ABOUT THE SYSTEM PRIMITIVES AND PERFECT OBSERVATION OF THE STATES OF THE SYSTEM , WE SHOW THAT THE BASE STOCK POLICY IS A UNIFORMLY ASYMPTOTICALLY OPTIMAL POLICY
6	WE THEN CONSIDER A MORE PRACTICAL PROBLEM WHERE THE SYSTEM PRIMITIVES ARE UNKNOWN AND ONLY THE SALES ARE OBSERVED
6	COMPARED TO THE LITERATURE , OUR PROBLEM HAS UNIQUE CHALLENGES AS , A , THE STATE OF THE SYSTEM IS ONLY PARTIALLY OBSERVABLE AND , B , THE SALES ARE MIXED BY THE EXOGENOUS DEMAND AND THE BACKORDER
6	AN UCB TYPE ALGORITHM IS THEN DEVELOPED AND WE PROVE THE REGRETS OF THE ALGORITHM ARE , NEARLY , TIGHT IN THE PLANNING HORIZON T 
6	APPLIED PROBABILITY MANUFACTURING AND SERVICE OPERATIONS MANAGEMENT , MSOM , MACHINE LEARNING IN OPERATIONS
6	OUR WORK INCORPORATE SALES DATA TO BALANCE LEARNING AND EARNING IN DECISION MAKING 
7	APRIORI ALGORITHM APPLICATION AND SIMULATION IN SUPPLY CHAIN MANAGEMENT
7	THE TRADITIONAL SUPPLY CHAIN NETWORK DISTRIBUTION IN THE ACTUAL OPERATION CAN NOT MEET CUSTOMER DEMAND FOR GOODS
7	BASED ON THE LIMITATION OF CAPACITY , THIS PAPER MAKES A REASONABLE ALLOCATION OF CUSTOMER RESOURCES BETWEEN PRIMARY AND SECONDARY WAREHOUSES
7	WHEN THE MAIN WAREHOUSE CAN NOT MEET THE CUSTOMER S DEMAND , WE CAN ADD A SUB WAREHOUSE IN THE VICINITY TO FILL THE SHORTAGE OF DEMAND
7	FIRSTLY , THE PROBLEM IS DESCRIBED AS AN INTEGER PROGRAMMING MODEL , AND THEN THE APRIORI ALGORITHM IS USED TO ENCODE AND ARRANGE ALL THE CUSTOMERS AND WAREHOUSES
7	THE TOC IS USED TO OPTIMIZE THE CONFIGURATION
7	FINALLY , THE ALGORITHM IS SIMULATED BY NUMERICAL EXAMPLES , WHICH PROVES THAT THE ALGORITHM IS SOLVING THE PROBLEM THE EFFECTIVENESS AND PRACTICALITY
7	APPLIED PROBABILITY MULTIPLE CRITERIA DECISION MAKING 
8	ESTIMATION OF OPTIMAL TREATMENT REGIME IN HIGH DIMENSIONAL SINGLE INDEX QUANTILE REGRESSION
8	ESTIMATION OF THE OPTIMAL TREATMENT REGIME IS AN IMPORTANT PROBLEM AND HAS USEFUL APPLICATIONS IN VARIOUS FIELDS
8	THE MEAN OPTIMAL TREATMENT REGIME IS NOT RELIABLE WHEN THE OUTCOME DISTRIBUTION IS NOT SYMMETRIC
8	THE QUANTILE OPTIMAL TREATMENT REGIME , WHICH OPTIMIZES SOME DESIRED QUANTILE OF THE POTENTIAL OUTCOME INSTEAD OF THE MEAN , MAY OCCASIONALLY BE OF INTEREST
8	WE PROPOSE A FLEXIBLE PENALIZED SINGLE INDEX MODEL WHICH CAN SELECT THE IMPORTANT VARIABLES FROM HIGH DIMENSIONAL BASELINE COVARIATES
8	WE DISCUSS THE ASYMPTOTIC PROPERTIES OF THE PROPOSED ESTIMATORS
8	OUR RESULTS HELP TO QUANTIFY THE VARIABILITY RELATED TO THE ESTIMATED QUANTILE OPTIMAL TREATMENT REGIME BY CONSTRUCTING SIMULTANEOUS CONFIDENCE BANDS
8	THE USEFULNESS OF THE PROPOSED METHODOLOGY IS ILLUSTRATED USING SIMULATIONS AND DATA ANALYSIS
8	APPLIED PROBABILITY OPT , MACHINE LEARNING DATA MINING
9	T ESTIMATION OF CONTROLLED MARKOV CHAINS VIA RANDOMISED HELLINGER DISTANCES USING HISTOGRAMS
9	IN THIS WORK , WE ESTIMATE THE TRANSITION FUNCTIONS S OF A CONTROLLED MARKOV CHAINS USING HISTOGRAMS
9	WE DEFINE A RANDOMISED HELLINGER DISTANCE AND PROVE THAT OUR ESTIMATOR SATISFIES MINIMAX RISK BOUNDS WITH RESPECT TO THAT DISTANCE
9	WE PRODUCE A TESTING FUNCTIONAL T TO EVALUATE TWO DISTINCT ESTIMATES OF S , AND DESCRIBE A MODEL SELECTION PROCEDURE FOR CHOOSING THE BEST ESTIMATOR BY REPRESENTING IT AS A CONSTRAINED MINIMISATION PROBLEM
9	WE THEN ILLUSTRATE THE APPLICABILITY OF OUR PROBLEM BY PROVIDING ORACLE RISK BOUNDS FOR ESTIMATING THE TRANSITION DENSITIES OF AN OFFLINE REINFORCEMENT LEARNING , RL , ALGORITHM WITH MINIMAL ASSUMPTION ON THE POLICY
9	APPLIED PROBABILITY OPT , MACHINE LEARNING MACHINE LEARNING IN OPERATIONS
10	POSTERIOR SAMPLING FROM THE SPIKED MODELS VIA DIFFUSION PROCESSES
10	SAMPLING FROM THE POSTERIOR IS A KEY TECHNICAL PROBLEM IN BAYESIAN STATISTICS
10	RIGOROUS GUARANTEES ARE DIFFICULT TO OBTAIN FOR MARKOV CHAIN MONTE CARLO ALGORITHMS OF COMMON USE
10	IN THIS PAPER , WE STUDY AN ALTERNATIVE CLASS OF ALGORITHMS BASED ON DIFFUSION PROCESSES
10	OUR CONSTRUCTION OF THE DIFFUSION IS BASED ON THE NOTION OF OBSERVATION PROCESS AND THE RELATED IDEA OF STOCHASTIC LOCALIZATION
10	WE APPLY THIS METHOD TO POSTERIOR SAMPLING IN THE HIGH DIMENSIONAL SYMMETRIC SPIKED MODEL
10	OUR SAMPLING ALGORITHM MAKES USE OF AN ORACLE THAT COMPUTES THE POSTERIOR EXPECTATION OF Θ GIVEN THE DATA AND THE ADDITIONAL OBSERVATION PROCESS
10	WE PROVIDE AN EFFICIENT IMPLEMENTATION OF THIS ORACLE USING APPROXIMATE MESSAGE PASSING
10	WE THUS DEVELOP THE FIRST SAMPLING ALGORITHM FOR THIS PROBLEM WITH APPROXIMATION GUARANTEES
10	APPLIED PROBABILITY OPT , OPTIMIZATION UNDER UNCERTAINTY COMPUTING SOCIETY
11	HOW THE MEAN FIELD GAMES APPLIED TO MANY PLAYERS DIFFERENTIAL GAMES
11	THE MEAN FIELD GAME SYSTEMS MAY BE USED TO CONSTRUCT NASH EQUILIBRIA FOR FINITELY MANY PLAYERS DIFFERENTIAL GAMES
11	IN THIS WORK , A MODEL WILL BE INTRODUCED TO SUPPORT TO FIND AN APPROXIMATE NASH EQUILIBRIA FOR MULTIPLAYER GAMES
11	APPLIED PROBABILITY OPTIMIZATION , OPT , DECISION ANALYSIS SOCIETY
12	LARGE DEVIATIONS OF AFFINE PROCESSES
12	WE DEVELOP AN LARGE DEVIATIONS PRINCIPLE FOR THE GENERAL CLASS OF AFFINE PROCESSES THAT INCLUDES AS SPECIAL CASES ALL LÉVY PROCESSES , CONTINUOUS TIME BRANCHING AND HAWKE S PROCESSES , THE ORNSTEIN UHLENBECK AND BESSEL DIFFUSIONS , COX INGERSOL ROSS PROCESSES AND THEIR MANY GENERALIZATIONS
12	OUR LARGE DEVIATION ASYMPTOTICS ARE OF THE FRIEDLIN WENTZELL TYPE AND THUS CONTRIBUTE TO THE STUDY OF DYNAMICAL SYSTEMS SUBJECT TO RANDOM PERTURBATIONS
12	THESE PERTURBATION ARE DRIVEN BY SMALL NOISE DIFFUSIONS AS WELL BY JUMP NOISE WITH PATHS OF , IN , FINITE VARIATIONS AND OR , IN , FINITE JUMP ACTIVITY
12	WE ESTABLISH OUR RESULTS USING THE DAWSON GARTNER PROJECTIVE LIMITS APPROACH AS WELL AS THE METHOD OF EXPONENTIAL MARTINGALES
12	WE PROVIDE AN EXPLICIT REPRESENTATION OF THE LARGE DEVIATIONS RATE FUNCTION FOR THE CASE OF FINITE JUMP ACTIVITY
12	APPLIED PROBABILITY QUALITY , STATISTICS AND RELIABILITY FINANCE
13	USING BIRTH DEATH PROCESSES TO INFER TUMOR SUBPOPULATION STRUCTURE FROM LIVE CELL IMAGING DRUG SCREENING DATA
13	TUMOR HETEROGENEITY IS A COMPLEX TRAIT THAT POSES SIGNIFICANT CHALLENGES IN THE DEVELOPMENT OF EFFECTIVE CANCER THERAPIES
13	ACCURATELY CHARACTERIZING THE SUBPOPULATION STRUCTURE WITHIN A TUMOR IS CRUCIAL
13	ONE POSSIBLE STRATEGY IS TO ANALYZE THE DIFFERENTIAL RESPONSES OF SUBPOPULATIONS TO VARIOUS DRUGS USING LIVE CELL IMAGING HIGH THROUGHPUT DRUG SCREEN TECHNIQUES
13	HOWEVER , SUCH DATA EXHIBITS DYNAMIC VARIANCE AND POSITIVE CORRELATION IN TIME , MAKING ANALYSIS DIFFICULT TO ADDRESS THIS CHALLENGE , WE PROPOSE A STOCHASTIC MODEL BASED ON THE LINEAR BIRTH DEATH PROCESS
13	OUR NEWLY DEVELOPED MODEL CAN PROVIDE MORE PRECISE AND ROBUST ESTIMATIONS THAN THE EXISTING METHODS
13	WE CONCLUDE OUR STUDY BY TESTING OUR MODEL ON BOTH SIMULATED DATA , IN SILICO , AND EXPERIMENTAL DATA , IN VITRO , , WHICH SUPPORTS OUR ARGUMENT ABOUT ITS ADVANTAGES
13	APPLIED PROBABILITY QUALITY , STATISTICS AND RELIABILITY HEALTH APPLICATIONS SOCIETY
13	UTILIZE OR MODEL TO ANALYZE THE DATA 
14	MARKOVIAN PERSUASION WITH LIMITED HISTORICAL INFORMATION
14	WE CONSIDER A REPEATED PERSUASION SETTING WHERE A LONG LIVED SENDER PERSUADES SHORT LIVED RECEIVERS BY SHARING PAYOFF RELEVANT STATE INFORMATION
14	THE STATE TRANSITIONS ARE MARKOVIAN CONDITIONAL ON THE RECEIVERS ACTIONS , AND THE SENDER SEEKS TO MAXIMIZE THE LONG RUN AVERAGE REWARD BY COMMITTING TO A SIGNALING MECHANISM
14	WE ANALYZE THE SETTING WHERE THE RECEIVERS MAY HAVE LIMITED HISTORICAL INFORMATION AND SHOW THAT SOLVING THIS PROBLEM REQUIRES SOLVING A LARGE NON LINEAR PROGRAM
14	TO OVERCOME THIS DIFFICULTY , WE PROPOSE A ROBUST HISTORY INDEPENDENT SIGNALING MECHANISM THAT IS PERSUASIVE EVEN WHEN RECEIVERS HAVE SOME HISTORICAL KNOWLEDGE , AND IT APPROXIMATES THE OPTIMAL PAYOFF IN SETTINGS WHERE THE RECEIVERS HAVE NO HISTORICAL INFORMATION
14	APPLIED PROBABILITY REVENUE MANAGEMENT AND PRICING MANUFACTURING AND SERVICE OPERATIONS MANAGEMENT , MSOM , 
15	SOJOURN TIMES IN BERNOULLI FEEDBACK QUEUES SUBJECT TO DISASTERS
15	WE CONSIDER A QUEUEING SYSTEM WITH BATCH POISSON ARRIVALS ANDBERNOULLI FEEDBACK WHICH IS SUBJECT TO DISASTERS OCCURRING ACCORDING TO AN INDEPENDENT POISSON PROCESS
15	EACH DISASTER IS FOLLOWED BY A REPAIR PERIOD
15	THE SERVER , WHEN IDLE , TAKES REPEATED VACATIONS OF RANDOM LENGTH AND , WHILE THE SERVER IS UNDER REPAIR OR ON VACATION , DISASTERS CANNOT OCCUR
15	WE ANALYZE THIS SYSTEM AND OBTAIN THE LAPLACE TRANSFORM OF THE SYSTEM TIME DISTRIBUTION FOR A TYPICAL CUSTOMER COMPLETING SERVICE
15	A SPECIAL CASE WHERE THE SYSTEM PARAMETERS FOLLOW THE EXPONENTIAL DISTRIBUTION IS PROVIDED
15	APPLIED PROBABILITY SERVICE SCIENCE MANUFACTURING AND SERVICE OPERATIONS MANAGEMENT , MSOM , 
16	QUEUE BASED SERVICE LEVEL ESTIMATION A FINITE INTERVAL LOOKAHEAD PREDICTOR FOR THE ERLANG A MODEL WITH CUSTOMER ABANDONMENT
16	IN THIS ARTICLE , WE DEVELOP EFFECTIVE METHODOLOGIES AND ALGORITHMS FOR ESTIMATING THE SERVICE LEVEL , SL , FOR AMAZON CUSTOMER SERVICE CONTACT CENTER
16	OUR SL METRIC IS THE FRACTION OF ALL CUSTOMER ARRIVALS IN AN INTERVAL , , T , EXPERIENCING A SHORTER THAN W WAITING TIME , E G , T HOURS AND W SECONDS , 
16	OUR ALGORITHM PREDICTS THE SL IN A FORWARD LOOKING FASHION USING INPUT PARAMETERS INCLUDING THE FUTURE DEMAND FORECAST , FUTURE AGENT CAPACITY , AVERAGE HANDLING TIME , AVERAGE ABANDONMENT TIME AND REAL TIME QUEUE INFORMATION
16	APPLIED PROBABILITY SERVICE SCIENCE 
17	MODELING INTER TEMPORAL CORRELATION BETWEEN STOCHASTIC PROCESSES
17	INTER TEMPORAL CORRELATION IS PRESENT IN MULTIPLE AREAS WHERE THE STATE OF A PROCESS AT ONE TIME AFFECTS THE STATE OF ANOTHER LATER
17	SUCH EXAMPLES CAN BE FOUND IN QUEUING , DISRUPTION PROPAGATION , DELAY PROLIFERATION , ETC
17	GIVEN ITS PREVALENCE , A CONVENIENT MODEL FOR INTER TEMPORAL CORRELATION COULD BE ADVANTAGEOUS TO AID IN MANAGERIAL DECISION MAKING
17	WE PROPOSE A NEW APPROACH USING TIME SUBORDINATED MARKOV CHAINS WHEREBY INTER TEMPORAL CORRELATION CAN BE MODELED IN A MATHEMATICALLY TRACTABLE FASHION
17	WE ALSO EXTEND THE APPROACH TO MODEL PROPAGATION IN NETWORKS
17	WE DEMONSTRATE THE APPLICABILITY OF OUR APPROACH USING EXAMPLES FROM ROUTE OPTIMIZATION IN ROAD NETWORKS AND DELAY PROPAGATION IN AIRLINES
17	APPLIED PROBABILITY SIMULATION SOCIETY 
17	MY TALK HELPS DISCOVERS PATTERNS OF INTER TEMPORAL CORRELATION FROM DATA
18	HOSPITAL IN A BOX , A KEY TO WAITING LISTS REDUCTION APPLIED PROBABILITY 
19	MEAN FIELD GAMES WITH REGIME SWITCHING DYNAMICS
19	WE STUDY THE CONVERGENCE OF NASH EQUILIBRIA IN N PLAYER DIFFERENTIAL GAMES TOWARDS OPTIMAL STRATEGIES IN THE ASYMPTOTIC MEAN FIELD GAME SYSTEM , WHEN PLAYER STATES HAVE REGIME SWITCHING DYNAMICS OR MARKOV CHAIN COMMON NOISE
19	WE OBTAIN THE MASTER EQUATION , WHOSE FINITE DIMENSIONAL PROJECTIONS ARE USED TO OBTAIN THE MEAN FIELD LIMIT ALONG WITH CONVERGENCE RATES
19	APPLIED PROBABILITY 
20	BIAS IN SEQUENTIAL DECISION MAKING FOR STOCHASTIC SERVICE SYSTEMS
20	DECISION MAKERS ARE OFTEN CONFRONTED WITH MAKING A RANDOM NUMBER OF DECISIONS SEQUENTIALLY OVER TIME
20	HOW SEQUENTIAL DECISIONS ARE MADE MAY DEPEND ON THE DECISION MAKER S PERCEPTION OF PRIOR AND ANALOGOUS DECISIONS AND THEIR OUTCOMES
20	THIS PHENOMENON , KNOWN AS SEQUENTIAL BIAS , VIOLATES A CORE ASSUMPTION IN CAUSAL INFERENCE THAT THE DECISION FOR ONE PERSON DOES NOT INTERFERE WITH THE POTENTIAL OUTCOMES OF ANOTHER
20	BY CONNECTING SEQUENTIAL BIAS IN SERVICE SYSTEMS TO DYNAMIC TREATMENT REGIMES , AND EXTENDING THESE LATTER SETTINGS TO ALLOW FOR A RANDOMIZED NUMBER OF DECISIONS , WE ARE TO DEFINE AND IDENTIFY AVERAGE CAUSAL EFFECTS FOR QUANTIFYING SEQUENTIAL BIAS
20	SUBSEQUENTLY , WE PROPOSE ESTIMATORS , AND DERIVE PROPERTIES THEREOF
20	IN A CASE STUDY , WE DEMONSTRATE THAT A PROVIDER S DECISION TO ROUTE A PATIENT IN THE EMERGENCY DEPARTMENT IMPACTS THE CARE OF FUTURE PATIENTS
20	APPLIED PROBABILITY 
21	ON THE OUTPUT DYNAMICS OF THE DISCRETE TIME M G QUEUE
21	THE DEPARTURE PROCESS OF THE M G QUEUE IS A POINT PROCESS
21	HOWEVER , DECOMPOSITION METHODS OFTEN ASSUME DEPARTURE STREAMS TO BE RENEWAL , WHICH CAUSES APPROXIMATION ERRORS WHEN ANALYZING DOWNSTREAM QUEUES
21	WE INVESTIGATE THE AUTO CORRELATION OF THE DEPARTURE PROCESS TO FIND SITUATIONS WHERE THE RENEWAL ASSUMPTION IS NOT JUSTIFIED
21	WE MODEL THE M G QUEUE AS A DISCRETE TIME MARKOV CHAIN AND COMPUTE THE JOINT PROBABILITY DISTRIBUTION OF TWO DEPARTURE INSTANCES THAT ARE Τ INSTANCES APART
21	NUMERICAL RESULTS SHOW THE EFFECT OF AUTO CORRELATION ON THE RENEWAL ASSUMPTION IN DECOMPOSITION METHODS
21	APPLIED PROBABILITY 
22	SINGLE SAMPLE ESTIMATION FOR CANCER RECURRENCE
22	IN THIS WORK , WE DERIVE CONSISTENT ESTIMATORS FOR KEY PARAMETERS THAT GOVERN THE EVOLUTION OF A TUMOR CELL POPULATION IN RESPONSE TO THERAPY
22	THE THERAPY DECREASES THE POPULATION OF SENSITIVE CELLS , BUT EVENTUALLY , A POPULATION OF DRUG RESISTANT CELLS TAKES OVER , AND THE TUMOR BURDEN INCREASES AGAIN
22	WE STUDY THIS PHENOMENON USING A COLLECTION OF MATHEMATICAL MODELS OF INCREASING COMPLEXITY
22	BASED ON OUR THEORETICAL RESULTS , WE DERIVE ESTIMATORS FOR OUR MODEL PARAMETERS BASED ON A SINGLE OBSERVATION OF THE TUMOR AT THE RECURRENCE TIME
22	APPLIED PROBABILITY 
23	TAP , THE ATTENTION PATCH FOR CROSS MODAL KNOWLEDGE TRANSFER FROM UNLABELED MODALITY
23	THIS PAPER ADDRESSES A CROSS MODAL LEARNING FRAMEWORK , WHERE THE OBJECTIVE IS TO ENHANCE THE PERFORMANCE OF SUPERVISED LEARNING IN THE PRIMARY MODALITY USING AN UNLABELED , UNPAIRED SECONDARY MODALITY
23	WE SHOW THAT THE EXTRA INFORMATION CONTAINED IN THE SECONDARY MODALITY CAN BE ESTIMATED VIA NADARAYA WATSON , NW , KERNEL REGRESSION , WHICH CAN FURTHER BE EXPRESSED AS A KERNELIZED CROSS ATTENTION MODULE , UNDER LINEAR TRANSFORMATION , 
23	OUR RESULTS LAY THE FOUNDATIONS FOR INTRODUCING THE ATTENTION PATCH , TAP , , A SIMPLE NEURAL NETWORK ADD ON THAT ALLOWS DATA LEVEL KNOWLEDGE TRANSFER FROM THE UNLABELED MODALITY
23	WE PROVIDE EXTENSIVE NUMERICAL SIMULATIONS USING FOUR REAL WORLD DATASETS TO SHOW THAT TAP CAN PROVIDE STATISTICALLY SIGNIFICANT IMPROVEMENT IN GENERALIZATION ACROSS DIFFERENT DOMAINS AND DIFFERENT NEURAL NETWORK ARCHITECTURES
23	ARTIFICIAL INTELLIGENCE APPLIED PROBABILITY DATA MINING
23	OUR WORKS INTRODUCES A NEW WAY TO USE CROSS MODAL DATA FOR DECISION MAKING 
24	MULTI AGENT AND MULTI OBJECTIVE MULTI ARMED BANDIT
24	EXP BASED ALGORITHMS ARE OFTEN USED FOR EXPLORATION IN NON STOCHASTIC BANDIT PROBLEMS ASSUMING REWARDS ARE BOUNDED
24	MOTIVATED BY THE RECENT ADVANCEMENTS IN REINFORCEMENT LEARNING , RL , WITH REWARDS OF ANY SCALE , WE PROPOSE A NEW ALGORITHM , NAMELY EXP P , AND EXTEND EXP P FROM BANDIT TO RL TO INCENTIVIZE EXPLORATION
24	FURTHERMORE , WE STUDY PARETO OPTIMALITY IN MULTI OBJECTIVE MULTI ARMED BANDIT BY PROVIDING A FORMULATION OF ADVERSARIAL SETTINGS AND DEFINING ITS PARETO REGRETS THAT CAN BE APPLIED TO BOTH STOCHASTIC AND ADVERSARIAL SETTINGS
24	WE ALSO PRESENT NEW , NEARLY , OPTIMAL ALGORITHMS
24	LASTLY , WE STUDY A DECENTRALIZED MULTI AGENT MULTI ARMED BANDIT PROBLEM IN WHICH MULTIPLE CLIENTS ARE CONNECTED BY GRAPHS
24	WE INTRODUCE A NOVEL ALGORITHMIC FRAMEWORK AND DERIVE , NEARLY , OPTIMAL INSTANCE DEPENDENT AND INSTANCE FREE REGRET UPPER BOUNDS
24	ARTIFICIAL INTELLIGENCE APPLIED PROBABILITY DECISION ANALYSIS SOCIETY
25	TOWARDS AN UNDERSTANDING OF CONTINUED USE OF CONVERSATIONAL AI , AN INTEGRATED FRAMEWORK
25	THE RISE OF CONVERSATIONAL AI , CA , HAS REVOLUTIONIZED HOW INDIVIDUALS INTERACT WITH INFORMATION TECHNOLOGY
25	RECENTLY , CHATGPT , IS EXPECTED TO BE A GAME CHANGER WITH THE POTENTIAL TO IMPACT EVERY ASPECT OF OUR SOCIETY DUE TO ITS CAPABILITY TO PROVIDE DETAILED RESPONSES TO VARIOUS REQUESTS
25	HOWEVER , THERE EXIST APPREHENSIONS CONCERNING THE VALIDITY AND FAIRNESS OF AI GENERATED CONTENT , AS WELL AS PERSONAL DEVELOPMENT WHEN USING CA
25	WHILE PREVIOUS RESEARCH HAS FOCUSED ON THE INITIAL ADOPTION OF A CA TOOL , THERE IS A LIMITED UNDERSTANDING OF USERS ATTITUDES TOWARD CONTINUED USE OF CA AFTER THEY HAVE ASSESSED THE IMPACT OF CA ON THEIR TASK PERFORMANCE AND PERSONAL DEVELOPMENT
25	TO FILL THIS GAP , THIS STUDY EXAMINES USERS POSITIVE AND NEGATIVE EXPERIENCES OF USING CA THROUGH THE LENS OF THE EXPECTATION CONFIRMATION MODEL AND INNOVATION RESISTANCE LITERATURE
25	ARTIFICIAL INTELLIGENCE BEHAVIORAL OPERATIONS MANAGEMENT INFORMATION SYSTEMS
26	LEVEREGING QUANTILE REGRESSION IN CAPACITY PLANNING FOR COLD STORAGE COMPANY
26	THIS RESEARCH EXPLORES THE CRITICAL ISSUE OF CAPACITY PLANNING FOR COLD STORAGE COMPANIES , AN INCREASINGLY PRESSING CONCERN GIVEN THE CURRENT CAPACITY SHORTAGES BEING EXPERIENCED WITHIN THE UNITED STATES
26	TO TACKLE THIS ISSUE , WE EMPLOY LINEAR QUANTILE REGRESSION AS WELL AS IMPLEMENT PINBALL LOSS WITH THE GRADIENT BOOSTING ALGORITHM
26	QUANTILE REGRESSION PROVIDES AN INSIGHTFUL WAY TO MODEL THE COMPLEX RELATIONSHIPS BETWEEN VARIOUS FACTORS INFLUENCING CAPACITY , ALLOWING FOR A MORE NUANCED UNDERSTANDING THAN TRADITIONAL MEAN REGRESSION METHODS
26	BY FOCUSING ON DIFFERENT QUANTILES , WE CAN BETTER PREDICT BOTH AVERAGE SCENARIOS AND OUTLIERS , THUS ENSURING OPTIMAL RESOURCE ALLOCATION AND PLANNING IN A RANGE OF SITUATIONS
26	ARTIFICIAL INTELLIGENCE DATA MINING APPLIED PROBABILITY 
26	BY LEVERAGING THE WEALTH OF DATA AVAILABLE , WE ARE ABLE TO BETTER PREDICT A VARIETY OF OUTCOMES AND 
27	INVESTIGATING DISTANCE DECAY AND SOCIAL DETERMINANTS ON HEALTHCARE OUTCOMES USING META ENSEMBLES PREDICTIVE MODELS IN BROOME COUNTY , NY
27	TO IMPROVE ACCESS TO HEALTHCARE , ISSUES ASSOCIATED WITH DISTANCE DECAY AND SOCIAL DETERMINANTS NEED TO BE ADDRESSED
27	IN THIS WORK WE DEVELOPED AN AUTOMATED ARTIFICIAL INTELLIGENCE APPLICATION TO GENERATE A LIST OF PATIENTS WHO COULD BENEFIT FROM INTERVENTIONS TO IMPROVE THEIR HEALTHCARE OUTCOMES
27	WE INSPECTED THE EFFECT OF DISTANCE DECAY ON HEALTHCARE OUTCOMES BY PERFORMING META ENSEMBLES PREDICTIVE MODELS
27	DATA USED IN THIS PAPER IS RETRIEVED FROM A LOCAL HOSPITAL IN BROOME COUNTY , NY
27	PROPOSED MODELS WERE EVALUATED FOR GENERALIZABILITY
27	THE STACKED MODEL , RF NB NNET , GBM TOP LAYER , OUTPERFORMED THE REST OF THE MODELS
27	THE MODEL IDENTIFIED CONTRIBUTING FACTORS TO POOR HEALTH OUTCOMES , SUCH AS UNAVAILABILITY OF TRANSPORTATION , NO SHOW RATE , INSURANCE TYPE , AND TRAVEL DISTANCE
27	THE DEVELOPED APPLICATION IS USED BY POPULATION HEALTH NURSES FOR OUTREACH PURPOSES
27	ARTIFICIAL INTELLIGENCE DATA MINING DIVERSITY , EQUITY , AND INCLUSION
28	SUB BIUX X SUB 
28	WIND ENERGY PLAYS A CRUCIAL COMPONENT IN THE CONTEST TO FULFILL ENVIRONMENTAL CONTROL OBJECTIVES
28	WIND ENERGY , ON THE OTHER HAND , WILL ONLY BE ABLE TO FULFILL ITS ESSENTIAL IMPORTANCE IF THE WIND TURBINES WORK EFFICIENTLY
28	THE PAPER AIMS TO ANALYZE THE APPLICATION OF ARTIFICIAL INTELLIGENCE , AI , ALGORITHMS IN WIND SPEED
28	IN THIS PAPER , THREE NETWORK PARAMETER OPTIMIZATION ALGORITHMS , ADAGRAD , RMSPROP , AND ADAM , ARE IMPLEMENTED AND COMPARED IN THE CONTEXT OF WIND SPEED FORECASTING
28	THIS PAPER EMPLOYS WIND SPEED DATA OBTAINED FROM SAUDI ARABIA
28	MEAN ABSOLUTE ERROR , MAE , , MEAN SQUARE ERROR , MSE , , ROOT MEAN SQUARE ERROR , RMSE , , AND R SQUARED ARE THE FOUR METRICS USED TO ASSESS PERFORMANCE
28	THE EXPERIMENT RESULTS SHOW THAT THE ADAM ALGORITHM OUTPERFORMS THE OTHER OPTIMIZATION ALGORITHMS REGARDING FORECASTING ACCURACY AND TRAINING TIME
28	ARTIFICIAL INTELLIGENCE DATA MINING ENRE , ENERGY
29	PHD CANDIDATE
29	CANCER RESULTS FROM GENETIC MUTATIONS DISRUPTING CELL GROWTH AND CAN LEAD TO THE FORMATION OF TUMORS
29	BREAST CANCER IS THE MOST COMMON CANCER IN WOMEN
29	MICROARRAY TECHNOLOGY ENABLES SCIENTISTS TO MEASURE THE ACTIVITY OF THOUSANDS GENES SIMULTANEOUSLY , BUT ANALYZING THE DATA CAN BE CHALLENGING , ESPECIALLY WHEN THERE IS MANY GENETIC INFORMATION BUT LIMITED OBSERVATION DATA
29	IN THIS STUDY , A NOVEL GRAPH NEURAL NETWORK IS DEVELOPED TO PREDICT THE SURVIVAL TIME OF PATIENTS WITH BREAST CANCER
29	THE MODEL INCORPORATES THE PATIENT S AGE AT DIAGNOSIS AND WHETHER THEY HAVE A MUTATION IN A GENE ASSOCIATED WITH BREAST CANCER
29	THE PROPOSED APPROACH MAY PROVIDE INSIGHTS INTO BREAST CANCER SURVIVAL PREDICTION AND COULD BE USEFUL IN DEVELOPING PERSONALIZED TREATMENT PLANS
29	ARTIFICIAL INTELLIGENCE DATA MINING HEALTH APPLICATIONS SOCIETY
30	PREDICTING CERVICAL CANCER WITH MACHINE LEARNING ALGORITHMS , A STUDY ON THE EFFECTIVENESS OF SAMPLING METHODS 
30	MACHINE LEARNING ALGORITHMS HAVE BEEN STUDIED TO PREDICT THE LIKELIHOOD OF CERVICAL CANCER
30	THE DATASET WAS ANALYZED WITH UNDER SAMPLING , OVER SAMPLING , AND NO SAMPLING
30	LOGISTIC REGRESSION , SVM , AND RANDOM FOREST WERE BUILT TO COMPARE THE PREDICTION PERFORMANCE OF FOUR TARGETS , BIOPSY , CYTOLOGY , HINSELMANN , AND SCHILLER , WITH AND WITHOUT SAMPLING TECHNIQUES
30	THE DATA HAS BEEN PREPROCESSED
30	THE RESULTS SHOWED THAT OVER SAMPLING HAD THE BEST PREDICTION PERFORMANCE , AND NO SAMPLING AND UNDER SAMPLING NEED IMPROVEMENT
30	THE MACHINE LEARNING MODELS WERE CAPABLE OF PREDICTING THE LIKELIHOOD OF CERVICAL CANCER IN THE FUTURE
30	ARTIFICIAL INTELLIGENCE DATA MINING HEALTH APPLICATIONS SOCIETY
31	TRACKING EARLY HEART DISEASE USING DEEP LEARNING FOR SMALL AND IMBALANCED DATASETS
31	HEART DISEASE IS A LEADING CAUSE OF MORTALITY IN THE US , WITH CORONARY ARTERY DISEASE , CAD , BEING THE MOST COMMON FORM
31	IN THIS RESEARCH , WE PROPOSED A METHODOLOGY THAT USES MACHINE LEARNING AND DEEP LEARNING METHODS TO TRACK STENOSIS IN EACH CORONARY ARTERY
31	OUR FRAMEWORK APPLIED AUTOENCODER , AE , , SMOTE , AND CONVENTIONAL NEURAL NETWORKS , CNN , TO BALANCE AND GENERATE DATA FOR MORE ACCURATE DETECTION IN EARLY STAGES
31	OUR RESULTS DEMONSTRATED THAT THE ACCURACY OF THIS PROPOSED METHOD FOR CAD DIAGNOSIS IN EARLY STAGES WAS AND WAS HIGHER THAN RANDOM FOREST , RF , , DECISION TREE , DT , , SUPPORT VECTOR MACHINE , SVM , , LOGISTIC REGRESSION , LR , , XGBOOST , AND ARTIFICIAL NEURAL NETWORKS , ANN , 
31	THIS METHODOLOGY COULD BE DEVELOPED IN VARIETY HEALTHCARE AND MEDICINE APPLICATIONS TO HANDLE IMBALANCED AND SMALL DATASETS
31	ARTIFICIAL INTELLIGENCE DATA MINING HEALTH APPLICATIONS SOCIETY
32	A HYBRID APPROACH TO VETERINARY CLINICAL DECISION SUPPORT SYSTEMS
32	VETERINARY CLINICAL DECISION SUPPORT SYSTEMS , CDSSS , ARE ESSENTIAL TOOLS FOR IMPROVING THE QUALITY OF CARE FOR ANIMALS
32	HOWEVER , TRADITIONAL CDSSS FACE UNIQUE CHALLENGES DUE TO THE RELIANCE ON UNSTRUCTURED MEDICAL RECORDS AND THE ABSENCE OF DIRECT PATIENT COMMUNICATION
32	TO ADDRESS THESE ISSUES , WE PROPOSE A HYBRID APPROACH THAT COMBINES THE STRENGTHS OF THREE DIFFERENT TYPES OF MODELS , RULE BASED MODELS , LLMS , AND XAI
32	RULE BASED MODELS IMPLEMENT CLINICAL GUIDELINES AND BEST PRACTICES
32	LLMS EXTRACT INSIGHTS FROM UNSTRUCTURED MEDICAL RECORDS
32	XAI EXPLAINS CLINICAL DECISIONS
32	WE EVALUATED OUR APPROACH ON VETERINARY MEDICAL RECORDS
32	OUR RESULTS SHOWED THAT OUR APPROACH SIGNIFICANTLY OUTPERFORMED TRADITIONAL CDSSS IN TERMS OF ACCURACY , EXPLAINABILITY , AND TRANSPARENCY
32	ARTIFICIAL INTELLIGENCE DATA MINING INFORMATION SYSTEMS
33	RECOGNITION OF SUPER AGERS AND COGNITIVE DECLINERS WITH FMRI AND SMRI CLASSIFICATION STUDY ON ADNI
33	THE DECLINE IN MULTIPLE COGNITIVE DOMAINS IS CONSIDERED THE NORMAL PART OF THE AGING PROCESS
33	HOWEVER , OLDER INDIVIDUALS SHOW VARIATION IN THE COGNITIVE TRAJECTORIES PATTERNS IN THEIR LIFETIME
33	FURTHERMORE , ADULTS AGED YEARS OR OLDER , CALLED SUPER AGER , SHOWED COGNITIVE FUNCTIONS AT LEAST AS GOOD AS MIDDLE AGED ADULTS
33	IN THIS STUDY ON THE ADNI DATABASE , WE DEVELOPED CLASSIFICATION MODELS TO DISTINGUISH SUPER AGERS FROM NORMAL COGNITIVE DECLINERS USING STRUCTURAL BRAIN MAGNETIC IMAGING RESONANCE , SMRI , AND FUNCTIONAL MAGNETIC IMAGING RESONANCE , FMRI , FEATURES
33	UNDERSTANDING THE DIFFERENCES IN NEUROBIOLOGICAL FEATURES PROVIDES THE KNOWLEDGE TO RESIST COGNITIVE DECLINE IN HEALTHY PEOPLE AND MITIGATE ALZHEIMER S DISEASE
33	ARTIFICIAL INTELLIGENCE DATA MINING MACHINE LEARNING FOR OPTIMIZATION
34	IMPROVING TRANSLATION OF VISIBLE TO THERMAL IMAGES USING GAN IN ADVERSE WEATHER CONDITIONS
34	THE USE OF VISIBLE AND INFRARED IMAGES CAN ENHANCE THE PERFORMANCE OF OBJECT RECOGNITION METHODS , PARTICULARLY UNDER DIFFERENT WEATHER CONDITIONS
34	HOWEVER , THERE IS A LACK OF PUBLICLY AVAILABLE DATASETS WITH LABELED INFRARED IMAGES
34	IN THIS WORK , WE USE GENERATIVE ADVERSARIAL NETWORKS , GANS , TO PERFORM VISIBLE TO INFRARED IMAGE TRANSLATION AND IMPROVE THE LABELING OF INFRARED IMAGES
34	WE PERFORM VARIOUS ANALYSES BASED ON DIFFERENT WEATHER CONDITIONS SUCH AS CLEAR , FOGGY , AND RAINY TO ASSIST IN THE DEVELOPMENT OF OBJECT RECOGNITION METHODS SUITABLE FOR ADVERSE WEATHER CONDITIONS
34	ARTIFICIAL INTELLIGENCE DATA MINING MACHINE LEARNING IN OPERATIONS
35	DEVELOPMENT OF EXPLAINABLE ANOMALY DETECTION ALGORITHM FOR MULTI SENSORS USING DEEP LEARNING THE SURGE IN THE INTERNET OF THINGS , IOT , HAS AMPLIFIED AUTOMATED SERVICES POTENTIAL , WITH ANOMALY DETECTION BEING A KEY APPLICATION
35	TRADITIONAL MACHINE LEARNING FACES HURDLES WITH INTRICATE MULTI SENSOR DATA , AND WHILE DEEP LEARNING CAN NAVIGATE THESE , IT FREQUENTLY LACKS DECISION TRANSPARENCY
35	THIS PAPER PRESENTS AN EXPLAINABLE DEEP LEARNING BASED MULTI SENSOR ANOMALY DETECTION METHOD , INCORPORATING A DEEP EMBEDDED CLUSTERING , DEC , ALGORITHM FOR ENHANCED ANOMALY DETECTION PERFORMANCE AND EXPLAINABILITY VIA EXPLAINABLE AI , XAI , TECHNIQUES
35	EXPERIMENTAL RESULTS ILLUSTRATE AN IMPROVEMENT IN PERFORMANCE COMPARED TO EXISTING METHODS BY AUGMENTING THE COMPREHENSIBILITY OF DECISION MAKING VIA XAI
35	FURTHERMORE , WE EVALUATED REAL WORLD MULTI SENSOR DATA , VALIDATING ITS EFFECTIVENESS IN IMPROVING DECISION MAKING TRANSPARENCY
35	ARTIFICIAL INTELLIGENCE DATA MINING MACHINE LEARNING IN OPERATIONS
36	REAL TIME OBJECT DETECTION AND TRAFFIC SIMULATION OF AUTONOMOUS VEHICLE DEPLOYMENT 
36	AUTOMATED AND AUTONOMOUS VEHICLES HAVE THE POTENTIAL TO REVOLUTIONIZE TRANSPORTATION BUT IN THE ABSENCE OF INTERCONNECTION AND DATA SHARING BETWEEN VEHICLES POSE CHALLENGES TO URBAN NETWORKS
36	BUSINESS MODELS OF ON DEMAND AND PRIVATELY OWNED AUTONOMOUS VEHICLES , AVS , HAVE THE POTENTIAL TO SIGNIFICANTLY IMPACT TRAFFIC VOLUME AND VEHICLE MILES TRAVELED , VMT , 
36	IN THIS PAPER WE DEVELOP A MODEL USING STATE OF THE ART ALGORITHMS TO DETECT AND TRACK AUTONOMOUS CARS USING EXISTING CAMERA INFRASTRUCTURE
36	THE RESULTS ARE USED AS AN INPUT INTO A VISUALIZATION PLATFORM THAT SIMULATES SCENARIOS AROUND TRAFFIC VOLUME
36	OUR WORK IS A STEP TOWARDS FILLING THE CURRENT VOID IN DATA FOR TRAVEL AND TRAFFIC PATTERNS SURROUNDING AVS
36	ARTIFICIAL INTELLIGENCE DATA MINING MACHINE LEARNING IN OPERATIONS
36	THE TALK DEVELOPS A COMPUTER VISION MODEL THAT USES LARGE IMAGE DATASETS AND OPTIMIZES 
37	THE EFFECT OF COVID ON COPD PATIENT S READMISSION AND ITS PREDICTORS
37	CHRONIC OBSTRUCTIVE PULMONARY DISEASE , COPD , IS A PROGRESSIVE LUNG DISEASE AMONG THE TOP THREE CAUSES OF DEATH IN THE US
37	IDENTIFYING RISK FACTORS FOR COPD PATIENTS READMISSION AND REDUCING IT HAS BECOME EVEN MORE CRITICAL SINCE THE START OF THE COVID PANDEMIC
37	IN THIS STUDY , WE USE A NATIONWIDE DATASET AND MACHINE LEARNING TECHNIQUES TO DEVELOP A NOVEL READMISSION PREDICTION MODEL , AND THE BAYESIAN OPTIMIZATION METHOD IS USED TO FIND THE MOST OPTIMAL HYPERPARAMETERS IN EACH MODEL
37	ARTIFICIAL INTELLIGENCE DATA MINING MSOM , HEALTHCARE
38	NATURAL LANGUAGE PROCESSING , NLP , BASED NEURAL NETWORK ARCHITECTURE TO PROCESS THE G , E AND APSIM INPUTS AND THEIR INTERACTIONS FOR YIELD PREDICTION
38	THIS STUDY PROPOSES A NATURAL LANGUAGE PROCESSING , NLP , BASED NEURAL NETWORK ARCHITECTURE FOR YIELD PREDICTION BY PROCESSING THE GENOTYPE , G , , ENVIRONMENT , E , , AND APSIM INPUTS ALONG WITH THEIR INTERACTIONS
38	THE PROPOSED MODEL UTILIZES A COMBINATION OF NLP TECHNIQUES AND NEURAL NETWORK ARCHITECTURES TO PROCESS TEMPORAL AND TEXTUAL INFORMATION AND EXTRACT USEFUL FEATURES FOR YIELD PREDICTION
38	THE STUDY USES A PUBLICLY AVAILABLE DATASET CONTAINING G , E , AND APSIM INPUTS ALONG WITH CORRESPONDING YIELD VALUES TO EVALUATE THE PROPOSED MODEL
38	THE EXPERIMENTAL RESULTS DEMONSTRATE THAT THE PROPOSED APPROACH ACHIEVES SUPERIOR PERFORMANCE COMPARED TO EXISTING STATE OF THE ART MODELS
38	THE PROPOSED MODEL NOT ONLY CAPTURES THE COMPLEX INTERACTIONS BETWEEN THE INPUT VARIABLES BUT ALSO PROVIDES INSIGHTS INTO THE UNDERLYING FACTORS INFLUENCING CROP YIELD PREDICTION
38	ARTIFICIAL INTELLIGENCE DATA MINING OPT , MACHINE LEARNING
39	INVESTIGATE PREDICTION POSSIBILITY OF CYBERATTACKS ON BLOCKCHAIN NETWORKS BLOCKCHAIN TECHNOLOGY PROMISES A NEW DIMENSION OF CONDUCTING BUSINESS TRANSACTIONS AMONG UNTRUSTED ENTITIES , ITS FEATURES SUPPORTING VERIFICATION , IDENTIFICATION , AUTHENTICATION , INTEGRITY , AND IMMUTABILITY ARE GUARANTEED THROUGH CRYPTOGRAPHY , DECENTRALIZED SMART CONTRACTS , AND SMART LEDGERS
39	THERE HAVE BEEN MANY CYBERSECURITY INCIDENTS ON BLOCKCHAIN NETWORKS
39	BLOCKCHAIN EXCHANGES ARE THE PRIME TARGETS THAT SUFFER MOST OF THE ATTACKS WITH A SIGNIFICANT AMOUNT OF LOSS
39	APART FROM THE ENHANCED CRYPTOGRAPHY TECHNIQUES FOR INTEGRITY , DEALING WITH MALWARE AND OTHER ACTIVE THREATS IS REQUIRED IN WORKING TOWARD FUTURE IMPLEMENTATIONS
39	FINALLY , WE BELIEVE THAT THE DETECTION OF VULNERABILITIES ON BLOCKCHAIN NETWORKS AND TEACHING MACHINES TO PREDICT NEW ONES ARE QUITE IMPORTANT TO ENSURE THAT TRUST AND PRIVACY PRESERVING ATTRIBUTES OF THE USERS ARE MAINTAINED
39	ARTIFICIAL INTELLIGENCE DATA MINING OPT , NETWORK OPTIMIZATION
40	THE IMPACT OF PRIVACY DATA UTILIZATION AND PROTECTION ON ENTERPRISES PERFORMANCE , A STRUCTURAL EQUATION MODELING APPROACH
40	THE DEVELOPMENT OF BIG DATA AND AI TECHNOLOGIES HAS DRIVEN ENTERPRISES TO BENEFIT FROM ACCURATE ANALYSIS OF USER DATA
40	HOWEVER , IT HAS ALSO RAISED CONCERNS ABOUT PRIVACY DATA SECURITY
40	THUS , THIS RESEARCH AIMS TO EXPLORE THE IMPACT OF ENTERPRISE USAGE AND PROTECTION OF USER PRIVACY DATA ON BUSINESS PERFORMANCE
40	HYPOTHESES AND MEASUREMENT SCALES OF THIS RESEARCH WILL BE DESIGNED FROM THE PERSPECTIVES OF BOTH ENTERPRISES AND USERS , BY USING THE PRIVACY RISK PERCEPTION PROCESS
40	FURTHERMORE , A STRUCTURAL EQUATION MODEL WILL BE USED FOR EMPIRICAL TESTING , IN ORDER TO OPTIMIZE ENTERPRISES UTILIZATION AND PROTECTION STRATEGIES OF PRIVATE DATA IN THE DATA REVOLUTION
40	ARTIFICIAL INTELLIGENCE DATA MINING SOCIAL MEDIA ANALYTICS
40	IT IS ABOUT THE USAGE AND PROTECTION OF THE PRIVATE DATA OF USERS
41	DECISION SUPPORT TOOL FOR EONR COMBING CROP SIMULATION AND ML MODEL
41	KNOWLEDGE OF THE ECONOMIC OPTIMUM NITROGEN RATE , EONR , IN FARM MANAGEMENT IS CRUCIAL AND CAN HELP IMPROVE NITROGEN EFFICIENCY WHILE REDUCING ENVIRONMENTAL IMPACT
41	IT IS CHALLENGING TO DETERMINE EONR SINCE IT VARIES BASED ON SITE LOCATION , MANAGEMENT PRACTICE , WEATHER , AND SOIL PROPERTIES
41	FURTHERMORE , THE DATA AVAILABILITY IS LIMITED TO BUILDING A MACHINE LEARNING , ML , MODEL TO DETERMINE EONR
41	WE PROPOSE A DECISION SUPPORT TOOL TO DETERMINE EONR , WHERE THE ML MODELS ARE TRAINED ON CROP MODELS , APSIM , SIMULATION OUTPUTS AND HISTORICAL WEATHER DATA
41	THE SIMULATION OUTPUTS WERE GENERATED WITH VARYING MANAGEMENT , WEATHER , AND GENOTYPE PROPERTIES TO HAVE ROBUST DATA
41	WE BUILD A RANDOM FOREST MULTI TARGET REGRESSION , RFMTR , MODEL TO PREDICT YIELD AND EONR FOR A SPECIFIC LOCATION
41	THE MODEL WAS EVALUATED FOR WITH AN RRMSE OF AND , RESPECTIVELY
41	ARTIFICIAL INTELLIGENCE DATA MINING TECHNOLOGY , INNOVATION MANAGEMENT AND ENTREPRENEURSHIP
41	IN THIS RESEARCH WE ARE USING ML TO BUILD DECISION SUPPORT TO FARM MANAGEMENT USING HISTORICAL DATA 
42	IMPROVING KNOWLEDGE DISTILLATION FOR REGRESSION UNDER DATA INSUFFICIENCY
42	KNOWLEDGE DISTILLATION , KD , HAS BEEN SUCCESSFUL IN COMPRESSING A LARGE TEACHER NETWORK INTO A SMALLER STUDENT NETWORK
42	HOWEVER , CONVENTIONAL KD METHODS CAN SUFFER FROM PERFORMANCE DEGRADATION WHEN THE ORIGINAL TRAINING DATASET IS NOT FULLY REUSABLE
42	WE PROPOSE A TEACHER STUDENT MATCHING METHOD TO IMPROVE KD UNDER DATA INSUFFICIENCY FOR REGRESSION
42	THE PROPOSED METHOD ENHANCES AN EXISTING KD METHOD BY INTRODUCING THREE ADDITIONAL LEARNING OBJECTIVES TO MAKE THE STUDENT NETWORK BETTER EMULATE THE PREDICTION CAPABILITY OF THE TEACHER NETWORK , PERTURBATION BASED MATCHING , ADVERSARIAL BELIEF MATCHING , AND GRADIENT MATCHING
42	THROUGH EXPERIMENTS USING BENCHMARK REGRESSION DATASETS , WE DEMONSTRATE THAT THE PROPOSED METHOD CAN IMPROVE THE PREDICTIVE PERFORMANCE OF THE STUDENT NETWORK , ESPECIALLY WHEN ONLY A SMALL PART OF THE TRAINING DATASET IS USABLE
42	ARTIFICIAL INTELLIGENCE DATA MINING 
43	GROUP SPARSE AUTOENCODER ARTIFICIAL INTELLIGENCE DATA MINING 
44	ADVANCING ROOT CAUSE ANALYSIS WITH CAUSAL INFERENCE USING BOOSTING TREES AND TOPOLOGICAL DATA ANALYSIS
44	CAUSAL INFERENCE IS VITAL ACROSS MANY FIELDS , BUT IT S CHALLENGING DUE TO CONFOUNDING EFFECTS , SELECTION BIAS , AND OTHER FACTORS
44	MACHINE LEARNING TECHNIQUES , SUCH AS BOOSTING TREES , IS HELPFUL BECAUSE IT HANDLES HIGH DIMENSIONAL DATA AND NONLINEAR RELATIONSHIPS
44	TOPOLOGICAL DATA ANALYSIS , TDA , IS ALSO PROMISING , AS IT UNCOVERS COMPLEX STRUCTURES AND PATTERNS IN DATA
44	WE PROPOSE A NOVEL FRAMEWORK FOR CAUSAL INFERENCE THAT COMBINES BOOSTING TREES AND TDA
44	WE USE BOOSTING TREES TO ESTIMATE CAUSAL EFFECTS AND TDA TO IDENTIFY POTENTIAL CAUSAL PATHWAYS AND MECHANISMS
44	OUR APPROACH PROVIDES ACCURATE CAUSAL INFERENCE AND DEEPER INSIGHTS INTO THE DATA
44	ARTIFICIAL INTELLIGENCE EMERGING TECHNOLOGIES AND APPLICATIONS DATA MINING
44	OUR CAUSAL INFERENCE BASED APPROACH WILL IMPROVE SEMICONDUCTOR YIELD THROUGH TIMELY REMEDIATION 
45	EXTRACTING INSIGHTS FROM CITIES WITH GRAPH NEURAL NETWORKS
45	MODELING AND OPTIMIZING CITIES IS A CHALLENGING TASK DUE TO THEIR COMPLEX AND INTERCONNECTED NATURE
45	GRAPH TOPOLOGIES AND GRAPH NEURAL NETWORKS , GNN , OFFER A PROMISING FRAMEWORK FOR REPRESENTING CITIES , LEVERAGING THEIR INHERENT HETEROGENEITY AND DYNAMICITY
45	HOWEVER , IMPLEMENTING EFFICIENTLY GNNS IS COMPLEX AS EXISTING APPROACHES STRUGGLE TO UNCOVER THE UNDERLYING CAUSE EFFECT RELATIONSHIPS
45	TO ADDRESS THIS LIMITATION , OUR WORK INTRODUCES A CAUSAL GRAPH DISCOVERY MECHANISM CAPABLE OF IDENTIFYING THE CAUSAL PROCESSES
45	WE CONDUCTED EXPERIMENTS TO EVALUATE THE FRAMEWORK S EFFECTIVENESS IN ACCURATELY REPRESENTING COMPLEX SYSTEMS AND ITS SCALABILITY TO HANDLE LARGE SCALE SCENARIOS
45	TWO CASE STUDIES FOCUSING ON TRANSPORTATION AND BUILDINGS IN SMARTER CITIES WERE EXAMINED , AND THE RESULTS DEMONSTRATE THE CAPABILITIES OF OUR APPROACH
45	ARTIFICIAL INTELLIGENCE EMERGING TECHNOLOGIES AND APPLICATIONS ENRE , ENERGY
46	A REINFORCEMENT LEARNING APPROACH FOR VEHICLE ROUTING PROBLEM WITH DRONES
46	MANY EXACT ALGORITHMS , HEURISTICS , AND METAHEURISTICS HAVE BEEN PROPOSED TO SOLVE THE I VEHICLE ROUTING PROBLEM WITH DRONES I , VRPD , , WHICH INVOLVES USING A FLEET OF HETEROGENEOUS VEHICLES TO FULFILL CUSTOMER ORDERS IN LAST MILE DELIVERY
46	WE FORMULATE THIS PROBLEM USING THE I MARKOV DECISION PROCESS I , MDP , AND PROPOSE A I REINFORCEMENT LEARNING I , RL , MODEL TO SOLVE IT , AIMING TO OBTAIN HIGH QUALITY SOLUTIONS FOR BOTH SMALL AND LARGE INSTANCES
46	OUR RL MODEL IS BASED ON AN ATTENTION BASED ENCODER DECODER ARCHITECTURE , ENABLING US TO CAPTURE EVERY ACTION TAKEN BY ANY AGENT IN THE ENVIRONMENT
46	THIS APPROACH ENHANCES COORDINATION , DETERMINING WHICH VEHICLES SHOULD VISIT SPECIFIC CUSTOMERS AND WHERE VEHICLES CAN RENDEZVOUS TO EFFECTIVELY LEVERAGE DRONES AND REDUCE THE OVERALL COMPLETION TIME
46	OUR EXPERIMENTS PRODUCE COMPETITIVE RESULTS WHEN COMPARED TO BENCHMARK ALGORITHMS
46	ARTIFICIAL INTELLIGENCE EMERGING TECHNOLOGIES AND APPLICATIONS OPT , MACHINE LEARNING
47	INTELLIGENT CT SCANNER PARAMETER SELECTION USING AI POWERED RECOMMENDER SYSTEM
47	IN THIS STUDY , A MACHINE LEARNING BASED RECOMMENDER SYSTEM FOR CT SCANNER PARAMETER SELECTION IS PROPOSED FOR RECOMMENDING OPTIMAL SCAN PARAMETERS
47	AS PREDICTING SCAN FEASIBILITY USING MACHINE LEARNING METHODS IS AT THE HEART OF THE PROPOSED RECOMMENDER SYSTEM , THE ACCURACY OF FOUR ML METHODS IN PREDICTING SCAN FEASIBILITY IS COMPARED
47	THE RESULTS INDICATE THAT MULTI LAYER PERCEPTRON PREDICTED SCAN FEASIBILITY WITH HIGHER ACCURACY AND OUTPERFORMED THE OTHER METHODS
47	FURTHERMORE , A GAME THEORETIC APPROACH WAS UTILIZED TO EXPLAIN THE PREDICTIONS PROVIDED BY THE MODEL
47	ARTIFICIAL INTELLIGENCE EMERGING TECHNOLOGIES AND APPLICATIONS OPT , MACHINE LEARNING
48	PERSONIFICATION OF ARTIFICIAL INTELLIGENCE AGENTS AND STEREOTYPE THREATS
48	ACADEMIC DISCUSSIONS REGARDING THE ETHICAL USE OF ARTIFICIAL INTELLIGENCE , AI , , TYPICALLY FOCUS ON PREVENTING CONSUMERS FROM BEING EXPOSED TO THE ACTIVE PATHWAYS OF AI GENERATED HARM
48	THIS STUDY CONTRIBUTES TO THE LITERATURE BY INVESTIGATING THE PASSIVE PATHWAYS OF POTENTIAL STEREOTYPE THREATS WHEN AI HAS PERSONIFIED CHARACTERS
48	WE EMPIRICALLY INVESTIGATE WHETHER AND TO WHAT EXTENT STEREOTYPE THREATS NEGATIVELY AFFECT CONSUMERS OBJECTIVES WHEN THEY INTERACT WITH PERSONIFIED AI AGENTS
48	WE FIND THAT FEMALE CONSUMERS SUFFER FROM GENDER STEREOTYPE THREATS WHEN INTERACTING WITH AI AGENTS DESIGNED AS MALE IN THE STEM DOMAIN , WHERE FEMALES ARE EXPECTED TO PERFORM WORSE THAN MALES
48	OUR FINDINGS SUGGEST THAT COMPANIES INTRODUCING AI BASED SERVICES SHOULD CONSIDER POTENTIAL NEGATIVE EFFECTS ARISING FROM MISMATCHES BETWEEN CONSUMERS AND AI AGENTS IN SOCIAL DIMENSIONS
48	ARTIFICIAL INTELLIGENCE EMERGING TECHNOLOGIES AND APPLICATIONS TECHNOLOGY , INNOVATION MANAGEMENT AND ENTREPRENEURSHIP
49	TARGETED DYNAMIC ELECTRICITY PRICING , A DEEP REINFORCEMENT LEARNING APPROACH FOR PEAK LOAD MANAGEMENT IN SMART GRIDS
49	THIS STUDY DELVES INTO PEAK LOAD MANAGEMENT STRATEGIES WITHIN ELECTRICITY NETWORKS , FOCUSING ON DEMAND RESPONSE STRATEGIES FOR SUSTAINABILITY
49	IT ANALYZES DIFFERENT CONSUMER TYPES AND THE IMPACT OF PROFILE CHARACTERISTICS ON DEMAND RESPONSE EFFECTIVENESS
49	THE RESEARCH USES REAL WORLD DATA FROM QUEBEC TO INVESTIGATE INTERACTIONS BETWEEN THE DISTRIBUTOR , PROSUMERS , AND CONSUMERS , PROVIDING INSIGHT INTO THEIR OPTIMAL STRATEGIES , COSTS , AND REVENUES
49	THE STUDY ALSO INTRODUCES A DUELING DOUBLE DEEP Q NETWORK FOR DEVELOPING A NOVEL TARGETED PRICING STRATEGY , ENABLING BETTER CONTROL OVER LOAD SHIFTING
49	IT FURTHER EXPLORES THE EFFECT OF DIFFERENT DISTRIBUTED ENERGY RESOURCE , DER , PENETRATION LEVELS ON THE NETWORK AND OFFERS POLICY RECOMMENDATIONS FOR FUTURE SMART GRIDS
49	ARTIFICIAL INTELLIGENCE ENRE , ELECTRICITY MACHINE LEARNING IN OPERATIONS
49	THE STUDY EXEMPLIFIES OR MS USING DATA FOR PEAK LOAD MANAGEMENT AND HIGHLIGHTING INNOVATION 
50	THE USAGE OF ROBOTICS , AI AND SENSOR FUSION TO MEET SUSTAINABILITY GOALS IN TECHNOLOGY COMPANIES
50	THIS PAPER INVESTIGATES THE INTEGRATION OF ROBOTICS , AI , SENSOR FUSION AND WAREHOUSE AUTOMATION AND ORDER FULFILLMENT TO ACHIEVE SUSTAINABLE OPERATIONS
50	THE AIM IS TO DRIVE SUSTAINABLE PRACTICES , REDUCE RESOURCE CONSUMPTION AND ENHANCE ENVIRONMENTAL PERFORMANCE
50	AI ALGORITHMS CONTRIBUTE TO SUSTAINABILITY BY OPTIMIZING PROCESSES AND MINIMIZING ENVIRONMENTAL IMPACT
50	METRICS SUCH AS A DECREASE IN ENERGY CONSUMPTION , A REDUCTION IN CARBON EMISSIONS , AND A IMPROVEMENT IN EQUIPMENT UPTIME HIGHLIGHT THE POSITIVE OUTCOMES ACHIEVED THROUGH ACCURATE DEMAND FORECASTING , ENERGY MANAGEMENT , OPTIMIZATION AND PREDICTIVE MAINTENANCE FACILITATED BY AI TECHNOLOGIES
50	WE COMPARE THE METRICS OF SUCH AN IMPLEMENTATION IN THE CONTEXT OF A REAL WORLD APPLICATION
50	ARTIFICIAL INTELLIGENCE ENRE , ENVIRONMENT AND SUSTAINABILITY SOCIALLY RESPONSIBLE AND SUSTAINABLE OPERATIONS
50	ENERGY CONSUMPTION DUE TO AI HAD INCREASED
50	WE DEMONSTRATE WAYS OF REDUCTION FOR SUSTAINABLE OPS 
51	CROP DETECTION USING DEEP LEARNING WITH SATELLITE IMAGES
51	REMOTE SENSING TECHNOLOGIES HAVE ENABLED LARGE SCALE MONITORING OF LAND USE
51	CLASSIFICATION OF CROP TYPES IS ONE OF THE MOST IMPORTANT APPLICATIONS , AS IT CAN INFORM THE AGRICULTURAL AND ECONOMIC PLANNING AT A COUNTRY LEVEL
51	WE HAVE LAUNCHED AN INITIATIVE IN AFRICA TO COLLECT IN GROUND LABELS WITH GPS LOCATIONS , AND HAVE USED THIS DATA TO BUILD MACHINE LEARNING MODELS THAT PREDICT CROP TYPES FROM SATELLITE IMAGES
51	WE HAVE USED A SUITE OF DEEP LEARNING MODELS INCLUDING D CNNS , GRU CNNS , AND TRANSFORMERS TO EXTRACT FEATURES FROM BOTH TEMPORAL AND SPATIAL ASPECTS OF THE IMAGES
51	WE SHOW HOW WE HANDLED THE UNIQUE CHALLENGES IN AFRICA WHERE THE FIELDS ARE SMALLER AND MOST DAYS ARE CLOUDY
51	THE MODEL ACHIEVES HIGH ACCURACY IN SENEGAL , KENYA , NIGERIA , AND OTHER REGIONS
51	ARTIFICIAL INTELLIGENCE ENRE , ENVIRONMENT AND SUSTAINABILITY BECAUSE WE USE THE UNPRECEDENTED LARGE SCALE SATELLITE DATA TO INFORM OR DECISIONS 
52	A MODIFIED FEATURE SELECTION METHOD TO BUILD INTERPRETABLE AND TRUSTABLE MACHINE LEARNING MODEL FOR DIABETIC RETINOPATHY DISEASE PREDICTION
52	THE USE OF AI TO HELP PHYSICIANS MAKE MEDICAL PREDICTIONS IS EXTENSIVELY EXPLORED NOWADAYS
52	HOWEVER , MEDICAL DOMAIN KNOWLEDGE NOT PROVIDED IN THE DATA SET PLAYS A PIVOTAL ROLE IN PRESCRIBING MEDICAL DECISIONS
52	CURRENT RESEARCH DIRECTION PREDOMINANTLY FOCUSES ON EXTRACTING INSIGHTS FROM DATA WHICH IS LIMITED COMPARED TO WELL ESTABLISHED MEDICAL DOMAIN KNOWLEDGE
52	ADDRESSING THIS GAP , OUR STUDY AIMS TO DEVELOP AN APPROACH TO GATHER MEDICAL DOMAIN KNOWLEDGE FROM WELL PUBLISHED MEDICAL CORPUS AVAILABLE IN THE PUBMED LIBRARY AND USE IT TO SELECT ML MODEL VARIABLES FOR PREDICTING DIABETIC RETINOPATHY PATIENT S CONDITION
52	MOREOVER , THIS METHOD ALSO CAN PRESERVE THE MODEL S INTERPRETABILITY WHICH FACILITATES THE LIMITATION OF USER CAPABILITY
52	THIS APPROACH WILL HELP TO MAKE A ROBUST AND TRUSTABLE AI DRIVEN DECISION TO SUPPORT PHYSICIANS IN MAKING BETTER PREDICTIONS
52	ARTIFICIAL INTELLIGENCE HEALTH APPLICATIONS SOCIETY MACHINE LEARNING IN OPERATIONS
52	IT IS ABOUT HARNESSING DATA DRIVEN APPROACH TO MAKE INTERPRETABLE MODEL FOR MEDICAL APPLICATION 
53	AI DIVIDE VERSUS INCLUSION , EVIDENCE FROM ALGORITHMIC TASK ASSIGNMENT OF A FOOD DELIVERY PLATFORM 
53	THE ADOPTION OF AI TASK ASSIGNMENT SYSTEMS IN GIG ECONOMY HAS RAISED GROWING CONCERNS ABOUT WHETHER THE SYSTEMS BENEFIT ALL PLATFORM STAKEHOLDERS
53	IN A UNIQUE SETTING OF A FOOD DELIVERY PLATFORM , WE STUDY THE IMPACT OF AI TASK ASSIGNMENT ON DELIVERY WORKERS PRODUCTIVITY AND THE QUALITY OF CUSTOMER SERVICE
53	OUR RESULTS SHOW THAT THE ADOPTION IMPROVES WORKER PRODUCTIVITY BY NEARLY , WITH THE IMPROVEMENT PRIMARILY CONCENTRATED AMONG MEDIUM SKILLED WORKERS
53	HOWEVER , IT TAKES MORE HOURS FOR LOW SKILLED WORKERS TO COMPLETE EXTENDED STACKS OF ORDERS
53	FOR HIGH SKILLED WORKERS , THERE IS NO APPARENT BENEFIT OR LOSS
53	THESE RESULTS INDICATE THAT AI TASK ASSIGNMENT CAN PARTIALLY ALLEVIATE EXISTING PRODUCTIVITY DISPARITIES AMONG WORKERS
53	WE ALSO FIND THAT THE ADOPTION REDUCES CUSTOMER WAITING TIME FOR A SINGLE ORDER DELIVERY , BUT THIS IS NOT THE CASE FOR A STACKED ORDER DELIVERY
53	ARTIFICIAL INTELLIGENCE INFORMATION SYSTEMS MSOM , SERVICE OPERATIONS
53	OUR RESEARCH PROVIDES IMPLICATIONS ABOUT WHETHER AI ADOPTION IMPROVES GIG ECONOMY 
54	A TEAM BASED APPROACH FOR DESIGN AND IMPLEMENTATION OF ARTIFICIAL INTELLIGENCE APPLICATIONS AND ITS IMPACT ON WORKFORCE DEVELOPMENT
54	A FALSE ASSUMPTION MADE BY INDUSTRY PROFESSIONALS IS THAT ARTIFICIAL INTELLIGENCE , AI , SYSTEMS ARE SOFTWARE CODES , AND THEIR DEVELOPMENT IS SOLELY DEPENDENT ON PEOPLE WITH PROGRAMMING SKILLS IN MACHINE LEARNING , ML , AND DATA PROCESSING
54	THIS PRESENTATION OUTLINES A TEAM BASED APPROACH FOR DESIGN AND IMPLEMENTATION OF AI APPLICATIONS
54	IT SHOWS THAT A SUCCESSFUL AI PROJECT REQUIRES SEVERAL SKILLSETS AND A FRAMEWORK THROUGH WHICH ML MODEL DEVELOPERS AND APPLICATION EXPERTS USERS NOT FAMILIAR WITH CODING AND ML MODEL DEVELOPMENT CAN COMMUNICATE ADVANCE THE PROJECT
54	REAL WORLD EXAMPLES OF THIS APPROACH IN HEALTHCARE AND OCCUPATIONAL SAFETY PROJECTS ARE PRESENTED
54	IT IS ARGUED THAT THE APPROACH MUST BE CONSIDERED AS THE EDUCATION CORE OF ANY AI WORKFORCE DEVELOPMENT EFFORT THAT IS MEANT TO TRAIN INDUSTRY PROFESSIONALS WHO ARE NOT COMPUTER SAVVY
54	ARTIFICIAL INTELLIGENCE INFORMS COMMITTEE ON TEACHING AND LEARNING AND EDUCATION OUTREACH DATA DRIVEN INNOVATIONS IN OR EDUCATION
54	IT PROVIDES A TEAM BASED APPROACH FOR AI APPLICATION DEVELOPMENT 
55	COMBINING KNOWLEDGE AND NEURAL ODES FOR LEARNING INDUSTRIAL CHEMICAL REACTIONS 
55	ORDINARY DIFFERENTIAL EQUATIONS , ODES , ARE OF CRITICAL IMPORTANCE TO SCIENCE AND ENGINEERING
55	FIELDS OF RESEARCH ARE DEDICATED TO THE TASK OF BUILDING SUCH MODELS THROUGH DOMAIN EXPERTISE
55	A DATA DRIVEN FRAMEWORK FOR CONSTRUCTING DYNAMIC MODELS HAS THE POTENTIAL TO ACCELERATE THE LAB TO MARKET PIPELINE BY REMOVING SOME OF THE NEED FOR DOMAIN EXPERTISE
55	IN THIS WORK WE INVESTIGATE THE APPLICABILITY OF NEURAL ODES , NODES , FOR BUILDING MODELS OF REACTION KINETICS FROM EXPERIMENTAL DATA , AND HOW AVAILABLE DOMAIN KNOWLEDGE MAY BE USED TO ACCELERATE LEARNING
55	USING A SIMULATION CASE STUDY WE SHOW THAT UTILIZING INFORMATION OF THE SYSTEM S DYNAMICS CAN AID IN TRAINING MODELS , HOWEVER , EXTREME CARE SHOULD BE TAKEN WHEN ATTEMPTING TO USE ADDITIONAL INFORMATION
55	OUR FINDINGS ON TWO INDUSTRIAL REACTION DATA SETS SUGGEST THAT EVEN WEAK ASSUMPTIONS CAN IMPAIR NODE TRAINING
55	ARTIFICIAL INTELLIGENCE MACHINE LEARNING FOR OPTIMIZATION EMERGING TECHNOLOGIES AND APPLICATIONS 
56	A MULTI LEADERS FOLLOWER FRAMEWORK FOR MATERIAL DISCOVERY
56	MATERIAL DISCOVERY HAS BEEN VASTLY ACCELERATED DUE TO THE DATA REVOLUTION AND THE APPLICATION OF OPTIMISATION AND AI
56	HOWEVER , THERE HAS NOT YET EXIST A METHOD THAT COMBINES OPTIMISATION WITH SEQUENTIAL DECISION MAKING TO UTILISE THE DESIGN OF MATERIAL ACCORDING TO A DESIRED PROPERTY
56	IN THIS PAPER , WE PROPOSE A MULTI LEADER ONE FOLLOWER ARCHITECTURE FOR MATERIAL DISCOVERY TO COMBINE HUMAN FEEDBACK , SURROGATE MODELS AND REINFORCEMENT LEARNING
56	ARTIFICIAL INTELLIGENCE MACHINE LEARNING FOR OPTIMIZATION EMERGING TECHNOLOGIES AND APPLICATIONS 
56	ARCHITECTURE TO UTILISE DATA USING OR 
57	LARGE LANGUAGE MODELS AND KNOWLEDGE GRAPHS TO OPTIMIZE COMMERCIAL REAL ESTATE PORTFOLIO
57	COMMERCIAL REAL ESTATE DECISION MAKING IS A COMPLEX PROCESS INFLUENCED BY VARIOUS FACTORS
57	FACTORS SUCH AS SUPPLY AND DEMAND , ECONOMIC CONDITIONS , SUSTAINABILITY OBJECTIVES , GOVERNMENT REGULATIONS , INFRASTRUCTURE , SOCIOECONOMIC AND DEMOGRAPHIC TRENDS , AND MARKET SENTIMENT ALL PLAY A ROLE IN SHAPING THE DYNAMICS OF THE MARKET
57	TO OPTIMIZE REAL ESTATE PORTFOLIOS , COMPANIES NEED COST EFFECTIVE AND EFFICIENT SPACE UTILIZATION THROUGH DATA INFORMED DECISION FRAMEWORKS SUPPORTED BY AI BACKED INTELLIGENCE
57	EXTRACTING INSIGHTS FROM DIVERSE DATA WITH COMPLEX CAUSAL DYNAMICS REQUIRES CONTEXTUAL KNOWLEDGE
57	ADDITIONALLY , AS ECONOMIC AND MARKET CONDITIONS EVOLVE , SYNOPTIC EVALUATIONS MAY LOSE VALUE
57	IN THIS TALK , WE EXPLORE THE POTENTIAL OF COMBINING KNOWLEDGE GRAPHS AND INSIGHTS FROM LARGE LANGUAGE MODELS TO ENHANCE REAL ESTATE DECISION MAKING
57	ARTIFICIAL INTELLIGENCE MACHINE LEARNING FOR OPTIMIZATION ENRE , ENVIRONMENT AND SUSTAINABILITY
57	LARGE LANGUAGE MODELS FOR OPTIMISATION 
58	INDIVIDUALIZED LOCATION PREDICTION USING AUTOENCODERS AND LONG SHORT TERM MEMORY NETWORKS
58	PREDICTING AN INDIVIDUAL S FUTURE LOCATION IS A CHALLENGING TASK THAT HAS SIGNIFICANT IMPLICATIONS FOR A VARIETY OF REAL WORLD APPLICATIONS
58	IN THIS PAPER , WE PRESENT A NOVEL LOCATION PREDICTION ALGORITHM BASED ON AN AUTOENCODER USING CONVOLUTIONAL NEURAL NETWORK AND LONG SHORT TERM NEURAL NETWORK
58	OUR APPROACH AIMS TO PREDICT AN INDIVIDUAL S FUTURE LOCATION RATHER THAN A GENERALIZED PREDICTION FOR EVERYONE S NEXT LOCATION
58	THE EXPERIMENTS WERE CONDUCTED USING THE GEOLIFE DATASET
58	THE AUTOENCODER MODEL EFFECTIVELY LEARNED THE UNDERLYING FEATURES OF THE INPUT DATA , WHILE THE LSTM MODEL SHOWCASED GREAT ABILITY TO LEARN FROM THE INPUT FEATURES , ACHIEVING A VALIDATION LOSS OF , MEAN SQUARED ERROR , 
58	THESE RESULTS DEMONSTRATE THE POTENTIAL OF THE PROPOSED APPROACH FOR INDIVIDUALIZED LOCATION PREDICTION IN REAL LIFE SCENARIOS
58	ARTIFICIAL INTELLIGENCE MACHINE LEARNING FOR OPTIMIZATION LOCATION ANALYSIS
59	BUDGET BOT , A HOTEL RECOMMENDATION TOOL POWERED BY GENERATIVE AI AND MIXED INTEGER PROGRAMMING
59	SELECTING HOTEL ACCOMMODATIONS IS A KEY COMPONENT OF PLANNING A MEMORABLE ROAD TRIP , AND IDENTIFYING OPTIONS THAT MATCH EACH TRAVELER S PREFERENCES CAN BE TIME CONSUMING
59	THIS PRESENTATION WILL COVER A HOTEL RECOMMENDATION TOOL THAT INTEGRATES GENERATIVE AI AND MIXED INTEGER PROGRAMMING , MIP , TO OPTIMIZE HOTEL SELECTIONS FOR MULTI DAY AND MULTI HOTEL TRIPS
59	THE GENERATIVE AI COMPONENT CAPTURES THE TRIP INFORMATION AND HOTEL PREFERENCES AS INPUTS TO THE MIP MODEL
59	THE OPTIMIZATION MODEL IDENTIFIES THE BEST COMBINATION OF HOTELS THAT MEET THE TRAVELER S REQUIREMENTS
59	THIS INTEGRATION OF GENERATIVE AI AND MIP CREATES AN EFFICIENT AND EFFECTIVE DECISION MAKING PROCESS FOR TRAVELERS
59	ARTIFICIAL INTELLIGENCE MACHINE LEARNING FOR OPTIMIZATION OPT , INTEGER AND DISCRETE OPTIMIZATION
60	EFFICIENT REINFORCEMENT LEARNING IN UNKNOWN CONTINUOUS ENVIRONMENTS
60	ONE OF THE MOST POPULAR DYNAMICAL MODELS FOR CONTINUOUS ENVIRONMENTS ARE LINEAR TIME INVARIANT SYSTEMS THAT EVOLVE ACCORDING TO STOCHASTIC DIFFERENTIAL EQUATIONS
60	A UBIQUITOUS PROBLEM IN THESE SYSTEMS IS LEARNING TO TAKE ACTIONS TO MINIMIZE A QUADRATIC COST FUNCTION WHEN THE DYNAMICS MATRICES ARE UNKNOWN
60	WE DISCUSS NOVEL AND FAST REINFORCEMENT LEARNING POLICIES THAT LEARN THE OPTIMAL ACTIONS FAST
60	IN FACT , THE PROPOSED POLICY EFFICIENTLY BALANCES EXPLORATION VERSUS EXPLOITATION BY CAREFULLY RANDOMIZING THE PARAMETER ESTIMATES SUCH THAT THE REGRET GROWS AS THE SQUARE ROOT OF TIME AND THE NUMBER OF PARAMETERS
60	THEORETICAL PERFORMANCE ANALYSIS AS WELL AS FLIGHT CONTROL SIMULATIONS WILL BE PRESENTED TO ILLUSTRATE EFFICIENCY
60	ARTIFICIAL INTELLIGENCE MACHINE LEARNING IN OPERATIONS DECISION ANALYSIS SOCIETY
60	FAST AI FOR OR 
61	EXPLAINABLE REAL TIME PREDICTIVE ANALYTICS ON EMPLOYEE WORKLOAD IN DIGITAL RAILWAY CONTROL ROOMS
61	WORKLOAD PEAKS LOWS IMPACT EMPLOYEE WELL BEING
61	WE PROPOSE REAL TIME PREDICTIVE EMPLOYEE WORKLOAD ANALYTICS AS DECISION SUPPORT FOR MANAGEMENT IN AN ENVIRONMENT WITH VARIABLE AND IMBALANCED WORKLOAD , THE DIGITAL RAILWAY CONTROL ROOMS OF INFRABEL
61	THE GRANULARITY OF THE DATA FACILITATES AN ANALYSIS OF THE MULTIPLE DIMENSIONS OF WORKLOAD AT THE MINUTE LEVEL
61	WE PERFORM AN EXTENSIVE BENCHMARK BETWEEN WELL KNOWN MACHINE LEARNING AND DEEP LEARNING MODELS TO PREDICT THE PRESENCE AND MAGNITUDE OF VARIOUS WORKLOAD DIMENSIONS
61	WE LEVERAGE SHAPLEY VALUES TO OBTAIN BOTH LOCAL AND GLOBAL EXPLAINABILITY
61	FURTHER , WE SHOW THE VALUE FOR ADEQUATE EXPLAINABILITY OF DISENTANGLING THE PRESENCE AND MAGNITUDE OF WORKLOAD
61	THE PROPOSED MODEL IS IMPLEMENTED AS A PROOF OF CONCEPT FOR EXPLAINABLE DECISION SUPPORT WITHIN THE COMPANY OF FOCUS
61	ARTIFICIAL INTELLIGENCE MACHINE LEARNING IN OPERATIONS EMERGING TECHNOLOGIES AND APPLICATIONS 
61	WE PROPOSE DATA DRIVEN PREDICTIVE ANALYTICS THAT ARE IMPLEMENTED AS A PROOF OF CONCEPT IN A COMPANY 
62	LEARNING HUMAN INTERPRETABLE MODELS USING MACHINE LEARNING AND A SMOOTH INFORMATION CRITERION
62	WE PROPOSE A METHOD THAT HARNESSES SCARCE DATA AND DOMAIN EXPERT KNOWLEDGE TO DISCOVER HUMAN INTERPRETABLE MODELS
62	OUR APPROACH COMBINES A SMOOTH INFORMATION CRITERION WITHIN A PHYSICS INFORMED MACHINE LEARNING LOSS FUNCTION , ALLOWING FOR SIMULTANEOUS IDENTIFICATION OF A HUMAN INTERPRETABLE MODEL AND ITS PARAMETER ESTIMATES
62	OUR METHOD CAN DISCOVER PHYSICS FROM DATA , WITHOUT THE BIASES INHERENT IN SEQUENTIAL THRESHOLD REGRESSION TECHNIQUES
62	WE DEMONSTRATE OUR APPROACH THROUGH A STUDY OF VARIOUS NONLINEAR DYNAMIC SYSTEMS , COMPARING IT TO SYMBOLIC REGRESSION AND PHYSICS INFORMED NEURAL NETWORKS
62	OUR RESULTS EMPHASIZE THE SIGNIFICANCE OF SMOOTH INFORMATION CRITERION LOSS FUNCTIONS ON DATA DRIVEN MODEL DISCOVERY AND PARAMETER IDENTIFICATION
62	ARTIFICIAL INTELLIGENCE MACHINE LEARNING IN OPERATIONS OPT , MACHINE LEARNING
62	DISCOVERY OF PHYSICS FROM DATA 
63	DEEP INVENTORY MANAGEMENT
63	THIS WORK PROVIDES A DEEP REINFORCEMENT LEARNING APPROACH TO SOLVING A PERIODIC REVIEW INVENTORY CONTROL SYSTEM WITH STOCHASTIC VENDOR LEAD TIMES , LOST SALES , CORRELATED DEMAND , AND PRICE MATCHING
63	IN ORDER TO TRAIN THESE ALGORITHMS , WE DEVELOP NOVEL TECHNIQUES TO CONVERT HISTORICAL DATA INTO A SIMULATOR
63	ON THE THEORETICAL SIDE , WE PRESENT LEARNABILITY RESULTS ON A SUBCLASS OF INVENTORY CONTROL PROBLEMS , WHERE WE PROVIDE A PROVABLE REDUCTION OF THE REINFORCEMENT LEARNING PROBLEM TO THAT OF SUPERVISED LEARNING
63	ON THE ALGORITHMIC SIDE , WE PRESENT A MODEL BASED REINFORCEMENT LEARNING PROCEDURE , DIRECT BACKPROP , TO SOLVE THE PERIODIC REVIEW INVENTORY CONTROL PROBLEM BY CONSTRUCTING A DIFFERENTIABLE SIMULATOR
63	UNDER A VARIETY OF METRICS DIRECT BACKPROP OUTPERFORMS MODEL FREE RL AND NEWSVENDOR BASELINES , IN BOTH SIMULATIONS AND REAL WORLD DEPLOYMENTS
63	ARTIFICIAL INTELLIGENCE MSOM , SUPPLY CHAIN SUPPLY CHAIN AND LOGISTICS IN PRACTICE
63	OUR PAPER FORMULATES TRADITIONAL OR PROBLEMS AS EXOMDP TO APPLY MODERN POLICY LEARNING APPROACHES 
64	SUPPLIER SELECTION AND ORDER ALLOCATION USING A MULTI OBJECTIVE MODEL , INTEGRATED WITH MACHINE LEARNING METHODS
64	SUPPLIER SELECTION AND ORDER ALLOCATION IS AN IMPORTANT PROBLEM IN PURCHASING AND PROCUREMENT
64	IN THIS TALK , A TWO STAGE APPROACH FOR SUPPLIER SELECTION AND ORDER ALLOCATION PLANNING IS DISCUSSED
64	STAGE INVOLVES DETERMINING THE VALUES OF THE DEMANDS BASED ON MACHINE LEARNING METHODS
64	IN STAGE , A NEW MULTI OBJECTIVE MODEL IS INTRODUCED TO SELECT THE BEST SUPPLIER , S , AND TO DETERMINE THE ORDER , S , 
64	THE RESULTS SHOW THAT THE VALUES OF DEMANDS HAVE EFFECTS ON BOTH THE SELECTED SUPPLIERS AND THE ALLOCATED ORDERS TO THEM
64	ARTIFICIAL INTELLIGENCE MSOM , SUSTAINABLE OPERATIONS SUPPLY CHAIN AND LOGISTICS IN PRACTICE
64	MACHINE LEARNING AND OPTIMIZATION HAVE BEEN COMBINED IN THIS RESEARCH 
65	HOW DOES COMPETITION AFFECT AI INVESTMENT IN FIRMS
65	EVIDENCE FROM A QUASI NATURAL EXPERIMENT IN THE UNITED STATES
65	THIS PAPER EXAMINES THE IMPACT OF THE US CHINA TRADE WAR ON AI INVESTMENT IN FIRMS
65	THE AUTHORS POSIT THAT MACRO LEVEL FACTORS , SUCH AS COMPETITION POLICY , CAN SIGNIFICANTLY INFLUENCE AI ADOPTION , A NOTION THAT PREVIOUS RESEARCH HAS NOT PAID SIGNIFICANT ATTENTION TO
65	OUR CONTEXT IS THE US CHINA TRADE WAR AND THE INCREASED IMPORT TARIFFS ON CHINESE GOODS
65	WE ARGUE THESE TRADE RESTRICTIONS REDUCED COMPETITION FOR US FIRMS , AFFECTING THEIR AI INVESTMENTS
65	OUR FINDINGS INDICATE A SIGNIFICANT INCREASE IN AI INVESTMENT BY FIRMS AFFECTED BY THE TRADE WAR
65	WE ALSO DISCOVERED A TREND AMONG FIRMS HIRING MORE AI RELATED LABOR , OFTEN THOSE WITH HIGH VALUE CHAIN COMPLEXITY AND UNSATISFACTORY OPERATIONAL EFFICIENCY
65	WE ARGUE THAT OUR FINDINGS UNCOVER THE UNINTENDED CONSEQUENCES OF PROTECTIONISM , SUCH AS A REDUCTION IN COMPETITION AND ITS POSITIVE IMPACT ON FIRMS
65	ARTIFICIAL INTELLIGENCE MSOM , TECHNOLOGY , INNOVATION AND ENTREPRENEURSHIP 
66	AUTOMATIC DISCOVERY AND GENERATION OF VISUAL DESIGN CHARACTERISTICS , APPLICATION TO VISUAL CONJOINT
66	VISUAL DESIGN IMPACTS CONSUMER PREFERENCES SIGNIFICANTLY , BUT QUANTIFYING THESE CHARACTERISTICS IS DIFFICULT
66	WE OFFER AN AUTOMATIC METHOD TO IDENTIFY AND QUANTIFY THESE FEATURES FROM IMAGE DATA USING A DISENTANGLEMENT APPROACH
66	OUR METHOD , UNLIKE OTHERS , DOESN T REQUIRE SUPERVISION OR PRIOR KNOWLEDGE OF DESIGN CHARACTERISTICS
66	IT USES STRUCTURED PRODUCT CHARACTERISTICS FOR DISENTANGLEMENT , UNVEILING HUMAN INTERPRETABLE AND INDEPENDENT ATTRIBUTES
66	APPLIED TO WATCHES , WE DISCOVERED SIX SUCH CHARACTERISTICS
66	WITH VISUAL CONJOINT ANALYSIS , WE UNDERSTOOD CONSUMER PREFERENCES FOR THESE FEATURES
66	OUR METHOD CAN ALSO GENERATE NOVEL DESIGNS TO MEET VARIOUS CONSUMER SEGMENTS IDEAL POINTS
66	ARTIFICIAL INTELLIGENCE NEW PRODUCT DEVELOPMENT DATA MINING
67	DRIVING DATA GENERATION IN MOLECULAR DISCOVERY THROUGH DEVELOPMENT OF BENCHMARK REINFORCEMENT LEARNING ENVIRONMENTS
67	MOLECULAR AND MATERIALS DISCOVERY IS AN AREA OF GREAT TECHNOLOGICAL SIGNIFICANCE THAT CONTINUES TO GREATLY BENEFIT FROM THE DATA REVOLUTION
67	HERE WE PRESENT A SERIES OF BENCHMARK REINFORCEMENT LEARNING ENVIRONMENTS THAT ALLOW MIXING AND MATCHING DIFFERENT DESIGN GOALS , DIFFERENT REPRESENTATIONS , AND DIFFERENT MOLECULAR SPACES WITH DIFFERENT REINFORCEMENT LEARNING AGENTS
67	THESE PROVIDE BOTH A SET OF STANDARDS TO EVALUATE DIFFERENT REINFORCEMENT LEARNING ALGORITHMS APPLIED TO MOLECULAR DESIGN BUT ALSO A STANDARDISED WAY OF GENERATING MOLECULAR DATASETS CAPTURING THE MOLECULAR DESIGN PROCESS
67	ARTIFICIAL INTELLIGENCE OPT , GLOBAL OPTIMIZATION OPT , MACHINE LEARNING
67	GENERATION OF STRUCTURED TO DATA FOR MOLECULAR DISCOVERY 
68	UNMANNED AERIAL VEHICLE MISSION PLANNING USING A NEURAL NETWORK
68	UNMANNED AERIAL VEHICLE MISSION PLANNING USING A NEURAL NETWORK THE OPERATIONAL PLANNING OF A MARITIME SEARCH MISSION CARRIED OUT BY AN UNMANNED AERIAL VEHICLE , UAV , CAN BE AUTOMATED AND PRIORITIZED , CONSIDERING THE CHARACTERISTICS OF THE VESSEL TO BE FOUND
68	THEREFORE , THIS WORK AIMS TO PRESENT A UAV SEARCH PLANNING METHODOLOGY , WHICH USES A NEURAL NETWORK TO PRIORITIZE TARGETS AND OPTIMIZE THE ROUTE , BASED ON INFORMATION OBTAINED FROM A DATABASE OF VESSELS AND DATA COLLECTED BY THE UAV S ELECTROMAGNETICS SENSORS
68	ARTIFICIAL INTELLIGENCE OPT , INTEGER AND DISCRETE OPTIMIZATION AVIATION APPLICATIONS
69	THE MODERATING ROLE OF WORK AUTONOMY IN THE RELATIONSHIP BETWEEN AI ADVANCEMENT AND TEAM CREATIVITY , A TASK TECHNOLOGY FIT PERSPECTIVE
69	DESPITE GROWING INTEREST IN THE ROLE OF ARTIFICIAL INTELLIGENCE , AI , IN ENHANCING TEAM CREATIVITY , LITTLE IS KNOWN ABOUT THE CONDITIONS THAT MAXIMIZE ITS POTENTIAL BENEFITS
69	IN THIS RESEARCH , WE ATTEMPT TO INVESTIGATE WHEN AND HOW AI ADVANCEMENT ENHANCES TEAM CREATIVITY
69	DRAWING ON THE TASK TECHNOLOGY FIT THEORY , WE PROPOSE THAT WORK AUTONOMY MODERATES THE POSITIVE RELATIONSHIP BETWEEN AI ADVANCEMENT AND TEAM CREATIVITY VIA PERCEIVED AI ASSISTANCE
69	FINDINGS BASED ON MULTISOURCE DATA FROM EMPLOYEES IN TEAMS SUPPORTED THE HYPOTHESES
69	THESE FINDINGS SUGGEST THAT WORK AUTONOMY CAN BE A SIGNIFICANT FACILITATOR IN REAPING THE BENEFITS OF AI IN A TEAM SETTING AND UNDERSCORE ORGANIZATIONS TO ENHANCE TEAM CREATIVITY BY ENCOURAGING WORK AUTONOMY IN CONJUNCTION WITH AI ADVANCEMENT
69	ARTIFICIAL INTELLIGENCE OPT , MACHINE LEARNING BEHAVIORAL OPERATIONS MANAGEMENT
70	CONTROL OF DUAL SOURCING INVENTORY SYSTEMS USING RECURRENT NEURAL NETWORKS
70	INVENTORY MANAGEMENT PROBLEMS HAVE BEEN STUDIED EXTENSIVELY FOR OVER YEARS , YET EVEN BASIC DUAL SOURCING PROBLEMS REMAIN GENERALLY INTRACTABLE
70	IN THIS WORK , WE APPROACH DUAL SOURCING FROM A NEURAL NETWORK BASED OPTIMIZATION LENS AND INCORPORATE INFORMATION ON INVENTORY DYNAMICS AND ITS REPLENISHMENT POLICIES INTO THE DESIGN OF RECURRENT NEURAL NETWORKS
70	THE PROPOSED NEURAL NETWORK CONTROLLERS LEARN NEAR OPTIMAL POLICIES OF COMMONLY USED INSTANCES WITHIN A FEW MINUTES OF CPU TIME ON A REGULAR PC
70	THEY ARE ALSO EFFECTIVE WITH EMPIRICAL , NON STATIONARY DEMAND DISTRIBUTIONS THAT ARE CHALLENGING TO TACKLE OTHERWISE
70	OUR WORK SHOWS THAT HIGH QUALITY SOLUTIONS OF COMPLEX INVENTORY MANAGEMENT PROBLEMS WITH NON STATIONARY DEMAND CAN BE OBTAINED WITH DEEP NEURAL NETWORK OPTIMIZATION APPROACHES
70	ARTIFICIAL INTELLIGENCE OPT , MACHINE LEARNING MACHINE LEARNING IN OPERATIONS
70	WE SHOW THAT NEURAL NETWORKS THAT USE EMPIRICAL DATA CAN BE EFFECTIVE FOR INVENTORY MANAGEMENT
71	EXPLAINABILITY IN ARTIFICIAL INTELLIGENCE , AI , CHALLENGES AND SOLUTIONS
71	INFORMATION LITERACY IS CRITICAL TODAY , AS COMPLEX INFORMATION TECHNOLOGY BASED PRODUCTS ARE GAINING MASS POPULARITY
71	THIS HAS BEEN EVIDENT WITH MOBILE DEVICES AND APPS OVER THE PAST DECADE , AND NOW WITH AI BASED SERVICES LIKE CHAT GPT
71	THIS PRESENTATION WILL COVER THE TOPIC OF EXPLAINABILITY IN AI
71	WITH THE USE OF EXAMPLES , THE PRESENTER WILL HELP THE AUDIENCE TO UNDERSTAND WHAT EXPLAINABILITY MEANS IN THE CONTEXT OF TECHNICAL USERS OF AI , AND ALSO FROM THE POINT OF VIEW OF END USERS OF AI BASED PRODUCTS
71	THE TYPES OF EXPLAINABILITY CHALLENGES ASSOCIATED WITH VARIOUS TYPES OF AI MODELS WILL BE PRESENTED , ALONG WITH THE ADVERSE IMPACTS THAT WOULD RESULT IN VARIOUS SCENARIOS IF THESE CHALLENGES ARE NOT DEALT WITH
71	APPROACHES FOR SOLVING THESE PROBLEMS WILL BE PRESENTED BASED ON LATEST RESEARCH , WITH AN EXPLANATION OF HOW THESE SOLUTIONS TRANSLATE INTO PRACTICAL APPLICATIONS
71	ARTIFICIAL INTELLIGENCE OPT , MACHINE LEARNING PRACTICE 
71	AS THIS TOPIC RELATES TO AI AND THE DATA DRIVING AI , IT RELATES TO THE THEME 
72	ROBUST STATISTICAL METHODS FOR ADVERSARIAL ATTACK MITIGATION IN FEDERATED LEARNING
72	THIS STUDY INVESTIGATES THE APPLICATION OF ROBUST STATISTICAL METHODS TO ADDRESS THE IMPACT OF ADVERSARIAL ATTACKS IN MACHINE LEARNING MODELS
72	SPECIFICALLY , WE EXPLORE THE EFFECTIVENESS OF THESE METHODS IN DIFFERENTIALLY PRIVATE FEDERATED LEARNING AND TRADITIONAL FEDERATED LEARNING SETTINGS
72	BY COMPARING THE RESULTS TO CENTRALIZED MACHINE LEARNING , BOTH IN THE ABSENCE AND PRESENCE OF ADVERSARIAL ATTACKS , WE AIM TO ASSESS THE ROBUSTNESS AND RELIABILITY OF THE PROPOSED TECHNIQUES
72	OUR FINDINGS SHED LIGHT ON THE POTENTIAL OF ROBUST STATISTICAL METHODS TO MITIGATE THE ADVERSE EFFECTS OF ADVERSARIAL ATTACKS IN FEDERATED LEARNING
72	ARTIFICIAL INTELLIGENCE OPT , MACHINE LEARNING QUALITY , STATISTICS AND RELIABILITY
72	ROBUST STATISTICS IN FEDERATED LEARNING ENSURE DATA RELIABILITY IN OR MS 
73	OPTIMIZATION PROXIES IN THE SUPPLY CHAIN FOR SEMICONDUCTOR MANUFACTURING
73	IN THE SUPPLY CHAIN FOR SEMICONDUCTOR MANUFACTURING , MANY PROCESSES AT VARIOUS STAGES AND LOCATIONS TRANSFORM THE SILICA WAFERS INTO MULTIPLE COMPONENTS TO FINALLY PRODUCE CHIPS
73	TO GENERATE THE PRODUCTION PLAN ALONG THIS SUPPLY CHAIN , A MASTER PRODUCTION SCHEDULER TOOL EXECUTES DIFFERENT OPTIMIZATION MODELS SEQUENTIALLY
73	HENCE , PERFORMING SENSITIVITY ANALYSES FOR PLANNING PURPOSES BECOMES A CHALLENGE , AS IT IS NECESSARY TO EXECUTE THE SEQUENTIAL OPTIMIZATION MULTIPLE TIMES TO QUANTIFY THE IMPACT OF VARIATIONS IN THE INPUT PARAMETERS
73	TO OVERCOME THIS CHALLENGE , WE COMBINE OPTIMIZATION AND MACHINE LEARNING TO PRODUCE AN OPTIMIZATION PROXY OF THE SEQUENTIAL OPTIMIZATION , ALLOWING QUICK SENSITIVITY ANALYSES FOR PLANNING PURPOSES
73	ARTIFICIAL INTELLIGENCE OPT , MACHINE LEARNING SUPPLY CHAIN AND LOGISTICS IN PRACTICE
73	COMBINING OPTIMIZATION AND MACHINE LEARNING ENABLES NEW HORIZONS IN THE DATA REVOLUTION 
74	RISK AVERSE MULTIARMED BANDIT PROBLEM WITH SWITCHING PENALTIES
74	THIS STUDY EXPLORES THE INTEGRATION OF RISK INTO THE MULTIARMED BANDIT PROBLEM , MAB , THAT INVOLVES SWITCHING PENALTIES
74	SPECIFICALLY , WE INVESTIGATE SCENARIOS IN WHICH DECISION MAKERS INCUR A COST EACH TIME THEY SWITCH BETWEEN ARMS , WHICH IS A COMMON OCCURRENCE IN MANY REAL WORLD APPLICATIONS
74	UNLIKE THE RISK NEUTRAL CASE , THE STRUCTURE OF OPTIMAL POLICY AND THE PERFORMANCE OF PRIORITY INDEX ALGORITHMS FOR ALLOCATING RESOURCES IN RISK AVERSE MAB PROBLEMS WITH SWITCHING PENALTIES REMAIN UNKNOWN , AND NO HEURISTIC METHOD EXISTS FOR GENERATING HIGH QUALITY , INTERPRETABLE SOLUTIONS
74	TO ADDRESS THIS GAP , WE EXPLORE THE QUALITATIVE FEATURES OF OPTIMAL POLICIES TO STREAMLINE THE SEARCH FOR AN EFFICIENT ALLOCATION STRATEGY
74	THEN , WE DEVELOP AN INDEX BASED HEURISTIC ALGORITHM AND SHOW ITS PERFORMANCE IN ACHIEVING NEAR OPTIMAL PERFORMANCE IN PRACTICE
74	ARTIFICIAL INTELLIGENCE OPT , OPTIMIZATION UNDER UNCERTAINTY OPTIMIZATION , OPT , WE HIGHLIGHT THE IMPORTANCE OF DATA DRIVEN DECISION MAKING IN REAL WORLD SCENARIOS 
75	SAFE RL PROMPTING FOR LLMS FOR SOLVING DATA MANAGEMENT CHALLENGES
75	WE CONSIDER THE PROBLEM OF USAGE OF LARGE LANGUAGE MODELS , LLMS , FOR DATA MANAGEMENT TASKS SUCH AS IMPUTATION AND ERROR DETECTION
75	AS TASK COMPLEXITY INCREASES AS WELL AS THE NEED FOR ACCURATE RESPONSES , SO DOES THE NEED FOR WELL CRAFTED PROMPTS , WHICH ALLOW LLMS TO LEARN IN CONTEXT
75	WE PROPOSE TO FORMULATE THE PROBLEM OF PROMPT TUNING AS AN RL PROBLEM
75	MOREOVER , WE INTEND TO CRAFT PROMPTING IN A SAFE WAY AVOIDING DANGEROUS DECISIONS AND FINALLY GETTING SAFE RL PROMPTING FOR LLMS TO TACKLE DATA MANAGEMENT TASK CHALLENGES
75	ARTIFICIAL INTELLIGENCE OPTIMIZATION , OPT , MACHINE LEARNING FOR OPTIMIZATION
76	A STATISTICAL ONLINE INFERENCE METHOD FOR REGULARIZED Q LEARNING ALGORITHM
76	REINFORCEMENT LEARNING ALGORITHMS ARE WIDELY USED FOR DECISION MAKING TASKS IN VARIOUS DOMAINS
76	HOWEVER , THE PERFORMANCE OF THESE ALGORITHMS CAN BE IMPACTED BY HIGH VARIANCE AND INSTABILITY , PARTICULARLY IN ENVIRONMENTS WITH NOISE OR SPARSE REWARDS
76	IN THIS PAPER WE PROPOSE A FRAMEWORK TO PERFORM STATISTICAL ONLINE INFERENCE FOR A REGULARIZED Q LEARNING APPROACH CALLED G LEARNING
76	WE ADAPT THE FUNCTIONAL CENTRAL LIMIT THEOREM , FCLT , FOR G LEARNING UNDER WEAKER CONDITIONS , AND THEN CONSTRUCT CONFIDENCE INTERVALS FOR PARAMETERS VIA RANDOM SCALING
76	WE CONDUCT EXPERIMENTS TO PERFORM INFERENCE ON BOTH G LEARNING AND ITS TRADITIONAL COUNTERPART Q LEARNING USING RANDOM SCALING AND OTHER BENCHMARK METHODS AND REPORT THEIR COVERAGE RATES ON A GRID WORLD PROBLEM FOR COMPARISON
76	ARTIFICIAL INTELLIGENCE QUALITY , STATISTICS AND RELIABILITY APPLIED PROBABILITY 
77	BPM METHODOLOGY FOR IMPLEMENTING AI IN BUSINESS PROCESSES
77	AI HAS ALREADY BEGUN TO AUTOMATE SPECIFIC TASKS AND ROLES , LEADING TO CHANGES IN THE JOB MARKET
77	THEREFORE , IT IS CRUCIAL TO ESTABLISH A FRAMEWORK FOR IMPLEMENTING CHANGES IN THE BUSINESS PROCESS THAT INVOLVE COMPLETING OR PARTIALLY REPLACING TASKS WITH AI
77	THIS RESEARCH AIMS TO PRESENT A BPM BASED METHODOLOGY THAT ENABLES THE IDENTIFICATION OF CRITERIA AND THE EXTENT TO WHICH TASKS WITHIN A PROCESS CAN BE EITHER REPLACED OR COMPLEMENTED BY AI
77	THE SIMULATION RESULTS FOR A LOAN APPROVAL PROCESS COMPARING THE PRE AND POST IMPLEMENTATION PHASES INDICATE SUBSTANTIAL LONG TERM COST SAVINGS AND REDUCED PROCESSING TIME
77	FURTHERMORE , THIS PAPER DELVES INTO THE CHALLENGES OF IMPLEMENTING AI TECHNOLOGIES IN A BUSINESS PROCESS , ENCOMPASSING ACCURACY , EFFECTIVE INFORMATION TRANSFER , AND ETHICAL AND SECURITY CONSIDERATIONS
77	ARTIFICIAL INTELLIGENCE SCHEDULING AND PROJECT MANAGEMENT TECHNOLOGY , INNOVATION MANAGEMENT AND ENTREPRENEURSHIP
77	THIS PRESENTATION FOCUSSES ON HOW AI , DATA REVOLUTION , , CAN TRANSFORM PROJECT MANAGEMENT 
78	MODEL AGNOSTIC PERSONALIZED PREFERENCE ESTIMATOR FOR TASK RECOMMENDATION IN ONLINE LABOR MARKETS , A META LEARNING APPROACH
78	THE TASK RECOMMENDATION SYSTEMS IN ONLINE LABOR MARKETS , OLMS , HAVE FACED THE CHALLENGE OF ACCURATELY RECOMMENDING SUITABLE TASKS FOR NEW WORKERS WITHOUT SUFFICIENT BIDDING HISTORY
78	THIS PAPER PROPOSES A MODEL AGNOSTIC PERSONALIZED PREFERENCE ESTIMATOR , MAPPE , FRAMEWORK TO SOLVE THE COLD START PROBLEM 
78	THE MAPPE FRAMEWORK UTILIZES AN INTEREST MODULE WITH SELF ATTENTION AND A COMPETENCE MODULE TO CAPTURE WORKERS PREFERENCES FOR TASK TYPE AND COMPLEXITY
78	THE META LEARNING APPROACH IS ADAPTED TO ENABLE EFFICIENT AND QUICK ADAPTATION TO NEW WORKERS WITH LIMITED BIDDING DATA
78	REAL WORLD DATASETS WERE USED TO DEMONSTRATE THE EFFECTIVENESS OF MAPPE COMPARED TO STATE OF THE ART MODELS
78	THE PROPOSED METHOD IMPROVES TASK QUALITY BY EFFECTIVELY RECOMMENDING TASKS TO NEW WORKERS BASED ON THEIR PREFERENCES , THUS HELPING TO ALLEVIATE THE COLD START PROBLEM IN OLMS
78	ARTIFICIAL INTELLIGENCE SHARING ECONOMY , INNOVATIVE MARKETPLACES , AND DATA DATA MINING
79	EXPLORING THE IMPACT OF AI GENERATED ARTWORK ON LEARNING AND CREATIVITY IN ONLINE ART COMMUNITIES
79	THIS STUDY EXAMINES THE IMPACT OF AI GENERATED ARTWORK ON ONLINE ART COMMUNITIES , FOCUSING ON LEARNING , COLLABORATION AND CREATIVITY
79	THE USE OF PROMPT ENGINEERING IN AI ARTWORK SHAPES ITS CHARACTERISTICS , ENABLING ARTISTS WITH VARYING TECHNICAL SKILLS TO PARTICIPATE AND EXPANDING PROFESSIONALISM AND STAGES OF ARTWORK SHARING
79	THE STUDY INVESTIGATES HOW AI GENERATED ARTWORK AFFECTS KNOWLEDGE SHARING IN VARIOUS STAGES OF ARTWORK CREATION , INCLUDING LEARNING , CREATING , DISCUSSING , AND SHARING
79	THROUGH DATA DRIVEN ANALYSIS , WE AIM TO UNDERSTAND THE ROLE OF AI IN ONLINE ART COMMUNITIES AND PROVIDE MANAGERIAL IMPLICATIONS
79	ARTIFICIAL INTELLIGENCE SOCIAL MEDIA ANALYTICS EBUSINESS
80	FIELD DELINEATION AND AI FOR FOOD SECURITY IN AFRICA
80	ONE OF THE KEY CHALLENGES IN AGRICULTURE IS TO ACCURATELY IDENTIFY ARABLE LAND , TO ENABLE FARMERS TO OPTIMIZE THEIR RESOURCES AND MAXIMIZE THEIR YIELDS
80	THIS IS ESPECIALLY IMPORTANT IN LESS DEVELOPED COUNTRIES LIKE AFRICA , WHERE A GROWING POPULATION AND CLIMATE CHANGE THREATEN FOOD SECURITY
80	IN OUR WORK , WE CREATED A FRAMEWORK TO LEVERAGE SATELLITE IMAGES TO ACCURATELY IDENTIFY CROPLAND
80	THE CHARACTERISTICS OF AFRICAN FIELDS VARY SIGNIFICANTLY FROM THOSE OF MORE DEVELOPED COUNTRIES LIKE FRANCE , WHICH PROVIDE PUBLICLY AVAILABLE FIELD DATA
80	FOR EXAMPLE , VARYING FIELD SIZE , CROP TYPE AND CLOUDS ARE AMONG THE BIGGEST CHALLENGES TO ACHIEVE A STRONG MODEL PERFORMANCE
80	TO ADDRESS THESE ISSUES , WE DEVELOPED CUSTOM IMAGE SEGMENTATION MODELS TO IDENTIFY FIELD BOUNDARIES USING DEEP LEARNING AND ACHIEVED COMPETITIVE PERFORMANCE
80	ARTIFICIAL INTELLIGENCE TECHNOLOGY , INNOVATION MANAGEMENT AND ENTREPRENEURSHIP ENRE , ENVIRONMENT AND SUSTAINABILITY
81	GRAPH KOOPMAN OPERATOR FOR TRAFFIC FORECASTING
81	TRAFFIC FORECASTING IS A CRUCIAL PART OF TRAFFIC MANAGEMENT
81	WHILE GRAPH NEURAL NETWORKS , GNNS , HAVE BEEN SUCCESSFUL IN PREDICTING TRAFFIC , THEIR COMPLEX MODEL ARCHITECTURES MAKE THEM IMPRACTICAL FOR USE IN LARGE NETWORKS DUE TO HIGH COMPUTING AND MEMORY COSTS
81	TO OVERCOME THIS BARRIER , WE PROPOSE A NOVEL LINEAR MODEL , NAMED GRAPH KOOPMAN OPERATOR , WHICH ENCODES THE GRAPH TOPOLOGY INTO THE KOOPMAN OPERATOR TO CAPTURE GRAPH BASED DYNAMICS
81	USING REAL WORLD TRAFFIC DATA FROM THE ENTIRE CALIFORNIA HIGHWAY NETWORK WITH OVER , NODES , WE DEMONSTRATE THAT THIS PROPOSED SIMPLE LINEAR METHOD , COMPARED TO ALL THE EXISTING NONLINEAR GNN FORECAST MODELS , SURPRISINGLY CAN ACHIEVE HIGHER PREDICTION ACCURACY AND IS MORE EFFICIENT BY AROUND TWO ORDERS OF MAGNITUDE
81	ARTIFICIAL INTELLIGENCE TRANSPORTATION SCIENCE AND LOGISTICS , TSL , DATA MINING
81	WE PROPOSED A NEW INSIGHT FOR GRAPH STRUCTURED TIME SERIES FORECASTING WITH BIG DATA 
82	INTEGRATING PHYSICAL LAWS INTO NEURAL NETWORKS FOR ENHANCED DATA CLEANING AND FUSION IN TRAFFIC MODEL CALIBRATION
82	THIS PRESENTATION INTRODUCES A COMPREHENSIVE FRAMEWORK THAT INCORPORATES PHYSICAL LAWS INTO PHYSICS INFORMED NEURAL NETWORKS , PINNS , FOR TRAFFIC MODEL CALIBRATION
82	LEVERAGING DIVERSE DATA SOURCES SUCH AS PROBE VEHICLE DATA , HIGH RESOLUTION VEHICLE TRAJECTORY DATA , CONNECTED AND AUTOMATED VEHICLE , CAV , DATA , AND CROWD SOURCED PLATFORMS DATA , THIS FRAMEWORK ADDRESSES THE CHALLENGES ASSOCIATED WITH DATA RELIABILITY , ACCURACY AND GRANULARITY
82	BY INTEGRATING KNOWLEDGE OF PHYSICAL LAWS , INCLUDING CONSERVATION LAWS , FLOW DENSITY RELATIONSHIPS , SHOCKWAVE THEORY , CAR FOLLOWING MODELS , AND LANE CHANGING MODELS , OUR APPROACH ENABLES ACCURATE PREDICTION AND ANALYSIS OF TRAFFIC CONDITIONS
82	THE COMPUTATIONAL GRAPH REPRESENTATION OF THE MODEL IS SOLVED USING A FORWARD BACKWARD METHOD , WITH NUMERICAL EXPERIMENTS WITH REAL WORLD DATASETS
82	ARTIFICIAL INTELLIGENCE TSL , INTELLIGENT TRANSPORTATION SYSTEMS TSL , URBAN TRANSPORTATION PLANNING AND MODELING
82	THIS IS PART OF FHWA PROJECT FOR USING EMERGING DATA SOURCES FOR TRAFFIC MODEL CALIBRATION 
83	ENHANCING SEMICONDUCTOR EQUIPMENT FAILURE DETECTION USING CORRELATION ANALYSIS AND DATA AUGMENTATION
83	TRADITIONAL CONTROL CHARTS AND MACHINE LEARNING METHODS HAVE BEEN USED TO DETECT EQUIPMENT FAILURES IN SEMICONDUCTOR PROCESSES
83	HOWEVER , DETECTING FAILURES AND IDENTIFYING THEIR ROOT CAUSES CAN BE CHALLENGING BECAUSE OF THE COMPLEXITY OF THE PROCESS AND STRUCTURAL CHARACTERISTICS OF THE EQUIPMENT
83	MOREOVER , THE ANOMALY SECTIONS FOR EACH PART CAN BE IMBALANCED , WHICH CAN HINDER CLASSIFICATION PERFORMANCE
83	IN THIS STUDY , WE PROPOSE A METHOD TO DETECT FAILURES USING THE CORRELATION OF VARIABLES AND DATA AUGMENTATION
83	WE DEMONSTRATE THE EFFECTIVENESS AND APPLICABILITY OF THE PROPOSED METHOD USING REAL WORLD MULTIVARIATE TIME SERIES DATA OBTAINED FROM ASHING PROCESS EQUIPMENT
83	ARTIFICIAL INTELLIGENCE 
84	MANAGING INFLUENCER BRAND COLLABORATION , A MULTITASK LEARNING MODEL FOR INFLUENCER SELECTION ARTIFICIAL INTELLIGENCE 
85	INTERPRETABLE TREATMENT EFFECT PREDICTION USING OPTIMAL TREES
85	POLICY TREES ARE A RECENT APPROACH THAT COMBINE INTERPRETABLE MACHINE LEARNING AND CAUSAL INFERENCE TECHNIQUES TO GENERATE INTERPRETABLE PRESCRIPTION POLICIES FROM OBSERVATIONAL DATA
85	HOWEVER , THIS APPROACH IS DESIGNED WITH THE GOAL OF FINDING THE SIMPLEST POLICY FOR OPTIMAL TREATMENT ASSIGNMENT
85	IN MANY PROBLEM SETTINGS , PARTICULAR IN MEDICINE , TREATMENTS MAY HAVE SIDE EFFECTS THAT ARE DIFFICULT TO QUANTIFY , AND SO INSTEAD OF SIMPLY PRESCRIBING THE BEST TREATMENT , OUR GOAL IS TO UNDERSTAND AND PREDICT PERSONALIZED TREATMENT EFFECTS IN AN INTERPRETABLE WAY
85	WE PROPOSE AN APPROACH THAT COMBINES CAUSAL INFERENCE TECHNIQUES WITH OPTIMAL REGRESSION TREES TO GENERATE INTERPRETABLE TREATMENT EFFECT PREDICTIONS
85	THIS NEW APPROACH HAS MANY APPLICATIONS , INCLUDING MEDICAL SCENARIOS WHERE OVER TREATMENT ISSUES ARE SUSPECTED
85	ARTIFICIAL INTELLIGENCE 
86	MELODIC INTELLIGENCE , NEURAL NETWORKS APPLICATION FOR INDIAN CLASSICAL MUSIC GENERATION
86	IN RECENT YEARS , THERE HAS BEEN A GROWING INTEREST IN USING AI FOR MUSIC COMPOSITION , BUT RESEARCH ON AI MUSIC GENERATION FOR INDIAN TRADITIONAL MUSIC IS LIMITED
86	THIS PROJECT USES RNN AND LSTM , ML , TECHNIQUES TO GENERATE TRACKS FOR A WIDE RANGE OF INSTRUMENTS AND EXPAND THE CREATIVE CAPABILITIES OF COMPOSERS
86	THIS STUDY PROVIDES AN OVERVIEW OF INDIAN RAGA MUSIC AND DISCUSSES MELODY GENERATION TECHNIQUES USING AI
86	THIS MODEL COULD BE APPLIED TO VARIOUS GENRES AND COULD BLEND EASTERN AND WESTERN STYLES FOR BACKGROUND MUSIC IN THERAPY , MOVIES , GAMES , ETC
86	THIS WOULD ALLOW LISTENERS TO COMPOSE AND DOWNLOAD CUSTOMIZED MUSIC OF DIFFERENT GENRES , POTENTIALLY REVOLUTIONIZING MUSIC PRODUCTION
86	MOVING AHEAD , WE WOULD IMPLEMENT TRANSFORMER MODELS TO GENERATE SYNCHRONOUS TRACKS WITH MULTIPLE INSTRUMENTS
86	ARTIFICIAL INTELLIGENCE AIM , TO TRANSFORM THE MUSIC INDUSTRY BY PROVIDING NEW TOOLS AND METHODS FOR MUSIC COMPOSITION 
87	STATISTICAL COMPLEXITY AND OPTIMAL ALGORITHMS FOR NON LINEAR RIDGE BANDITS
87	WE CONSIDER THE SEQUENTIAL DECISION MAKING PROBLEM WHERE THE MEAN OUTCOME IS A NON LINEAR FUNCTION OF THE CHOSEN ACTION
87	COMPARED WITH THE LINEAR MODEL , TWO CURIOUS PHENOMENA ARISE IN NON LINEAR MODELS , FIRST , THERE IS AN BURN IN PERIOD WITH A FIXED COST DETERMINED BY THE NON LINEAR FUNCTION , SECOND , ACHIEVING THE SMALLEST BURN IN COST REQUIRES NEW EXPLORATION ALGORITHMS
87	FOR A SPECIAL FAMILY OF NON LINEAR FUNCTIONS NAMED RIDGE BANDITS , WE DERIVE UPPER AND LOWER BOUNDS ON THE OPTIMAL BURN IN COST , AS WELL AS ON THE ENTIRE LEARNING TRAJECTORY DURING THE BURN IN PERIOD VIA DIFFERENTIAL EQUATIONS
87	IN PARTICULAR , A TWO STAGE ALGORITHM THAT FIRST FINDS A GOOD INITIAL ACTION AND THEN TREATS THE PROBLEM AS LOCALLY LINEAR IS STATISTICALLY OPTIMAL
87	IN CONTRAST , SEVERAL CLASSICAL ALGORITHMS , SUCH AS UCB AND ALGORITHMS RELYING ON REGRESSION ORACLES , ARE PROVABLY SUBOPTIMAL
87	ARTIFICIAL INTELLIGENCE 
88	DIFFUSION MODEL BASED OVERSAMPLING FOR CLASS IMBALANCED PROBLEMS
88	OVERSAMPLING IS ONE OF THE IMPORTANT APPROACHES TO OVERCOME THE CLASS IMBALANCED PROBLEMS
88	SEVERAL OVERSAMPLING METHODS HAVE BEEN STUDIED BY UTILIZING LOCAL PROPERTY OF DATA OR GENERATIVE MODELS
88	IN THIS WORK , WE PROPOSE AN OVERSAMPLING METHOD BY EMPLOYING THE DENOISING DIFFUSION PROBABILISTIC MODELS , DDPM , FOR BINARY CLASSIFICATION
88	THE PROPOSED METHOD ADAPTS THE COSINE SCHEDULAR INSTEAD OF THE LINEAR SCHEDULAR FOR SMOOTH NOISING AND LEARNS VARIOUS IMBALANCED DATA DISTRIBUTIONS
88	WE AIM TO OVERSAMPLE THE MINORITY CLASSES DATA TO MAKE THE BALANCE IN TERMS OF THE FREQUENCY OF MINOR TO MAJOR
88	THE EXPERIMENTAL RESULTS DEMONSTRATED THAT OUR METHOD PERFORMED WELL WHEN COMPARED TO EXISTING OVERSAMPLING METHODS
88	ARTIFICIAL INTELLIGENCE 
89	CONSISTENCY REGULARIZATION FOR DISTORTION ROBUST SUPERVISED LEARNING 
89	CONVOLUTIONAL NEURAL NETWORKS , CNNS , HAVE SHOWN HIGH ACCURACY IN VARIOUS IMAGE CLASSIFICATION TASKS
89	HOWEVER , THEIR PERFORMANCE CAN BE SIGNIFICANTLY DEGRADED FOR DISTORTED IMAGES
89	TO ADDRESS THIS ISSUE , WE PROPOSE AN IMPROVED TRAINING METHOD FOR BUILDING A CNN ROBUST TO IMAGE DISTORTIONS
89	IT UTILIZES CONSISTENCY REGULARIZATION , A TECHNIQUE COMMONLY USED FOR SEMI SUPERVISED LEARNING , FOR SUPERVISED LEARNING
89	BY INCORPORATING A CONSISTENCY REGULARIZATION TERM INTO THE OBJECTIVE FUNCTION , THE CNN IS ENCOURAGED TO PRODUCE SIMILAR OUTPUTS FOR STRONG AND WEAK TRANSFORMATIONS OF THE SAME INPUT IMAGE , THEREBY ENHANCING THE ROBUSTNESS AGAINST IMAGE DISTORTIONS
89	EXPERIMENTAL RESULTS ON IMAGE CLASSIFICATION BENCHMARKS DEMONSTRATE THAT THE PROPOSED METHOD IMPROVES BOTH CLASSIFICATION ACCURACY AND ROBUSTNESS AGAINST IMAGE DISTORTIONS
89	ARTIFICIAL INTELLIGENCE 
90	REINFORCEMENT LEARNING WITH NON CONTRASTIVE LEARNING TO ENHANCE SAMPLE EFFICIENCY IN ATARI 
90	DEEP REINFORCEMENT LEARNING HAS SHOWN IMPRESSIVE PERFORMANCE IN SOLVING SEQUENTIAL DECISION MAKING PROBLEMS
90	HOWEVER , IT REQUIRES EXTENSIVE INTERACTIONS WITH IMAGE BASED ENVIRONMENTS
90	TO ADDRESS THIS CHALLENGE , IMPROVING SAMPLE EFFICIENCY HAS BECOME A PROMISING SOLUTION
90	WE PROPOSE AN APPROACH THAT COMBINES REINFORCEMENT LEARNING WITH NON CONTRASTIVE LEARNING , AND INCORPORATES ENVIRONMENTAL DYNAMICS TO ENHANCE SAMPLE EFFICIENCY
90	OUR METHOD ALSO PROVIDES AN EFFECTIVE LEARNING STRATEGY FOR STATE REPRESENTATION , LEVERAGING GATED RECURRENT UNITS TO CAPTURE TEMPORAL INFORMATION
90	WE DEMONSRATE THE EFFECTIVENESS OF THE PROPOSED METHOD THROUGH EXPERIMENTS ON THE ATARI GAME BENCHMARK , LIMITING THE ENVIRONMENT INTERACTIONS TO K STEPS
90	ARTIFICIAL INTELLIGENCE 
91	SEMI SUPERVISED LEARNING FOR CLASSIFICATION OF TRANSVERSE TEMPERATURE DEFECTS IN HOT ROLLED PRODUCTS
91	WE PROPOSE A SEMI SUPERVISED LEARNING MODEL TO CLASSIFY TRANSVERSE TEMPERATURE DEFECTS IN MATERIALS DURING HOT ROLLING
91	THERMAL IMAGING CAMERAS ARE USED TO MEASURE AND STORE THE TEMPERATURE DATA DURING HOT ROLLING PROCESS
91	TYPICALLY , CLASSIFICATION MODELS ARE USED TO CLASSIFY DEFECTS IN THE THERMAL IMAGES
91	HOWEVER , TRAINING CLASSIFICATION MODELS REQUIRES LABELED DATA , WHICH CAN BE TIME CONSUMING
91	TO ADDRESS THIS LABELING ISSUE , WE PROPOSE USING A SEMI SUPERVISED LEARNING MODEL THAT LEVERAGES BOTH LABELED AND UNLABELED DATA FOR TRAINING
91	OUR EXPERIMENTAL RESULTS CONFIRM THAT THE SEMI SUPERVISED LEARNING METHODS OUTPERFORM THE SUPERVISED LEARNING METHODS FOR THE ACCURATE DETECTION OF TRANSVERSE TEMPERATURE DEFECTS DURING HOT ROLLING
91	ARTIFICIAL INTELLIGENCE 
92	REINFORCEMENT LEARNING FOR IMAGE CLASSIFICATION
92	WE PRESENT A REINFORCEMENT LEARNING BASED APPROACH THAT LEVERAGES DATA AUGMENTATION TECHNIQUES TO IMPROVE THE ACCURACY OF IMAGE CLASSIFICATION TASKS
92	WE DEFINE THE ESSENTIAL COMPONENTS OF REINFORCEMENT LEARNING AND CREATE A SIMULATOR THAT ENABLES THE MODEL TO LEARN MORE AUTONOMOUSLY WHEN ADDITIONAL LEARNING IS REQUIRED
92	OUR EXPERIMENTS WITH VARIOUS BENCHMARK DATASETS DEMONSTRATE THAT THE REINFORCEMENT LEARNING BASED APPROACH OUTPERFORMS THE CONVENTIONAL CONVOLUTIONAL NEURAL NETWORKS IN TERMS OF CLASSIFICATION ACCURACY , HIGHLIGHTING ITS POTENTIAL TO EFFECTIVELY ADDRESS CLASSIFICATION PROBLEMS USING REINFORCEMENT LEARNING
92	ARTIFICIAL INTELLIGENCE 
93	TIME SERIES PERTURBATION BASED ON GRADIENT OF DEEP LEARNING MODELS
93	PERTURBATION REFERS TO A TINY CHANGE DESIGNED TO DEGRADE THE PERFORMANCE OF DEEP LEARNING MODELS
93	PERTURBATION IS USUALLY MADE ONCE BY WEIGHTS OF TRAINED MODEL , WHICH HAS DRAWBACKS , TIME COMPLEXITY IS RELATIVELY HIGH , AND PERTURBATION IS LIMITED TO THE LAST GRADIENT OF TRAINED MODEL
93	IN THIS PAPER , WE PROPOSE A NEW METHOD CAN MAKE THE PERTURBATION TO TIME SERIES WITH DEEP LEARNING MODEL
93	PREDICTION MODEL IS TRAINED FOR ORIGINAL PURPOSE , AND AN ADDITIONAL PERTURBATION MODEL IS TRAINED FOR ATTACK OF PREDICTION MODEL
93	THE PERTURBATION MODEL USES ORIGINAL TIME SERIES AND GRADIENT OF PREDICTION MODEL AS INPUT DATA AND LABEL , AND DERIVES THE CHANGING PERTURBATION TO ATTACK THE PREDICTION MODEL
93	THE EXPERIMENTAL RESULTS SHOWED THAT WITH REAL WORLD DATASET , THE PROPOSED METHOD OUTPERFORMED OTHER BENCHMARK METHODS IN TERMS OF PERFORMANCE DEGRADATION OF THE PREDICTION MODEL
93	ARTIFICIAL INTELLIGENCE 
94	TRANSFORMER BASED UNSUPERVISED ANOMALY DETECTION WITH MULTIVARIATE TIME SERIES
94	ANOMALY DETECTION IS ONE OF THE MOST IMPORTANT TASKS IN VARIOUS INDUSTRIES
94	FOR MULTIVARIATE TIME SERIES , MTS , , ANOMALY DETECTION METHODS HAVE BEEN PROPOSED BY CONSIDERING CHARACTERISTICS SUCH AS FREQUENCY AND TREND
94	WE PROPOSE A NOVEL TRANSFORMER BASED UNSUPERVISED ANOMALY DETECTION MODEL FOR MTS
94	THE PROPOSED METHOD CONSIDERS BOTH TIME AND FREQUENCY DOMAINS
94	THE PROPOSED MODEL FOR ANOMALY DETECTION INCLUDES INDEPENDENT MODULES TO DECOMPOSE THE SIGNAL AND EXTRACT INFORMATION IN THE TIME AND FREQUENCY DOMAINS
94	THE EXPERIMENTS EMPLOYING FOUR BENCHMARKS RESULTED THAT OUR METHOD OUTPERFORMED SEVERAL BENCHMARK METHODS , WHICH WAS PROMISING ENOUGH TO WARRANT FURTHER STUDY ON VARIOUS DOMAINS
94	ARTIFICIAL INTELLIGENCE 
95	CLUSTERING MORPHOLOGICAL PROPERTIES OF CELLS USING NEURAL NETWORK BASEDIMAGE SEGMENTATION MODELS
95	IMAGE BASED CELL PROFILING IS A METHOD THAT EXTRACTS FEATURES FROM CELL IMAGES TO QUANTIFY CELL INFORMATION
95	WITH RECENT ADVANCEMENTS IN CNN BASED RESEARCH , RECOGNITION OF SMALL OBJECTS SUCH AS MICROSCOPE IMAGES HAS BECOME FEASIBLE
95	IN THIS PAPER , WE PROPOSE A METHOD FOR CLUSTERING CELLS USING A COMBINATION OF NEURAL NETWORK BASED SEGMENTATION AND CLUSTERING MODELS BY UTILIZING A PRETRAINED MODEL ON THE LIVECELL DATASET
95	EXPERIMENTAL RESULTS DEMONSTRATED THAT THE PROPOSED METHOD SHOWED SUPERIOR PERFORMANCE COMPARED TO EXISTING CLUSTERING MODELS
95	ARTIFICIAL INTELLIGENCE 
96	PERSONALITY CLASSIFICATION WITH REDDIT DATA USING NATURAL LANGUAGE PROCESSING
96	RECENTLY , MYERS BRIX TYPE INDICATORS , MBTIS , ARE THE KEY KEYWORDS THAT IDENTIFY AND INFER PERSONAL CHARACTERISTICS OF COMMUNITY USERS
96	IN ADDITION , THE MBTIS HAVE BEEN INCREASINGLY USED IN BUSINESS FIELDS FOR A PERSONALIZED MANAGEMENT OF EMPLOYEES
96	IN THIS PAPER , WE PROPOSE AN MBTI CLASSIFICATION METHOD WITH NATURAL LANGUAGE PROCESSING , NLP , MODELS
96	THE MBTI REDDIT , CONSISTING OF REAL WORLD REDDIT DATA OF VARIOUS USERS , WAS USED FOR TRAIN
96	THE EXPERIMENT SHOWED THAT THE PROPOSED METHOD OUTPERFORMED THE CONVENTIONAL MACHINE LEARNING METHODS FOR REAL WORLD DATASET
96	ARTIFICIAL INTELLIGENCE 
97	MACHINE LEARNING TO SOLVE VEHICLE ROUTING PROBLEMS , A SURVEY
97	THIS PAPER PROVIDES A SYSTEMATIC OVERVIEW OF MACHINE LEARNING METHODS APPLIED TO SOLVE NP HARD VEHICLE ROUTING PROBLEMS , VRPS , 
97	RECENTLY , THERE HAS BEEN A GREAT INTEREST FROM BOTH MACHINE LEARNING AND OPERATIONS RESEARCH COMMUNITIES TO SOLVE VRPS EITHER BY PURE LEARNING METHODS OR BY COMBINING THEM WITH THE TRADITIONAL HAND CRAFTED HEURISTICS
97	WE PRESENT THE TAXONOMY OF THE STUDIES FOR LEARNING PARADIGMS , SOLUTION STRUCTURES , UNDERLYING MODELS , AND ALGORITHMS
97	WE PRESENT IN DETAIL THE RESULTS OF THE STATE OF THE ART METHODS DEMONSTRATING THEIR COMPETITIVENESS WITH THE TRADITIONAL METHODS
97	THE SURVEY INDICATES THE ADVANTAGES OF THE MACHINE LEARNING BASED MODELS THAT AIM TO EXPLOIT THE SYMMETRY OF VRP SOLUTIONS
97	THE PAPER OUTLINES THE FUTURE RESEARCH DIRECTIONS TO INCORPORATE LEARNING BASED SOLUTIONS TO OVERCOME THE CHALLENGES OF MODERN TRANSPORTATION SYSTEMS
97	ARTIFICIAL INTELLIGENCE 
98	AI , AUTOMATED ITINERARY , FOR ROAD TRIPS , 
98	WHEN PLANNING A ROAD TRIP , TRAVELERS TYPICALLY PLAN ROUTES , BOOK HOTELS , AND FIND LOCAL ATTRACTIONS USING DIFFERENT ONLINE PLATFORMS
98	THIS PRESENTATION WILL DISCUSS A TOOL THAT INTEGRATES GOOGLE MAPS , CHAT GPT , AND HOTEL PROPERTY LOCATION DATA TO DO ALL THREE THINGS IN ONE PLACE
98	THE TOOL STARTS WITH A LIST OF USER SPECIFIED REQUIRED STOPS AND USES A HEURISTIC TO GENERATE A LIST OF RECOMMENDED ADDITIONAL STOPS
98	THEN IT LEVERAGES CHATGPT PROMPTS TO GENERATE RELEVANT , FUN , AND SAFE RECOMMENDATIONS FOR A UNIQUE USER EXPERIENCE AT EACH ADDITIONAL STOP
98	ONCE A TRAVEL ITINERARY IS PLANNED , LOCATION DATA IS USED TO RECOMMEND HOTELS ALONG THE WAY
98	ARTIFICIAL INTELLIGENCE 
99	THE ECONOMIC ADVANTAGE OF COMPUTER VISION OVER HUMAN LABOR
99	WITH THE EMERGENCE OF ARTIFICIAL INTELLIGENCE , A I , , OUR LIVES AND ECONOMY ARE UNDERGOING A PROFOUND TRANSFORMATION
99	WHILE THERE ARE HUGE BENEFITS TO BE REALIZED BY THE TECHNOLOGY , WE MUST ALSO PREPARE FOR SHIFTING CIRCUMSTANCES , INCLUDING CHANGES IN MARKET DYNAMICS AND THE LABOR MARKET
99	THUS , TO INFORM POLICY , WE NEED TO UNDERSTAND AND FORECAST THE IMPLEMENTATION OF A I BR PREVIOUS FORECASTS OF A I PROLIFERATION HAVE FOCUSED ON THE TECHNICAL FEASIBILITY OF REPLACING HUMAN LABOR IN EXISTING TASKS
99	HOWEVER , SINCE THE DECISION TO DEPLOY A TECHNOLOGY IS ULTIMATELY AN ECONOMIC ONE , I DEVELOP A FRAMEWORK THAT COMPARES THE COST OF A I TO THE COST OF WORKER COMPENSATION
99	AS SUCH , THIS APPROACH CONSIDERS NOT ONLY TECHNICAL FEASIBILITY , BUT ALSO THE ECONOMIC ADVANTAGE OF A I OVER HUMAN LABOR BR USING THE FRAMEWORK , I EXAMINE THE CASE OF COMPUTER VISION IN THE U S NON FARM ECONOMY , DRAWING ON PREVIOUS WORK ON THE COST OF COMPUTER VISION , AS WELL AS GOVERNMENT DATA ON WAGES , TASKS , AND THE SIZE OF FIRMS
99	THE RESULTS SUGGEST THAT WHILE COMPUTER VISION CAN REPLACE HUMAN LABOR ACROSS SECTORS AND INDUSTRIES , IT WILL ONLY HAVE AN ECONOMIC ADVANTAGE OVER HUMAN LABOR IN THE VERY LARGEST ENTERPRISES
99	IN SMALLER COMPANIES , THE SUM OF TASK SPECIFIC EMPLOYEE COMPENSATION DOES NOT EXCEED SYSTEM DEVELOPMENT COSTS
99	DATA IS IDENTIFIED AS THE MAIN DRIVER OF TOTAL COMPUTER VISION DEVELOPMENT COSTS , PLACING INCUMBENT FIRMS AT AN ADVANTAGE IN THE RACE TO REALIZE THE ECONOMIES OF SCALE THAT COMPUTER VISION , AND A I IN GENERAL , ENABLE
99	ARTIFICIAL INTELLIGENCE 
100	MULTIDIMENSIONAL PROCUREMENT AUCTION WITH LOSS AVERSE WORKERS IN ONLINE LABOR MARKETS
100	SERVICE PROCUREMENT AUCTION INVOLVING MULTIDIMENSIONAL BIDS TYPICALLY A PROPOSAL AND A PRICE ARE UBIQUITOUS IN ONLINE LABOR MARKETS
100	WE STUDY THE IMPACT OF LOSS AVERSION BY THE USE OF GAME THEORETICAL ANALYSIS
100	WE SHOW , IN THE UNIQUE SYMMETRIC EQUILIBRIUM OF THIS SETTING , THAT WORKER S LOSS AVERSION BEHAVIOR ALWAYS DECREASES THEIR OWN EQUILIBRIUM EXPECTED UTILITY , BUT CAN INCREASE OR DECREASE THE BUYER S EQUILIBRIUM EXPECTED UTILITY , DEPENDING ON THE DEGREE OF LOSS AVERSION AND HOW THE BUYER VALUES THE WORKER S PROPOSAL TWO REIMBURSEMENT POLICIES THAT ARE COMMONLY USED IN PRACTICE AND STUDIED IN LITERATURE THE PERCENTAGE AND THE FLAT REIMBURSEMENT POLICY ARE INVESTIGATED AS A MITIGATION STRATEGY TO THE POTENTIAL NEGATIVE IMPACT OF LOSS AVERSION IN THE PROCUREMENT AUCTION
100	AUCTIONS AND MARKET DESIGN BEHAVIORAL OPERATIONS MANAGEMENT EMERGING TECHNOLOGIES AND APPLICATIONS 
101	SMART MICROTRANSIT , DESIGNING TO MAXIMIZE WELFARE AUCTIONS AND MARKET DESIGN DIVERSITY , EQUITY , AND INCLUSION OPT , NETWORK OPTIMIZATION
102	USEFUL POW MECHANISM DESIGN , ECONOMIC AND ENERGY EFFICIENCY FOR BLOCKCHAIN SYSTEMS
102	IN BLOCKCHAIN SYSTEMS , PROOF OF WORK , POW , IS AN ESSENTIAL CRYPTOGRAPHICAL PROTOCOL IN WHICH MINERS COMPETE TO COMPUTE RANDOM CHALLENGES FOR WRITING ACCESS OF BLOCKS
102	WHILE A MAJOR DISADVANTAGE TRADITIONAL POW IS LARGE OVERHEADS OF COMPUTATION AND ENERGY CONSUMPTION WITH NO BENEFICIAL USE , THE PROOF OF USEFUL WORK , POUW , INTRODUCES POW CHALLENGES THAT COMPUTES USEFUL PROBLEMS
102	WE STUDY THE MECHANISM DESIGN OF THE POUW MARKET BETWEEN CHALLENGE PROVIDERS AND MINERS IN ORDER TO ACHIEVE SOCIAL EFFICIENCY IN BOTH CRYPTOCURRENCY AND COMPUTATIONAL RESOURCES
102	AUCTIONS AND MARKET DESIGN EMERGING TECHNOLOGIES AND APPLICATIONS REVENUE MANAGEMENT AND PRICING
103	POPULAR MATCHING UNDER BOSTON SCHOOL CHOICE MECHANISM AND ITS APPLICATIONS
103	BOSTON MECHANISM IS A LONG ESTABLISHED MODEL FOR TWO SIDED MATCHING PROBLEMS WITH STRICT PREFERENCES ON ONE SIDE AND ROUGH PRIORITIES ON THE OTHER
103	THE MODEL FOCUSES ON THE WELFARE OF THE AGENTS WITH THE PREFERENCES
103	WE ANALYZE THE POPULARITY OF THE MATCHING PRODUCED USING THE BOSTON MECHANISM AND PROVIDE A CHARACTERIZATION OF THE POPULAR MATCHING AND THE MAXIMUM CARDINALITY POPULAR MATCHING IN THE MODEL
103	A POPULAR MATCHING IS THE ONE PREFERRED BY THE MAXIMUM NUMBER OF AGENTS AMONG ALL MATCHINGS
103	OUR PROPOSED POLYNOMIAL TIME ALGORITHM FINDS A POPULAR MATCHING IF THERE IS ANY IN SUCH A SETTING
103	THERE EXIST MANY CORRESPONDING APPLICATIONS OF POPULAR MATCHING UNDER THE BOSTON MECHANISM SUCH AS VOLUNTEER AND FOOD RESCUE TASKS MATCHING
103	AUCTIONS AND MARKET DESIGN FAIRNESS IN OPERATIONS COMPUTING SOCIETY
103	AN ORGANIZED DATASET CAN IMPROVE THE EFFICIENCY OF MATCHING STRATEGY OF TWO SIDED AGENTS 
104	OPTIMAL ASSEMBLY MECHANISMS WITH SECRET OFFERS
104	WE CONSIDER THE ISSUE OF CONTRACT CONFIDENTIALITY IN A DECENTRALIZED SUPPLY CHAIN , WHERE A SINGLE PRINCIPAL ORDERS DIFFERENT COMPONENTS FROM DIFFERENT AGENTS
104	CONTRARY TO CONVENTIONAL WISDOM IN THE LITERATURE , WE FIND THAT THE EFFICIENCY ACHIEVED THROUGH PUBLIC OFFERS CAN BE MAINTAINED EVEN WITH SECRET OFFERS IN AN ASSEMBLY SETTING
104	IN OUR SETTING THE TRILATERAL NEGOTIATION IS REDUCED TO A BILATERAL NEGOTIATION IF THE PRINCIPAL S OFFER TO ONE AGENT CAN MATCH THE OTHER AGENT S BELIEF , RESULTING IN AN OPPORTUNISM FREE SITUATION EVEN WHEN CONTRACTING TAKES THE FORM OF SECRET OFFERS
104	THIS IS A NOVEL FINDING IN THE LITERATURE , AND OUR ANALYSIS PROVIDES INSIGHTS INTO THE IMPORTANCE AND PREVALENCE OF NON DISCLOSURE AGREEMENTS IN PRACTICE
104	AUCTIONS AND MARKET DESIGN MANUFACTURING AND SERVICE OPERATIONS MANAGEMENT , MSOM , 
105	OPTIMAL BIDDING STRATEGY FOR SPONSORED ADVERTISING ON ECOMMERCE
105	REAL TIME BIDDING , RTB , IS A WIDELY USED MECHANISM IN ONLINE SPONSORED ADVERTISING , WHERE ADVERTISERS COMPETE TO SHOW THEIR ADS TO RELEVANT CUSTOMERS THROUGH REAL TIME AUCTIONS
105	HOWEVER , DERIVING THE OPTIMAL BIDDING STRATEGY CAN BE CHALLENGING DUE TO THE COMPLEXITY AND VOLATILITY OF THE AUCTION ENVIRONMENT
105	IN THIS TALK , WE WILL DISCUSS TWO MAIN BIDDING STRATEGIES THAT ARE DRIVEN BY CONSTRAINED OPTIMIZATION AND REINFORCEMENT LEARNING , TO HELP MAXIMIZE ADVERTISER S OBJECTIVE , S , IN SUP ND SUP PRICE AUCTION ENVIRONMENT ON WALMART ECOMMERCE
105	WE WILL DISCUSS THE ALGORITHM AND FORMULATION IN DETAILS , AND SHARE THE CHALLENGES AND INSIGHTS WHEN APPLYING THEM IN REAL WORLD SCENARIO
105	AT THE END , OUR EXPERIMENTS DEMONSTRATE THE EFFECTIVENESS AND EFFICIENCY OF THE PROPOSED BIDDING STRATEGIES THROUGH AUCTION SIMULATION IN TERMS OF OPTIMIZING AD CAMPAIGN PERFORMANCE
105	AUCTIONS AND MARKET DESIGN OPTIMIZATION , OPT , ARTIFICIAL INTELLIGENCE
105	MY WORK TALK USES OR MS MODELS TO GUIDE DECISION MAKING AND PRODUCE MEANINGFUL DATA IN THE CYCLE 
106	FAIR PRICE DISCRIMINATION
106	A SELLER IS PRICING IDENTICAL COPIES OF A GOOD TO A STREAM OF UNIT DEMAND BUYERS
106	EACH BUYER HAS A VALUE ON THE GOOD AS HIS PRIVATE INFORMATION
106	THE SELLER ONLY KNOWS THE EMPIRICAL VALUE DISTRIBUTION OF THE BUYER POPULATION AND CHOOSES THE REVENUE OPTIMAL PRICE
106	WE CONSIDER A WIDELY STUDIED THIRD DEGREE PRICE DISCRIMINATION MODEL WHERE AN INFORMATION INTERMEDIARY WITH PERFECT KNOWLEDGE OF THE ARRIVING BUYER S VALUE SENDS A SIGNAL TO THE SELLER , HENCE CHANGING THE SELLER S POSTERIOR AND INDUCING THE SELLER TO SET A PERSONALIZED POSTED PRICE
106	WE AIM TO FIND SIGNALING SCHEMES THAT IS FAIR TO THE BUYERS , AND WE SHOW THE SURPRISING EXISTENCE OF A NOVEL SIGNALING SCHEME THAT SIMULTANEOUSLY APPROXIMATES ALL WELFARE FUNCTIONS THAT ARE NON NEGATIVE , MONOTONICALLY INCREASING , SYMMETRIC , AND CONCAVE , E G THE UTILITARIAN SOCIAL WELFARE , THE NASH WELFARE , AND THE MAX MIN WELFARE , 
106	AUCTIONS AND MARKET DESIGN REVENUE MANAGEMENT AND PRICING FAIRNESS IN OPERATIONS
106	THIS WORK DEMONSTRATES HOW TO USE DATA OF BUYER VALUES TO INDUCE FAIR PRICE DISCRIMINATION 
107	WHO BENEFITS FROM MULTI CLOUD
107	A GAME THEORETIC ANALYSIS WHO BENEFITS FROM A MULTI CLOUD MARKET
107	A GAME THEORETIC ANALYSIS M A MULTI CLOUD MARKET
107	A GAME THEORETIC ANALYSIS
107	THE BENEFITS OF CLOUD COMPUTING , ALONG WITH ITS LIMITATIONS SUCH AS PROVIDER LOCK IN AND GEOGRAPHICAL RESTRICTIONS ON DATA , ARE LEADING TO THE FORMATION OF A NEW MULTI CLOUD MARKET IN WHICH CLOUD USERS WILL BE ABLE TO DISTRIBUTE THEIR WORKLOADS EASILY AND DYNAMICALLY ACROSS DIFFERENT CLOUDS
107	WHILE THIS IS EXPECTED TO BE BENEFICIAL TO USERS , PROVIDERS INCOME MAY REDUCE FROM SUCH A MOVE BR IN THIS WORK , USING TRADING NETWORKS , WE FORMALLY ANALYZE THE MULTI CLOUD MARKET AND SHOW THAT , SURPRISINGLY , USERS MAY ALSO PAY MORE IN SUCH A MARKET
107	MOREOVER , WE SHOW THAT WITH A CENTRALIZED BROKER , IT IS ALMOST ALWAYS POSSIBLE TO CREATE A MULTI CLOUD MARKET BENEFICIAL TO ALL WHEN ASSUMING TRUTHFUL REVELATION
107	FINALLY , WE SHOW THAT IT MANY CASES , USING AUTOMATED MECHANISM DESIGN , IT IS POSSIBLE TO LEARN MUTUALLY BENEFICIAL MECHANISMS WHERE TRUTHFUL VALUE REPORTING IS THE DOMINANT STRATEGY
107	AUCTIONS AND MARKET DESIGN 
108	OPTIMAL SLIDER DESIGN
108	THE USE OF SLIDERS TO SOLICIT BIDS FROM CUSTOMERS IS GAINING IN POPULARITY
108	WE LOOK AT THE OPTIMAL DESIGN OF SLIDERS FOR FIRMS USING THEM TO SOLICIT OFFERS
108	EXPLICIT NASH EQUILIBRIA ARE DERIVED FOR THE CASES WHERE THE CUSTOMER PERCEIVES THE THRESHOLD BEYOND WHICH A BID WILL BE ACCEPTED AS THE VALUE OF A UNIFORM OR TRIANGULAR RANDOM VARIABLE
108	WE EXTEND THE RESULTS NUMERICALLY TO MORE GENERAL DISTRIBUTIONS
108	OUR RESULTS SHOW THAT FIRMS CAN BOTH INCREASE CONSUMER PARTICIPATION , MAKING OFFERS , AND FIRM REVENUE THROUGH THE OPTIMAL DESIGN OF SLIDER SETTINGS
108	AUCTIONS AND MARKET DESIGN 
109	UNDERSTANDING TRADEOFFS BETWEEN TRAINING AND READINESS IN U S ARMY AVIATION
109	THE USAGE AND MAINTENANCE OF THE US ARMY S AH APACHE HELICOPTER ARE HIGHLY SCRUTINIZED , WITH MONTHLY REPORTS DETAILING FLYING HOURS AND READINESS RATES PREPARED FOR COMMANDERS ON THE SUP TH SUP OF EVERY MONTH
109	SINCE THE PUBLICATION OF ARMY REGULATION IN , THE ARMY HAS IMPOSED A READINESS REQUIREMENT ON ITS UNITS
109	FIRST , AN ANALYSIS OF SEVEN YEARS OF AH MAINTENANCE DATA ILLUSTRATES HISTORICAL PATTERNS SURROUNDING THE DECISION TO FLY NOT FLY AN INDIVIDUAL AIRCRAFT ON A GIVEN DAY , THE TIME UNTIL PHASE MAINTENANCE , AND THE UNIT READINESS RATINGS OVER TIME
109	ANALYSIS INCLUDES THE PRESENTATION OF AN EFFICIENT FRONTIER THAT CAPTURES TRADEOFFS BETWEEN READINESS AND FLIGHT HOURS , TRAINING PROFICIENCY , 
109	SECOND , A MATHEMATICAL MODEL IDENTIFIES RELEVANT FACTORS TO PROVIDE THE ARMY WITH DECISION SUPPORT TOOLS TO MAXIMIZE READINESS SUBJECT TO A READINESS CONSTRAINT
109	AVIATION APPLICATIONS MILITARY AND SECURITY BEHAVIORAL OPERATIONS MANAGEMENT
109	US ARMY AVIATION DATA HAS BEEN AGGREGATED BUT RARELY USED FOR POLICY LEVEL IMPLICATIONS 
110	MODELING FLIGHT INTERARRIVAL TIMES
110	RUNWAY CAPACITY IS A CRITICAL LIMITING FACTOR IN AIRPORT AND AIR TRAFFIC NETWORK EFFICIENCY
110	UNDERSTANDING THE BEHAVIOR OF CONTROLLED INTERARRIVAL TIME , I CIT I , AND THE OPERATIONAL CONDITIONS IS IMPORTANT
110	THIS WORK PRESENTS AN EMPIRICAL STUDY OF I CIT I AT LANDING RUNWAY THRESHOLD
110	A MATHEMATICAL MODEL IS DESIGNED TO FIT THE DISTRIBUTION OF OBSERVED RUNWAY CROSSING TIME INTERVAL , I RCTI I , FOR ARRIVAL PAIRS BY A CONDITIONAL PROBABILITY WITH UNIFORM DISTRIBUTION FOR ESTIMATED TIME OF ARRIVAL , I ETA I , AND NORMAL DISTRIBUTION FOR I CIT I 
110	BEHAVIOR OF I CIT I IS FURTHER EXPLAINED BY VARIABLES RELATING TO WEATHER , RUNWAY AND AIRCRAFT
110	THIS CONDITIONAL PROBABILITY MODEL CAPTURES THE SITUATION WHEN ARRIVAL DEMAND IS LOW AND TIME GAPS BETWEEN ARRIVALS ARE CONSTRAINED BY I ETA I S , AND ALSO IDEALLY APPROXIMATES THE LEFT HAND SIDE OF I RCTI I WHEN SHORT TERM ARRIVAL DEMAND EXCEEDS CAPACITY
110	AVIATION APPLICATIONS 
111	GENDER DIFFERENCES IN INVENTORY MANAGEMENT UNDER OBSTACLES
111	WE EXAMINE THE IMPACT OF TOP MANAGERS GENDER ON THE INVENTORY POLICY OF PRIVATE FIRMS AND THE EXTENT OBSTACLES IN BUSINESS ENVIRONMENT MODERATE THE RELATIONSHIP
111	WE USE DATA FROM WORLD BANK S ENTERPRISE SURVEYS COVERING , FIRM LEVEL OBSERVATIONS , FROM COUNTRIES
111	WE FIND THAT THE DAYS OF INVENTORY FOR FEMALE MANAGED FIRMS IS DAYS SMALLER THAN MALE MANAGED FIRMS , UNCONDITIONALLY
111	OBSTACLES IN TRANSPORTATION AND POLITICAL INSTABILITY PROVE SIGNIFICANTLY DIFFERENT INVENTORY LEVELS IN FEMALE AND MALE MANAGED FIRMS
111	AMONG MEDIUM SIZED FIRMS , FEMALE MANAGED ONES ARE MORE SENSITIVE TO FINANCIAL OBSTACLES AND LARGE SIZED FIRMS , THEY ARE MORE SENSITIVE TO TAX RATES THAN MALE MANAGED ONES
111	BEHAVIORAL OPERATIONS MANAGEMENT DATA , OR , AND SOCIAL JUSTICE 
111	WE ANALYZE FIRM LEVEL OBSERVATIONS TO STUDY THE IMPACT OF GENDER ON INVENTORY DECISIONS 
112	THE EFFECT OF INTERPRETABLE ARTIFICIAL INTELLIGENCE ON REPEATED MANAGERIAL DECISION MAKING UNDER UNCERTAINTY
112	MANY BUSINESS DECISIONS , SUCH AS MANAGING INVESTMENT INSTRUMENTS , SELECTING MEDICAL CARE , AND MANAGING VARIOUS SUPPLY CHAINS , ARE BEING MADE REPETITIVELY IN UNCERTAIN ENVIRONMENTS
112	AT TIMES , DECISIONS UNDER UNCERTAINTY COULD BE PERCEIVED AS WRONG EX POST EVEN THOUGH THEY ARE REALLY EX ANTE OPTIMAL
112	THEREFORE , DECISION MAKERS TEND TO INTUITIVELY RESIST TAKING ALGORITHMIC ADVICE UNDER HIGH UNCERTAINTY
112	IN OUR STUDY , WE EMPIRICALLY INVESTIGATE THE IMPACT OF VARIOUS COMMON INTERPRETABILITY FORMATS ON AI ADOPTION AND TRUST UNDER UNCERTAINTY
112	INTERESTINGLY , WE SHOW THAT EXPLAINING THE INNER WORKINGS OF A MODEL IN FACT DECREASES AI ADOPTION
112	ON THE OTHER HAND , FREQUENTLY SHARING THE CUMULATIVE PERFORMANCE OVER TIME OF BOTH THE USERS AND THE AI IMPROVES USERS TRUST IN THE MODEL
112	ON THE OTHER HAND , IT HAD NO NEGATIVE IMPACT ON THE AI ADOPTION RATE
112	BEHAVIORAL OPERATIONS MANAGEMENT DECISION ANALYSIS SOCIETY ARTIFICIAL INTELLIGENCE
113	LEVERAGING THE INTERNET OF THINGS AND AN UNDERSTANDING OF HUMAN BEHAVIOR IN CONDITION BASED PREVENTIVE MAINTENANCE
113	WE INVESTIGATE SETTINGS WHERE THE INTERNET OF THINGS AUGMENTS CONDITION BASED PREVENTIVE MAINTENANCE
113	INSPIRED BY FIELD CASE DATA AND ON SITE OBSERVATIONS , WE OBSERVE WORK BEHAVIORS THAT UNDERMINE THE FULL POTENTIAL OF THIS TECHNICAL BENEFIT AND CONSIDER MITIGATION OPTIONS
113	WE DELVE INTO THESE ISSUES THROUGH THE USE OF A MULTIMETHOD EMPIRICAL PERSPECTIVE
113	BEHAVIORAL OPERATIONS MANAGEMENT EMERGING TECHNOLOGIES AND APPLICATIONS MANUFACTURING AND SERVICE OPERATIONS MANAGEMENT , MSOM , 
114	THE PROBLEM WITH EVIDENCE BASED GUIDELINES ENDOGENOUS DYNAMICS OF EVIDENCE , POLICY , AND PRACTICE IN EARLY DETECTION
114	CLINICAL PRACTICE GUIDELINES , CPGS , FOR ROUTINE SCREENING ARE CONTENTIOUS
114	SOME TESTS ARE OVER OR UNDERUSED , WITH CLINICAL PRACTICE PERSISTENTLY DEVIATING FROM EVIDENCE
114	WHILE THERE IS A PROLIFERATION OF MODELING STUDIES TO INFORM CPGS , NOT MANY ARE ADDRESSING THE ACTUAL GUIDELINE MAKING PROCESS ITSELF
114	WE DEVELOP AN INTEGRATED , BROAD BOUNDARY FEEDBACK THEORY AND FORMAL SIMULATION MODELS TO INVESTIGATE THE UNIVERSAL PROBLEM OF EVIDENCE BASED DEVELOPMENT OF SOUND AND RELIABLE GUIDELINES
114	WE CONTINUE WITH AN EXTENDED CASE STUDY FOR CANCER SCREENING TO EXPLAIN WHY SOME TESTS ARE OVER WHILE OTHERS ARE UNDERUSED , CONTRARY TO SCIENTIFIC EVIDENCE
114	LONG TERM TRENDS IN POPULATION SCREENING AND RELATED PROBLEMS , SIGNIFICANT VARIATIONS , OVER AND UNDERUSE , GAPS BETWEEN EVIDENCE , POLICY , AND PRACTICE , SUBOPTIMALITY , AND FLUCTUATIONS IN GUIDELINES , ARE DISCUSSED
114	BEHAVIORAL OPERATIONS MANAGEMENT HEALTH APPLICATIONS SOCIETY DECISION ANALYSIS SOCIETY
115	DOING WELL BY BEING WELL , CORPORATE WELLNESS PROGRAMS AND INCENTIVES TO EXERCISE
115	MANY EMPLOYERS PROVIDE WELLNESS PROGRAMS THAT OFFER FINANCIAL INCENTIVES TO EMPLOYEES FOR EXERCISING , AS HEALTHIER EMPLOYEES ARE GENERALLY MORE PRODUCTIVE AND INCUR LOWER HEALTH INSURANCE COSTS COVERED BY EMPLOYERS
115	HOWEVER , WELLNESS PROGRAMS ARE NOT ALWAYS EFFECTIVE BECAUSE PEOPLE MAY RENEGE ON THEIR COMMITMENTS TO EXERCISE
115	WE THEN INVESTIGATE THE OPTIMAL DESIGN OF WELLNESS PROGRAMS REGARDING THE STRUCTURE AND SIZE OF FINANCIAL INCENTIVES
115	BEHAVIORAL OPERATIONS MANAGEMENT HEALTH APPLICATIONS SOCIETY SOCIAL OPERATIONS MANAGEMENT
116	THE EFFECT OF REMOVING THE FOUR HOUR ACCESS STANDARD IN THE ED , A RETROSPECTIVE OBSERVATIONAL STUDY
116	TIME BASED TARGETS ARE USED TO IMPROVE PATIENT FLOW AND QUALITY OF CARE WITHIN EMERGENCY DEPARTMENTS
116	WHILE PREVIOUS RESEARCH OFTEN HIGHLIGHTED THE BENEFITS OF THESE TARGETS , SOME STUDIES FOUND NEGATIVE CONSEQUENCES OF THEIR IMPLEMENTATION
116	WE FOUND THAT LIFTING THE FOUR HOUR STANDARD WAS ASSOCIATED WITH A DROP IN SHORT STAY ADMISSION AND AN INCREASE IN THE AVERAGE LENGTH OF STAY IN THE ED
116	BEHAVIORAL OPERATIONS MANAGEMENT HEALTH APPLICATIONS SOCIETY 
117	EXPLORING MANAGERIAL CHOICE MAKING AND INFORMATION BOUNDARIES IN GLOBAL FACILITY LOCATION DECISION MAKING PROCESS
117	GLOBAL FACILITY LOCATION DECISION MAKING , GFLD , IS A COMPLEX PROCESS THAT OFTEN PROMPTS MANAGERS , PARTICULARLY IN SMALL AND MEDIUM SIZED ENTERPRISES , SMES , TO ADOPT A SATISFICING APPROACH
117	HOWEVER , THE OPTIMAL AMOUNT OF INFORMATION NEEDED FROM SITE SELECTION INTERMEDIARIES REGARDING LOCATION ATTRIBUTES REMAINS UNCLEAR , AS MANAGERS MAY EMPLOY VARIOUS DECISION MAKING AND ASSESSMENT STRATEGIES
117	TO ADDRESS THIS GAP , OUR PAPER DELVES INTO THE CHOICE MAKING PROCESS OF MANAGERS AND INVESTIGATES THE INFORMATION BOUNDARIES WITHIN THE GFLD PROCESS SPECIFICALLY FOR SMES
117	USING QUASI EXPERIMENTS BASED ON VERBAL PROTOCOL ANALYSIS , INVOLVING STUDENTS AND SME MANAGERS , WE FOUND THAT MEDIUM INFORMATION VOLUME LED TO HIGHER SATISFACTION , SIMPLIFYING DECISION MAKING , IMPROVING OUTCOMES , AND GENERATING RELEVANT ATTRIBUTES , ALBEIT WITH SOME TRADE OFFS IN ACCURACY
117	BEHAVIORAL OPERATIONS MANAGEMENT LOCATION ANALYSIS 
118	MOBILE ADVERTISEMENT CAMPAIGNS FOR BOOSTING IN STORE VISITS , A DESIGN FRAMEWORK AND CASE STUDY
118	BRICK AND MORTAR RETAILERS AIM TO INCREASE FOOT TRAFFIC IN THEIR STORES FOR BETTER SALES OPPORTUNITIES
118	MOBILE LOCATION BASED ADVERTISING HAS BECOME A CRUCIAL MARKETING TOOL FOR REACHING POTENTIAL CUSTOMERS
118	HOWEVER , DESIGNING EFFECTIVE CAMPAIGNS REQUIRES COMPLEX ANALYSIS OF DATA TO TARGET THE RIGHT CUSTOMERS AT THE RIGHT TIME AND PLACE
118	WE PRESENT A CAMPAIGN DESIGN FRAMEWORK THAT CONSIDERS DATA ACQUISITION COSTS , DATA UTILIZATION , AND THE VARYING EFFECTS OF DATA ON CAMPAIGN PERFORMANCE
118	USING A REAL WORLD CASE STUDY , WE DEMONSTRATE THAT THE OPTIMAL ATTRIBUTES FOR TARGETING CUSTOMERS DEPEND ON THEIR PROXIMITY TO THE STORE
118	CAMPAIGNS THAT USE ALL OR A NAÏVE SUBSET OF DATA ATTRIBUTES YIELD LOWER RETURNS COMPARED TO OUR PROPOSED APPROACH
118	OUR FINDINGS HAVE IMPLICATIONS FOR MOBILE ADVERTISING CAMPAIGN DESIGN , DEPLOYMENT , AND FURTHER RESEARCH IN TARGETED ADVERTISING
118	BEHAVIORAL OPERATIONS MANAGEMENT MACHINE LEARNING FOR OPTIMIZATION INFORMATION SYSTEMS
119	AN INVISIBLE HAND , HOW I HIDDEN I BUSINESS CYCLE AFFECTS MARKET ENTRY
119	BUSINESS CYCLES ARE A PRIMARY DRIVER BEHIND A FIRM S EXPANSION OR CONTRACTION DECISIONS
119	HOWEVER , THERE IS INHERENT UNCERTAINTY ABOUT THE STATE OF THE BUSINESS CYCLE BECAUSE OBSERVED ECONOMIC FUNDAMENTALS ARE IMPERFECT INDICATORS
119	IN THIS PAPER , WE DEVELOP AN EQUILIBRIUM MODEL WITH AN ESTIMATION METHODOLOGY OF STRATEGIC ENTRY EXIT POLICIES
119	IN THE MODEL , FIRMS MAKE ENTRY EXIT DECISIONS BASED UPON A I BELIEF I DISTRIBUTION ABOUT THE UNDERLYING I HIDDEN I STATE OF BUSINESS CYCLE
119	THE MODELING AND ESTIMATION METHODOLOGY IS TESTED ON A DATASET OF CANADA S FAST FOOD INDUSTRY
119	OUR ESTIMATION RESULTS SHOW THAT THE CANADIAN FAST FOOD INDUSTRY IS RECESSION PROOF AS ITS MARGINAL PROFITABILITY IS LARGELY IMMUNE TO ECONOMIC DOWNTURNS
119	MOREOVER , A FIRM WITH HIGH EXPANSION BASE PROFIT IS NOT GUARANTEED TO MAINTAIN A STEADILY GROWING MARKET SHARE IF ITS NOT SUFFICIENTLY RECESSION PROOF
119	BEHAVIORAL OPERATIONS MANAGEMENT MACHINE LEARNING IN OPERATIONS 
120	VALUE ALLOCATION IN MAKE TO ORDER , MTO , AND MAKE TO STOCK , MTS , , AN EXPERIMENTAL STUDY
120	WE EXPLORE THE VALUE ALLOCATION IN TWO MAJOR PRODUCTION PROCEDURES , MAKE TO ORDER , MTO , AND MAKE TO STOCK , MTS , 
120	WEIGHING IN THE PREFERENCE OF VALUE CREATION ASSOCIATED WITH PRODUCERS TECHNOLOGY , WE POSIT THAT THE PRODUCERS SELECTION OF COST FOR PRODUCTION OUT OF THE PRICE IN MTO IS INFLUENCED BY THE LEVEL OF PRODUCERS TECHNOLOGY
120	THIS PREFERENCE IS ABSENT IN MTS WHEN PRODUCERS NEGOTIATE THE PRICE WITH THE CUSTOMERS
120	HOLDING VALUE CREATION CONSTANT , WE TEST THE VALUE ALLOCATION BETWEEN MTO AND MTS WITH A SERIES OF EXPERIMENTS AND WE FIND PRODUCERS SPITTING RATE WOULD FAVOR CUSTOMERS MORE WHEN THEIR TECHNOLOGY IS MORE ADVANCED IN MTO WHILE THE SPLITTING RATE REMAINS CONSTANT IN MTS
120	BEHAVIORAL OPERATIONS MANAGEMENT MANUFACTURING AND SERVICE OPERATIONS MANAGEMENT , MSOM , FAIRNESS IN OPERATIONS
121	DO CONSUMERS RETURN MORE WHEN THEY BROWSE MORE ALTERNATIVES
121	ALTHOUGH THE EXISTING LITERATURE ESTABLISHES A RELATIONSHIP BETWEEN PRODUCT VARIETY AND PURCHASE BEHAVIOR , THE IMPACT ON PRODUCT RETURNS HAS BEEN OVERLOOKED
121	TO ADDRESS THIS GAP , WE CONDUCT A STUDY USING CLICKSTREAM AND TRANSACTION DATA FROM MILLION UNIQUE VISITORS TO A FASHION ACCESSORIES E RETAILER
121	OUR INVESTIGATION UTILIZES A NATURAL EXPERIMENT SETTING , CAPITALIZING ON THE EXOGENOUS VARIATION CAUSED BY PRODUCT MODEL CHARACTERISTICS
121	THE FINDINGS REVEAL THAT BROWSING ONE MORE SKU NOT ONLY DECREASES THE LIKELIHOOD OF A CONSUMER VISIT BEING CONVERTED INTO AN ORDER BUT ALSO INCREASES THE PROBABILITY OF A PRODUCT RETURN
121	BEHAVIORAL OPERATIONS MANAGEMENT MANUFACTURING AND SERVICE OPERATIONS MANAGEMENT , MSOM , SUPPLY CHAIN AND LOGISTICS IN PRACTICE
122	THE CALL CENTER PRODUCTIVITY PUZZLE , AN EXAMINATION OF INTER AGENT VARIATIONS IN PRODUCTIVITY AND STRESS REACTIONS
122	THIS STUDY DELVES INTO THE PERFORMANCE DISCREPANCIES AMONG CALL CENTER AGENTS BY EXAMINING DIFFERENCES IN PRODUCTIVITY RATES AND RESPONSES TO WORK STRESSORS
122	USING EMPIRICAL ANALYSIS DRAWN FROM OVER , LOGGED CALLS IN A CALL CENTER , WE HIGHLIGHT THE SIGNIFICANT VARIATION IN PRODUCTIVITY , WITH THE MOST EFFICIENT AGENTS BEING TIMES QUICKER THAN THEIR SLOWER COUNTERPARTS
122	THE FINDINGS REVEAL UNIQUE REACTIONS TO STRESS STIMULI SUCH AS CALL VOLUME , AGENT LOAD , SHIFT FATIGUE , AND OVERWORK
122	INTERESTINGLY , NOT ALL AGENTS RESPOND SIMILARLY TO ESCALATING STRESS LEVELS , WITH SOME ACCELERATING , WHILE OTHERS DECELERATING
122	MOREOVER , AGENTS EXHIBIT VARYING DEGREES OF SUSCEPTIBILITY TO FLUCTUATING STRESSOR INTENSITY
122	THESE INSIGHTS UNDERSCORE THE IMPORTANCE OF RECOGNIZING INDIVIDUAL DIFFERENCES IN ENHANCING PRODUCTIVITY AND MANAGING WORK STRESS
122	BEHAVIORAL OPERATIONS MANAGEMENT MANUFACTURING AND SERVICE OPERATIONS MANAGEMENT , MSOM , 
122	IT UTILIZES A LARGE DATASET FROM CALL LOGS TO ANALYZE THE OPERATIONAL EFFICIENCY OF A CALL CENTER 
123	SELECTION AND MORAL HAZARD IN GIG AND TRADITIONAL AGENTS
123	THE PAPER IS TO SUMMARIZE THE QUESTIONS WE WANT TO ANSWER BASED ON THE ISSUES IN CALL CENTERS THAT ALIBABA IS MOSTLY CONCERNED WITH
123	WE DESCRIBE THE DATA WE WANT TO COLLECT AND EXPLAIN THE TWO STAGE ANALYSIS
123	WE WANT TO MEASURE THE EFFECTS OF CUSTOMERS EMOTION ON OPERATIONAL PERFORMANCE AND DECISIONS , AND EXPLORE NEW STAFFING AND ROUTING POLICIES TO IMPROVE SERVICE QUALITY
123	BEHAVIORAL OPERATIONS MANAGEMENT MSOM , SERVICE OPERATIONS 
124	PRODUCT DESIGN AND BRANDING DECISION IN THE PRESENCE OF BRAND SPILLOVERS
124	WHEN CONSUMERS EVALUATE THE QUALITY OF A BRANDED FIRM S NEW PRODUCT , THEIR PERCEPTION OF THAT FIRM S EXISTING PRODUCTS CAN INFLUENCE THEIR EVALUATION WITH SOME BIAS
124	CONSIDERING SUCH A BRAND SPILLOVER EFFECT , WE ANALYTICALLY EXAMINE A BRANDED FIRM S QUALITY CHOICE AND BRAND STRATEGY FOR ITS NEW PRODUCT
124	OUR RESULTS SHOW THAT THE FIRM S OPTIMAL STRATEGY DEPENDS ON THE QUALITY LEVEL OF ITS EXISTING PRODUCT AND THE RATIO OF TWO TYPES OF CONSUMERS WHO DIFFER IN THEIR ATTITUDES TO THE QUALITY CHANGE WITH THE NEW PRODUCT OFFERING
124	UNLIKE THE RESULTS IN THE RELATED LITERATURE , IT CAN BE OPTIMAL TO SET THE STRENGTH OF SPILLOVER AT AN INTERMEDIATE LEVEL THROUGH A USE OF SUB BRAND
124	BEHAVIORAL OPERATIONS MANAGEMENT NEW PRODUCT DEVELOPMENT 
125	THE IMPACT OF ECONOMIC INSECURITY ON COVID MITIGATION EFFORTS
125	DUE TO THE WAY THAT THE US FEDERAL GOVERNMENT DELEGATED THE EFFORT TO MITIGATE THE IMPACT OF THE COVID PANDEMIC TO STATE GOVERNMENTS , WE SAW HOW VARIOUS PREVENTION METHODOLOGIES SIGNIFICANTLY IMPACTED BOTH STATE INFECTION RATES AND ECONOMIC IMPACTS
125	DIFFERENT LOCKDOWN PROTOCOLS , SOCIAL DISTANCING MANDATES , AND MASK REQUIREMENTS , IMPLEMENTED OVER THE FIRST THREE WAVES OF THE PANDEMIC WERE POSITED TO HAVE DIFFERENT IMPACTS DEPENDENT ON STATE CULTURE , CLIMATE , AND ECONOMIC STABILITY
125	OUR WORK COMPARES TWO ECONOMICALLY SIMILAR STATES CALIFORNIA AND FLORIDA AND DEMONSTRATES HOW A STATE S VIEW OF ECONOMIC INSECURITY SIGNIFICANTLY DROVE INFECTIONS RATES AND ECONOMIC RECOVERIES
125	BEHAVIORAL OPERATIONS MANAGEMENT PANDEMIC MANAGEMENT MSOM , HEALTHCARE
125	THE RELATIONSHIP BETWEEN BEHAVIORAL DATA AND ECONOMIC RECOVERY PROGRESSION IS A THEMATIC EXAMPLE 
126	IMPACT OF REMORT WORK ON FIRMS DATA BREACH RISKS
126	AS FIRMS SWITCH TO LONG TERM REMOTE WORKFORCES AS THE EFFECTS OF COVID LINGER , HOW TO EFFECTIVELY DEAL WITH DATA BREACH RISKS HAS BECOME A CRITICAL AND THORNY ISSUE
126	DOES REMOTE WORK INCREASE FIRMS DATA BREACHES
126	IF YES , UNDER WHAT CIRCUMSTANCES CAN THE NEGATIVE IMPACT BE OFFSET
126	TO ANSWER THESE RESEARCH QUESTIONS , WE MANUALLY INTEGRATE DATA BREACH LEAKAGE DATA FROM TWO MAJOR DATABASES AND MATCH THE DATA BREACH DATA WITH FIRMS REMOTE WORK ARRANGEMENT DATA
126	WE ALSO EMPLOY A QUASI EXPERIMENTAL DESIGN USING THE PSM DID ANALYSIS METHOD TO COMPARE THE TREATED AND CONTROL GROUPS
126	THE RESULTS REVEAL THAT REMOTE WORK ARRANGEMENTS SIGNIFICANTLY INCREASE FIRMS DATA BREACHES
126	WE FURTHER EXAMINED THAT THE NEGATIVE IMPACT MAY BE MITIGATED IF FIRMS HAVE PRIOR DATA BREACH EXPERIENCE BEFORE WFH ARRANGEMENTS AND HAVE A HIGH LEVEL OF IT INPUT
126	BEHAVIORAL OPERATIONS MANAGEMENT PANDEMIC MANAGEMENT SOCIAL OPERATIONS MANAGEMENT
126	WE EXPLORE HOW TO MANAGE DATA BREACH ASSOCIATED WITH REMOTE WORK 
127	PRICE SIGNAL IN CONSPICUOUS CONSUMPTION
127	IN CONSPICUOUS CONSUMPTION , IF CONSUMERS LACK INFORMATION ON ACTUAL DEMAND DISTRIBUTION , THEY ARE UNCERTAIN ABOUT THE LEVEL OF EXCLUSIVITY FOR WHICH THEY ARE WILLING TO PAY A PREMIUM
127	WE SHOW THAT THE PRICE SET BY A MONOPOLISTIC SELLER WHO HAS FULL KNOWLEDGE OF DEMAND DISTRIBUTION CAN SERVE AS A SIGNAL FOR CONSUMERS TO ESTIMATE THE LEVEL OF EXCLUSIVITY
127	CONSPICUOUS CONSUMPTION BASED ON THE PRICE SIGNAL MECHANISM EXHIBITS A CONVENTIONAL PATTERN OF SELLING TO FEWER CONSUMERS AT A HIGHER MARKUP
127	HOWEVER , THE NATURE OF THIS MECHANISM TENDS TO CAUSE CONSUMERS TO UNDERESTIMATE THE CONSPICUOUS VALUE , RESULTING IN A LOSS FOR THE SELLER OR EVEN THE ELIMINATION OF CONSPICUOUS CONSUMPTION
127	OUR FINDINGS ARE ROBUST IN BOTH CONTEXTS WHERE CONSUMER TYPES ARE SUBJECT TO BINARY AND CONTINUOUS DISTRIBUTION
127	BEHAVIORAL OPERATIONS MANAGEMENT REVENUE MANAGEMENT AND PRICING DECISION ANALYSIS SOCIETY
128	PRICE OBFUSCATION IN ONLINE PLATFORMS , WHEN CAN TRANSPARENCY PAY
128	MANY POPULAR CONSUMER FACING PLATFORMS OFFER TO REDUCE SEARCH COSTS AND EFFICIENTLY FIND LOWEST PRICES
128	UNDER COMPETITIVE PRESSURE , HOWEVER , THE PLATFORM S INCENTIVES MAY NOT DIRECTLY ALIGN WITH THOSE OF THEIR CONSUMERS
128	WE STUDY THE EFFECTS OF PRICE OBFUSCATION ON PLATFORM PERFORMANCE , AND ON CONSUMER WELFARE , BY AUGMENTING CURRENT MODELS TO INCORPORATE MULTIPLE SOURCES OF COMPETITIVE PRESSURE , CONSUMER BEHAVIORAL LEARNING , AND EXPLICITLY ACCOUNT FOR THE ROLE OF TRUST , AND THE EFFECTS OF REPUTATION BUILDING
128	BEHAVIORAL OPERATIONS MANAGEMENT REVENUE MANAGEMENT AND PRICING FAIRNESS IN OPERATIONS
128	GIVEN THE RISE IN MATCHING PLATFORMS IT S IMPORTANT UNDERSTAND THEIR INCENTIVES 
129	FREE FREIGHT OR NOT
129	RETAIL PLATFORM OPERATIONS UNDER REFERENCE PRICE EFFECT
129	WE INCORPORATE REFERENCE PRICE EFFECT INTO A HOTELLING MODEL TO CHARACTERIZE THE PRICING AND FREIGHT DECISIONS OF TWO COMPETITIVE RETAIL PLATFORMS
129	OUR RESULTS FIND RETAIL PLATFORMS PREFER SEQUENTIAL PRICING OVER SIMULTANEOUS PRICING , AND FREE FREIGHT WILL NOT AFFECT THE PLATFORMS OPERATIONAL DECISIONS IF THE REFERENCE PRICE EFFECT IS IGNORED
129	BEHAVIORAL OPERATIONS MANAGEMENT REVENUE MANAGEMENT AND PRICING SUPPLY CHAIN AND LOGISTICS IN PRACTICE
130	THE EFFECT OF THE AUTOMATION OF MANAGERIAL CONTROLS ON ORGANIZATIONAL OUTCOMES , AN EXPERIMENTAL EXAMINATION OF THE HIDDEN COSTS OF AI BASED CONTROLS
130	THE RELIANCE ON AUTOMATION AND AI IN MANAGERIAL CONTROLS IN THE WORKPLACE HAS BEEN SUBJECT TO A HEAVY DEBATE IN RECENT YEARS
130	AUTOMATED WORKPLACE CONTROLS RANGE FROM INSTALLING A SURVEILLANCE CAMERA TO MICROCHIPPING EMPLOYEES TO TRACK THEIR WHEREABOUTS
130	THIS STUDY USES A CONTROLLED EXPERIMENT TO EXAMINE WHETHER AND HOW THE AUTOMATION OF MANAGERIAL CONTROLS IMPACTS ORGANIZATIONAL OUTCOMES
130	WE MANIPULATED BETWEEN SUBJECTS WORKPLACE CONTROLS AT LEVELS , LOW , MEDIUM , AND HIGH AUTOMATION , AND RECRUITED US EMPLOYEES
130	RESULTS SHOW THAT THE AUTOMATION OF CONTROLS INCREASES EMPLOYEE PERFORMANCE , YET , DECREASES ORGANIZATIONAL COMMITMENT AND CITIZENSHIP WHILE INCREASING TURNOVER RATE
130	IN ADDITION , EMPLOYEES DEMAND HIGHER WAGE PREMIUMS WHEN CONTROLS ARE AUTOMATED
130	HOWEVER , THE NEGATIVE EFFECTS OF INCREASED CONTROL AUTOMATION ARE MODERATED FOR YOUNGER GENERATIONS
130	BEHAVIORAL OPERATIONS MANAGEMENT TECHNOLOGY , INNOVATION MANAGEMENT AND ENTREPRENEURSHIP ARTIFICIAL INTELLIGENCE
130	MY RESEARCH EMPIRICALLY EXAMINES HOW THE USE OF AI AND AUTOMATING WORKPLACE CONTROLS IMPACT FIRMS 
131	THE IMPACT OF SAFETY AND PRODUCTIVITY REMINDERS ON WAREHOUSE DRIVER BEHAVIOR , AVR EXPERIMENT
131	BALANCING OFTEN COMPETING GOALS OF PRODUCTIVITY AND SAFETY IS AN ONGOING CHALLENGE IN WAREHOUSES
131	DESPITE THE ORGANIZATIONS EMPHASIS ON SAFE AND PRODUCTIVE WORK , THE COMBINED IMPACT OF EMPHASIS ON SPEED , QUALITY , AND SAFETY REMAINS UNCLEAR
131	THIS STUDY EMPLOYS A LABORATORY EXPERIMENT INVOLVING A VR SIMULATOR TO EXAMINE THE IMPACT OF AUDIO REMINDERS WITH DIFFERENT LEVELS OF SPECIFICITY IN TERMS OF CONTENT AND EXPOSURE TIME ON THE PERFORMANCE OF WAREHOUSE VEHICLE DRIVERS
131	WE ALSO MEASURE INDIVIDUAL DIFFERENCES BETWEEN DRIVERS , IN TERMS OF REGULATORY FOCUS
131	MOREOVER , WE ALSO TRACK HEAD MOVEMENTS AS A POTENTIAL MECHANISM IN THE RELATIONSHIP BETWEEN AUDIO , HEAD ORIENTATION , AND DRIVERS PERFORMANCE
131	BEHAVIORAL OPERATIONS MANAGEMENT 
132	A SOCIAL TRUTH TELLING MECHANISM IN INFORMATION SHARING 
132	IN THIS STUDY , WE AIM TO UNDERSTAND HOW SOCIAL PREFERENCE AND TRUST INTERACT AND IMPACT INFORMATION SHARING UNDER THE TARGET WITH BONUS INCENTIVE COMPENSATION SCHEME
132	BEHAVIORAL OPERATIONS MANAGEMENT 
133	THE DOUBLE EDGED EFFECTS OF COMPETITIVE REWARD STRUCTURE , BASED ON SOCIAL INTERDEPENDENCE THEORY
133	DESPITE THE PREVALENCE OF COMPETITIVE MECHANISMS , THEIR EFFECTIVENESS HAS BEEN UNDER ONGOING AND EXTENSIVE DEBATE , PROMPTING THE NEED FOR FURTHER EXPLORATION
133	THIS STUDY FOCUSES ON THE MOST TYPICAL MANIFESTATION OF COMPETITIVE MECHANISMS , COMPETITIVE REWARD STRUCTURE
133	BASED ON SOCIAL INTERDEPENDENCE THEORY , WE INVESTIGATE HOW AND WHEN IT INFLUENCES EMPLOYEES COMPETITIVE BEHAVIORS
133	UTILIZING A WAVE DATA COLLECTED FROM EMPLOYEES , WE FIND THAT COMPETITIVE REWARD STRUCTURE BOOSTS EMPLOYEES COMPETITIVE MOTIVATION , WHICH EVOKES HIGH LEVEL JOB PERFORMANCE AND INCURS SOCIAL UNDERMINING TOWARDS THEIR COWORKERS
133	ZERO SUM BELIEFS STRENGTHEN THE EFFECT OF COMPETITIVE REWARD STRUCTURE ON COMPETITIVE MOTIVATION AS WELL AS THE INDIRECT EFFECT OF COMPETITIVE REWARD STRUCTURE ON JOB PERFORMANCE AND SOCIAL UNDERMINING VIA COMPETITIVE MOTIVATION
133	BEHAVIORAL OPERATIONS MANAGEMENT 
134	DISCRETION IN AUTOMATED SUPERMARKET REPLENISHMENT , CENSORSHIP BIAS AND SELF INFLICTED STOCKOUTS
134	RETAIL STORE MANAGERS CAN USE THEIR DISCRETION TO ADJUST ORDER PROPOSALS OF AUTOMATIC STORE REPLENISHMENT , ASR , SYSTEMS TO INCORPORATE THEIR PRIVATE KNOWLEDGE
134	APART FROM OCCASIONALLY IMPROVING ORDERING DECISIONS WITH HUMAN INSIGHTS THAT IS NOT AVAILABLE TO THE ASR SYSTEM , STORE MANAGERS ARE SUSPECT TO BIASES
134	WE EXAMINE THE PREVALENCE AND PERFORMANCE IMPLICATIONS OF CENSORSHIP BIAS , WHICH EXPLAINS A PARADOX WHERE RETAILERS ORDER LESS THAN ASR PROPOSALS AFTER A STOCKOUT
134	ACCOUNTING FOR THE ENDOGENEITY OF ORDERING DECISIONS , WE SHOW THAT CENSORSHIP BIAS IS EQUALLY PREVALENT AND DETRIMENTAL AS THE WELL KNOWN ANCHORING BIAS OF ORDERING BEHAVIOR
134	BY OUT OF SAMPLE ANALYSIS , WE SHOW THAT ASR SYSTEMS CAN BE IMPROVED TO BLOCK DEVIATIONS SUSCEPTIBLE TO CENSORSHIP BIAS
134	BEHAVIORAL OPERATIONS MANAGEMENT 
135	HOW TO MAKE YOU TRUST ME ALL THE TIME
135	GUIDANCE STRATEGIES IN A COST LOSS GAME
135	THE EXPERT POSSESSES KNOWLEDGE REGARDING THE POSSIBILITY OF A STATE S REALIZATION THAT THE DECISION MAKER LACKS AND OFFERS AN UNEQUIVOCAL ADVICE TO THE DECISION MAKER , WHO THEN DETERMINES WHETHER TO FOLLOW THE ADVICE
135	THE DECISION MAKER S ACTION IMPACTS THE WELFARE OF BOTH PLAYERS
135	HOW CAN THE EXPERT PERSUADE THE NONEXPERT DECISION MAKER TO FOLLOW HIS ADVICE , EVEN WHEN THEIR BENEFITS ARE NOT COMPLETELY ALIGNED
135	WE TEST TWO STRATEGIES TO CONVEY THIS ADVICE , BAYESIAN PERSUASION AND THIRD THRESHOLD
135	WE CONSIDER A COST LOSS GAME WITH HETEROGENEOUS PAYOFFS BETWEEN PLAYERS , IN WHICH DECISION MAKERS DECIDE WHETHER TO TAKE A RISK OF A LOSS OR PAY A COST TO AVOID THE RISK
135	WE FIND THAT THE THIRD THRESHOLD STRATEGY IS SUPERIOR FOR THE EXPERT
135	BEHAVIORAL OPERATIONS MANAGEMENT WE STUDY HOW TO LET THE ADVICE RECEIVER TRUST THE EXPERT WHO CAN INTERPRET DATA WITH HIS KNOWLEDGE 
136	THE COMPUTE DIVIDE IN MACHINE LEARNING , A THREAT TO ACADEMIC CONTRIBUTION AND SCRUTINY
136	WE PROVIDE AN ANALYSIS OF HOW THE COMPUTE DIVIDE SHAPES MACHINE LEARNING RESEARCH , PRESENTING A DATA DRIVEN SURVEY OF ITS IMPLICATIONS
136	WE SHOW THAT THIS DIVIDE COINCIDES WITH LESS ACADEMIC PRESENCE IN COMPUTE INTENSIVE TOPICS
136	THIS TREND IS PRONOUNCED IN FOUNDATION MODELS , LIKE LARGE LANGUAGE MODELS
136	WE ARGUE THAT ACADEMIA MAY PLAY A SMALLER ROLE IN ADVANCING RELATED TECHNIQUES , PROVIDING EVALUATION AND SCRUTINY , AND IN DIFFUSING SUCH MODELS PUBLICLY
136	CONCURRENTLY , WE SEE A RISE IN INDUSTRY DEVELOPED OPEN SOURCE PRE TRAINED MODELS
136	OUR WORK OFFERS POLICY AND GOVERNANCE RECOMMENDATIONS TO NAVIGATE THIS TREND , AIMING TO ADDRESS THE POTENTIAL ISSUES WE IDENTIFY , SPECIFICALLY THE LOSS OF SCRUTINY AND TRUST IN AI SYSTEMS
136	COMPUTING SOCIETY 
137	USING DECISION TREES TO EXPLAIN MACHINE LEARNING MODELS
137	MACHINE LEARNING ALGORITHMS CAN BE POWERFUL TOOLS IN COMPLEX ANALYTIC MODELS
137	HOWEVER , USING A MACHINE LEARNING MODEL IS CONSIDERED BLACK BOX TECHNIQUE , WHERE THE RELATIONSHIPS BETWEEN INPUTS AND TARGET CANNOT BE DIRECTLY COMMUNICATED FOR EXPLANATORY PURPOSES
137	THE APPEAL OF USING TRADITIONAL STATISTICAL MODELS , SUCH AS REGRESSION , BECAUSE THE MAGNITUDE AND DIRECTIONAL IMPACT , POSITIVE OR NEGATIVE , OF EACH MODEL INPUT CAN BE DETERMINED , OFTEN OVER RULES THE USE OF MACHINE LEARNING MODELS , PARTICULARLY IN OBSERVATIONAL STUDIES , USING DECISION TREES AFTER A MACHINE LEARNING MODEL IS BUILT , CAN HELP REMOVE MOST OF THE AMBIGUITY THAT COMES WITH THESE BLACK BOX ALGORITHMS THE COMBINATION OF MACHINE LEARNING AND DECISION TREES ALLOWS THE MODELER TO TAKE ADVANTAGE OF THE FLEXIBILITY AND STRENGTH OF THE ALGORITHMS WITHOUT LOSING THE INTERPRETABILITY
137	DATA MINING APPLIED PROBABILITY ARTIFICIAL INTELLIGENCE
137	DEMYSTIFYING MACHINE LEARNING 
138	ANOMALY DETECTION IN TIME SERIES USING A HYBRID DEEP LEARNING ONE CLASS ALGORITHM
138	DETECTING ANOMALIES IN TIME SERIES DATA IS AN IMPORTANT AREA OF RESEARCH WITH APPLICATIONS IN A WIDE VARIETY OF FIELDS INCLUDING FINANCE , TRANSPORTATION , HEALTH MONITORING , ETC
138	IN THIS WORK WE PRESENT A HYBRID ALGORITHM CONSISTING OF A AUTO ENCODER ARCHITECTURE AS A FEATURE EXTRACTOR AND A ONE CLASS PEELING , OCP , SUPPORT VECTOR MACHINE , SVM , ALGORITHM AS A DISCRIMINATOR TO DETECT POTENTIAL NOVEL AND ANOMALOUS OBSERVATIONS
138	WE FIND THAT THE PROPOSED HYBRID ALGORITHM PERFORMS FAVORABLY AGAINST OTHER COMPETING DEEP LEARNING , STATISTICAL AND MACHINE LEARNING METHODOLOGIES
138	DATA MINING ARTIFICIAL INTELLIGENCE APPLIED PROBABILITY 
139	TRIAGE IN HOSPITAL APPOINTMENT SCHEDULING
139	FOR MEDICAL CARE APPOINTMENT , A FIRST IN FIRST OUT APPROACH MAY NOT BE THE MOST PREFERRED AND EFFECTIVE APPROACH
139	SCHEDULING DOCTORS APPOINTMENTS FOR HOSPITALS IS A HUGE TASK
139	BECAUSE OF THE NUMBER OF CALLS RECEIVED PER DAY , CRITICAL SITUATIONS MAY BE MISSED DUE TO THE ENORMOUS NUMBER OF CALLERS
139	THERE IS THEREFORE A NEED FOR MORE AUTOMATED PROCESSES THAT CAN CATEGORIZE AND PRIORITIZE PHONE CALLS BASED ON THEIR URGENCY
139	THIS STUDY WILL BE APPLYING A DATA MINING APPROACH THAT CAN ANALYZE AND CLASSIFY CALLS USING THE TRIAGE CONCEPT
139	WITH THE USE OF ARTIFICIAL INTELLIGENCE METHODOLOGIES , SUCH AS THE GENERATIVE AI THESE CALLS CAN BE PRIORITIZED TO DETERMINE AN OPTIMIZED SCHEDULE FOR THE SERVICE PROVIDERS
139	THE RESULT OF THIS WILL BE IMPROVED CUSTOMER SERVICE , PRIORITIZATION OF URGENT CALLS WHICH WILL LEAD TO EFFICIENCY IN SERVICE DELIVERY
139	DATA MINING ARTIFICIAL INTELLIGENCE HEALTH APPLICATIONS SOCIETY
139	THE USE OF ARTIFICIAL INTELLIGENCE TO HELP IN DECISION MAKING FOR SCHEDULING MEDICAL APPOINTMENTS 
140	A HYBRID ANALYTICS FRAMEWORK TOWARD BETTER EXPLANATIONS , THE CASE OF SURVIVAL AFTER LUNG TRANSPLANTATION
140	WE PROPOSE A HYBRID ANALYTICS FRAMEWORK FOR IMPROVING THE INTERPRETABILITY OF BLACK BOX ML MODELS
140	USING A FEATURE SELECTION STRATEGY , SUPERVISED AND UNSUPERVISED LEARNING , AND EXPLANATION METHODS , OUR GOAL IS TO OFFER MEDICAL PROFESSIONALS A TOOL THAT , PROVIDES FURTHER INSIGHT INTO THE MOST IMPORTANT FACTORS INVOLVED IN A PROGNOSTIC OR SURVIVAL ANALYSIS AND , ALSO , ADDS FLEXIBILITY TO THE DEVELOPMENT OF EFFECTIVE CLINICAL DECISION SUPPORT SYSTEMS
140	WE APPLY THE PROPOSED FRAMEWORK TO INVESTIGATE THE FACTORS INVOLVED IN PATIENTS SHORT AND LONG TERM SURVIVAL AFTER LUNG TRANSPLANTATION
140	THE RESULTS CAN ASSIST IN DEVELOPING MORE EFFECTIVE INDICATORS FOR LUNG ALLOCATION DECISIONS , ULTIMATELY LEADING TO IMPROVED TRANSPLANTATION BENEFITS
140	DATA MINING ARTIFICIAL INTELLIGENCE HEALTH APPLICATIONS SOCIETY
141	EVALUATION IMPUTATION IN A TWO WAY TABLE OF MEANS FOR TRAINING DATA CONSTRUCTION
141	THE PROCESS OF PREDICTIVE MACHINE LEARNING STARTS WITH A TRAINING DATASET
141	FOR EACH OF TWO PREDICTOR VARIABLES AND A RESPONSE VARIABLE , THE TRAINING DATASET CAN BE CONVERTED INTO A TWO WAY TABLE WHERE THE ROWS AND COLUMNS ARE EACH OF THE PREDICTOR VARIABLES AND THE VALUES OF EACH CELL ARE THE VALUE OF THE RESPONSE VARIABLE CORRESPONDING TO THOSE PREDICTOR VARIABLES
141	THIS TWO WAY TABLE CAN BE HIGHLY SPARSE WITH A LOT OF MISSING VALUES WHERE EACH MISSING VALUE REPRESENTS AN OBSERVATION THAT COULD HAVE BEEN POSSIBLY MADE BUT HASN T THE VALUES FOR MISSING OBSERVATIONS CAN BE CONSTRUCTED USING IMPUTATION METHODS
141	THIS RESEARCH STUDY IMPUTATION METHODS IN TWO WAY TABLES TO INVESTIGATE HOW THEY CAN BE USED FOR CONSTRUCTING NEW DATA POINTS WHEN THE TWO WAY TABLE IS CONVERTED BACK TO THE TRAINING DATASET THEN ANALYZE HOW WELL SUCH DATA CONSTRUCTION IMPROVE QUALITY OF PREDICTIVE MODELS
141	DATA MINING ARTIFICIAL INTELLIGENCE MACHINE LEARNING IN OPERATIONS
142	SIMPLE TWO STAGE FORECAST UPSCALING FOR LONG HORIZON INTERMITTENT DEMAND
142	INTRADAY FORECASTS HAVE BROAD APPLICATIONS IN THE INDUSTRY
142	WHEN COMBINED WITH LONG HORIZON REQUIREMENTS , FORECASTING AT A HIGH TEMPORAL RESOLUTION IS OFTEN A CHALLENGING PROBLEM DUE TO HIGH MEMORY REQUIREMENTS , TRAINING TIMES AND COST , ESPECIALLY WITH SOME DEEP LEARNING MODELS
142	THE PROBLEM BECOMES EVEN MORE CHALLENGING WHEN THE DATA IS INTERMITTENT SPARSE , AND WHEN VARIOUS FEATURE INTERACTIONS NEED TO BE CONSIDERED
142	WE PROPOSE A NEW METHOD THAT CAN CONVERT LOW TEMPORAL RESOLUTION , E G , WEEKLY , FORECASTS TO HIGHER RESOLUTION , E G , INTRADAY , FORECASTS AS A SECONDARY STEP ON TOP OF AN EXISTING FORECASTING MODEL OF CHOICE , PROVIDED THAT THE HIGHER RESOLUTION DATA IS AVAILABLE IN THE IN SAMPLE SET
142	ON REAL WORLD DATASETS , OUR METHOD ACHIEVES SIMILAR OR BETTER RESULTS WITH LESS COSTS COMPARED TO OTHER METHODS THAT DIRECTLY FORECASTS AT HIGH RESOLUTION
142	DATA MINING ARTIFICIAL INTELLIGENCE 
142	WE ARE USING A MULTI OBJECTIVE LOSS FUNCTION IN A DEEP LEARNING SETTING TO IMPROVE FORECASTING 
143	ENHANCING INTERPRETABILITY AND PREDICTION RELIABILITY IN REGRESSION TASKS THROUGH CONSTRAINED MIXTURE OF EXPERTS
143	IN THIS PAPER , WE INTRODUCE A NEW METHOD LEVERAGING MIXTURE OF EXPERTS , MOE , MODELS FOR RELIABILITY PREDICTION IN REGRESSION TASKS , WITH A FOCUS ON INTERPRETABILITY
143	TRADITIONAL MOE MODELS CAN CAPTURE COMPLEX RELATIONSHIPS BUT LACK IN INTERPRETABILITY
143	WE MITIGATE THIS BY CONSTRAINING MOES INTO SIMPLE , LOCALIZED LINEAR MODELS
143	THE MOE GATING NETWORK WEIGHTS , USUALLY EMPLOYED TO WEIGH THE CONTRIBUTION OF EACH EXPERT , ARE REPURPOSED IN OUR WORK
143	THEY ARE USED TO MEASURE PREDICTION CONFIDENCE , OFFERING AN INSIGHTFUL RELIABILITY EVALUATION
143	OUR MODEL WAS TRAINED ON BOTH SYNTHETIC AND REAL DATA AND CONSISTENTLY SHOWED ACCURATE RELIABILITY MEASURES IN DIFFERENT SCENARIOS , DEMONSTRAING THE ROBUSTNESS OF OUR APPROACH
143	DATA MINING ARTIFICIAL INTELLIGENCE 
144	INCORPORATING PRIOR FUNCTION BELIEF INTO NEURAL NETWORKS THROUGH DROPOUT AND NEGATIVE CORRELATION LEARNING 
144	THE UTILIZATION OF DROPOUT IN NEURAL NETWORKS , WHICH IS RECOGNIZED AS AN ENSEMBLE TECHNIQUE , HAS BEEN LINKED TO GAUSSIAN PROCESS , GP , REGRESSION
144	HOWEVER , THE CURRENT DROPOUT METHOD LACKS THE MODELING CAPABILITIES OF THE GP COVARIANCE STRUCTURE FOUND IN THE ORIGINAL GP MODEL
144	TO ADDRESS THIS LIMITATION , WE PROPOSE A NOVEL DROPOUT TRAINING METHOD THAT INCORPORATES NEGATIVE CORRELATION LEARNING
144	THROUGH EMPIRICAL EVALUATION , WE DEMONSTRATE THAT OUR APPROACH EFFECTIVELY CAPTURES THE INTENDED COVARIANCE STRUCTURE OF GP WITHIN THE NEURAL NETWORKS MODEL
144	WE BELIEVE THAT OUR RESEARCH HAS IMPORTANT IMPLICATIONS FOR THE MACHINE LEARNING FIELD , PARTICULARLY IN ENHANCING THE GENERALIZATION CAPABILITY OF NEURAL NETWORKS
144	DATA MINING ARTIFICIAL INTELLIGENCE 
145	DC ALGORITHM FOR ESTIMATION OF SPARSE GAUSSIAN GRAPHICAL MODELS
145	GRAPHICAL LASSO IS WIDELY USED AS A METHOD FOR ESTIMATION OF SPARSE GAUSSIAN GRAPHICAL MODELS , WHERE THE L NORM OF ELEMENTS IN THE PRECISION MATRIX IS USED AS A REGULARIZATION TERM FOR SPARSE ESTIMATION
145	HOWEVER , SINCE THE L NORM IS A CONVEX APPROXIMATION OF THE L PSEUDO NORM , I E , TOTAL NUMBER OF NONZERO ELEMENTS , , IT IS MORE DESIRABLE TO USE THE L PSEUDO NORM AS A REGULARIZATION TERM TO OBTAIN HIGH QUALITY SOLUTIONS
145	WE PROPOSE A METHOD THAT LEVERAGES THE DC ALGORITHM BASED ON THE L PSEUDO NORM TO ACHIEVE ESTIMATION OF SPARSE GAUSSIAN GRAPHICAL MODELS
145	TO DEMONSTRATE THE EFFECTIVENESS OF THE PROPOSED METHOD , WE CONDUCT COMPUTATIONAL EXPERIMENTS FOR COMPARING THE PERFORMANCE OF THE PROPOSED METHOD WITH THE GRAPHICAL LASSO FOR VARIOUS EXPERIMENTAL SETTINGS WITH DIFFERENT SAMPLE SIZES AND NUMBERS OF FEATURES
145	DATA MINING DATA , OR , AND SOCIAL JUSTICE OPTIMIZATION , OPT , 
146	CUSTOMIZED COUPON PROMOTIONS WITH MINIMUM PURCHASE REQUIREMENTS
146	MINIMUM PURCHASE REQUIREMENT , MPRS , COUPON PROMOTIONS ARE WIDELY USED BY RETAILERS YET , THE LITERATURE GIVES NO COMPREHENSIVE ANSWER ON HOW TO OPTIMIZE AND INDIVIDUALIZE MPR POLICIES
146	WE DEMONSTRATE HOW RETAILERS CAN USE BESPOKE MPRS TO INDUCE INCREMENTAL SPEND IN THE PROMOTION PERIOD AND HIGHLIGHT THE VALUE THAT COMES FROM CUSTOMIZING MPRS BASED ON CUSTOMERS PURCHASE HISTORIES
146	MOREOVER , WE ADD TO THE CONDITIONAL PROMOTION LITERATURE BY UNCOVERING THE EFFECTS OF VARYING LEVELS OF MPRS ON TRIP INCIDENCE , REDEMPTION LIKELIHOOD AND SPEND
146	USING DATA FROM A LARGE SCALE FIELD EXPERIMENT WITH AN OMNI CHANNEL RETAILER , WE EMPIRICALLY SHOW THE VALUE OF OUR APPROACH
146	DATA MINING EBUSINESS 
147	IMPROVING THE FORECAST ACCURACY OF PROTECTED DATA USING TIME SERIES FEATURES
147	EXISTING DATA PRIVACY METHODS DEGRADE FORECAST ACCURACY TO UNUSABLE LEVELS
147	TO OVERCOME THIS PROBLEM , WE INVESTIGATE THE SIMILARITY BETWEEN TIME SERIES FEATURES THAT ARE PREDICTIVE OF FORECAST ACCURACY
147	WE DEVELOP A MATRIX BASED PRIVACY METHOD CALLED K NEAREST TIME SERIES , K NTS , SWAPPING TAILORED TO MAINTAIN FORECAST ACCURACY
147	WE APPLY OUR PRIVACY METHOD TO A FORECASTING COMPETITION DATA SET WHERE THE IDENTITIES OF THE TIME SERIES ARE HIDDEN BUT AN ADVERSARY SEEKS TO IDENTIFY THEM
147	USING ONLY SIX TIME SERIES FEATURES , WE FIND THAT K NTS SWAPPING MAINTAINS FORECAST ACCURACY AND PRESERVES THE DISTRIBUTION OF TIME SERIES FEATURES MUCH BETTER THAN COMPETITOR METHODS AT SIMILAR PRIVACY LEVELS
147	THE K NTS PROTECTED TIME SERIES ARE ALSO MORE REPRESENTATIVE OF THE ORIGINAL DATA , POTENTIALLY LEADING TO INCREASED TRUST BETWEEN DATA OWNERS AND FORECASTERS
147	DATA MINING EMERGING TECHNOLOGIES AND APPLICATIONS QUALITY , STATISTICS AND RELIABILITY
147	THE PAPER PROVIDES A DATA PRIVACY SOLUTION FOR TIME SERIES DATA 
148	OPTIMAL DECISION TREE BASED FEATURE SELECTION FOR ENHANCED RENEWABLE CARBON CONTENT QUANTIFICATION IN CO PROCESSED FUELS
148	ADDRESSING THE CHALLENGE OF ACCURATELY QUANTIFYING RENEWABLE CARBON IN CO PROCESSED FUELS , WE PROPOSE A METHOD UTILIZING AN OPTIMAL DECISION TREE MODEL
148	EXISTING METHODS ARE DESIGNED TO PROCESS THE FEATURE SELECTION ON THE WHOLE DATASET , WITHOUT CONSIDERING DIFFERENT WORKING CONDITIONS
148	OUR APPROACH PARTITIONS THE DATASET INTO SUBSETS BASED ON THE DECISION TREE MODEL
148	EACH SUBSET INDEPENDENTLY ESTABLISHES A ROBUST LINEAR REGRESSION MODEL , USING FEATURES FROM THE CORRESPONDING DECISION TREE PREDICTION PATH
148	THIS METHOD HAS DEMONSTRATED ITS EFFECTIVENESS IN REAL WORLD OIL REFINING DATA , OFFERING A PRECISE RENEWABLE FUEL CONTENT ASSESSMENT TOOL
148	DATA MINING ENRE , ENERGY OPT , MACHINE LEARNING
148	OPTIMAL DECISION TREE BASED FEATURE SELECTION TO HANDLE THE COMPLEXITY OF LARGE DATASETS 
149	ADVANCING ORGAN TRANSPLANTATION DECISION MAKING , AN AI DRIVEN APPROACH FOR OPTIMAL DONOR RECIPIENT MATCHES
149	IN THIS PROJECT , WE UNDERTAKE THE ANALYSIS OF ORGAN TRANSPLANT DATA ACQUIRED FROM THE UNITED NETWORK FOR ORGAN SHARING , UNOS , 
149	OUR OBJECTIVE IS TO CREATE AN ADVANCED AI TOOL THAT ENHANCES THE DECISION MAKING PROCESS FOR ACHIEVING OPTIMAL DONOR RECIPIENT MATCHES
149	THIS ENDEAVOR ENCOMPASSES A COMPREHENSIVE APPROACH THAT LEVERAGES DATA ANALYSIS , VISUALIZATION , AND STATE OF THE ART MACHINE LEARNING MODELS
149	OUR PRIMARY FOCUS IS TO DEVELOP MODELS WITH EXCEPTIONAL ACCURACY IN IDENTIFYING SUITABLE MATCHES BETWEEN DONORS AND RECIPIENTS
149	FURTHERMORE , THE STUDY INVOLVES A METICULOUS ANALYSIS OF THE DATASET S FEATURES , WITH THE AIM OF IDENTIFYING A ROBUST SET OF VARIABLES THAT CONTRIBUTE TO SUCCESSFUL MATCHES
149	ULTIMATELY , WE STRIVE TO CREATE A USER FRIENDLY TOOL THAT EXPERTS IN THE FIELD CAN UTILIZE TO AUGMENT THEIR DECISION MAKING PROCESSES
149	DATA MINING HEALTH APPLICATIONS SOCIETY DECISION ANALYSIS SOCIETY
150	ENHANCING DIAGNOSIS AND PROGNOSIS OF DISEASES OF DESPAIR , AN ATTENTION NETWORK APPROACH
150	WE LEVERAGE STRUCTURED MEDICAL CLAIMS DATA OF PATIENTS SUFFERING FROM DISEASES OF DESPAIR AND ASSOCIATED SOCIAL DETERMINANTS OF HEALTH , SDOH , TO IMPROVE DISEASE DIAGNOSIS AND PROGNOSIS
150	UTILIZING ATTENTION NETWORK METHODS , WE AIM TO IDENTIFY AND PRIORITIZE CRITICAL FACTORS IN THE COMPLEX INTERPLAY BETWEEN PATIENT DEMOGRAPHICS , MEDICAL HISTORY , AND SDOH , ENABLING MORE ACCURATE AND PERSONALIZED TREATMENT RECOMMENDATIONS AND TIMELY INTERVENTIONS FOR AT RISK INDIVIDUALS
150	DATA MINING HEALTH APPLICATIONS SOCIETY 
150	THE ABSTRACT ALIGNS WITH HARNESSING DATA REVOLUTION THROUGH ADVANCED ANALYTICS IN HEALTHCARE
151	UNDERSTANDING THE RELATIONSHIP BETWEEN CUSTOMERS SEGMENTS AND THEIR SHORT TERM GOALS , A BAYESIAN APPROACH
151	ANALYZING CUSTOMERS GROCERY SHOPPING BASKETS HAS LONG BEEN A CRITICAL TOPIC RESEARCH TOPIC
151	THE ABUNDANCE OF DATA MAKES IT CHALLENGING TO EXTRACT USEFUL INSIGHTS , AND CUSTOMERS COMPLEX PURCHASING BEHAVIORS MAKE IT HARD TO IDENTIFY THEIR PREFERENCES
151	THIS RESEARCH DEVELOPS A HIERARCHICAL BAYESIAN MODEL TO SUMMARIZE CUSTOMERS DECISION MAKING PROCESSES , WHERE IT ASSUMES THAT A CUSTOMER TENDS TO WAIT FOR A PERIOD BEFORE SHOPPING AGAIN IN ANY SPECIFIC SEGMENT
151	WE USE CUSTOMERS PRODUCT PURCHASES TO DERIVE THE PROBABILITY DISTRIBUTION OF THEIR SHORT TERM SHOPPING GOALS , AND THEN FURTHER INFER THE LONG TERM SEGMENT DISTRIBUTION
151	WE USE REAL DATA ANALYSIS TO DEMONSTRATE THAT THE PROPOSED MODEL , CAN BE USED TO UNDERSTAND CUSTOMER HETEROGENEITY AND FACILITATE PERSONALIZED RECOMMENDATIONS , AND , PREDICT CUSTOMERS PURCHASES AND ASSIST WITH PRODUCT STOCK MANAGEMENT
151	DATA MINING INFORMATION SYSTEMS APPLIED PROBABILITY 
152	COVARIATE MATCHING FOR DATA PREPROCESSING IN CLASSIFICATION PROBLEMS
152	REAL WORLD DATASETS HAVE GROWN INCREASINGLY COMPLEX , RESULTING IN INEFFICIENCY IN CLASSIFICATION AND POTENTIAL RISKS IN NOT BEING ABLE TO FIND A BETTER LOCAL OPTIMUM , LET ALONE A GLOBAL ONE
152	ALTHOUGH THE COMMON SOLUTION IS TO CHOOSE MORE COMPLEX MODELS , SUCH AS BLACK BOX MODELS , IN ORDER TO BETTER HANDLE COMPLEX DATASETS , THIS IS IN DIRECT CONFLICT WITH THE NEED FOR INTERPRETABILITY IN A WIDE RANGE OF SOCIAL SCIENCE DISCIPLINES
152	TO ADDRESS THIS PROBLEM , THIS RESEARCH PROPOSES AN INTERPRETABLE PREPROCESSING SCHEME
152	OUR FOCUS IS ON DEVELOPING METRICS AS A WAY TO SIGNAL ITS DIFFICULTY LEVEL IN CLASSIFICATION FOR EACH SAMPLE UNIT AND LEVERAGE THIS INFORMATION IN CLASSIFICATION
152	DATA MINING INFORMATION SYSTEMS 
153	AN ENTROPY BASED DATA REDUCTION METHOD FOR DATA PREPROCESSING
153	WE PROPOSE AN ENTROPY BASED DATA REDUCTION , EBDR , ALGORITHM FOR DATA PRE PROCESSING BASED ON INFORMATION THEORY
153	THIS METHOD AIMS TO EXPLORE HIGH PURITY DATASET SUBSETS IN WHICH THE VALUES OF AN ATTRIBUTE ARE DIRECTLY LINKED TO SPECIFIC CLASS LABELS
153	EXPERIMENTAL RESULTS DEMONSTRATE THE EFFICIENCY OF EBDR ALGORITHM ON DIFFERENTLY SIZED DATASETS
153	MOREOVER , TO DEMONSTRATE EBDR S EFFECTIVENESS ON CLASSIFICATION PERFORMANCE , WE TEST IT ON A WIDE CROSS SECTION OF THE KDDCUP DATASET USING C DECISION TREE , C DT , 
153	THE EXPERIMENT RESULTS SHOW THAT THE SIZE OF C DT CAN BE GREATLY REDUCED WHILE THE ACCURACY IS MAINTAINED , AND THE TYPE II ERROR GETS LOWER
153	DATA MINING MACHINE LEARNING FOR OPTIMIZATION OPT , MACHINE LEARNING
154	APPLYING TEXT MINING AND CLUSTERING ANALYSIS TO IDENTIFY CLINICAL , SYSTEM LEVEL , AND SOCIODEMOGRAPHIC FACTORS AFFECTING MATERNAL HEALTH
154	MANY US WOMEN EXPERIENCE UNEXPECTED AND ADVERSE HEALTH OUTCOMES DURING LABOR AND DELIVERY
154	IN MOST STUDIES , SOCIODEMOGRAPHIC AND SOCIOECONOMIC FACTORS AS WELL AS PATIENT FACTORS AND CONDITIONS ARE MORE FOCUSED ON THAN SYSTEM LEVEL FACTORS SUCH AS POLICIES , CLINICAL GUIDELINES , INCENTIVES , AND CULTURE
154	THERE IS THEREFORE A SIGNIFICANT GAP IN RECOGNIZING HOW SYSTEM LEVEL FACTORS IMPACT MATERNAL HEALTH
154	IN ORDER TO FILL THIS GAP , WE USED TEXT MINING TECHNIQUES TO ANALYZE RELEVANT TERMINOLOGIES IN MORE THAN MATERNAL HEALTH PAPERS
154	THEN , BASED ON KNOWLEDGE ANALYSIS , WE FOUND SIGNIFICANT RELATIONSHIPS BETWEEN CLINICAL FACTORS , SYSTEM LEVEL FACTORS , AND SOCIODEMOGRAPHIC FACTORS
154	THEN BY USING CLUSTERING ANALYSIS , WE REFINED OUR PROCESS OF EXTRACTING DATA FROM HEALTH DATABASES TO CREATE RELEVANT COHORTS FOR FURTHER ANALYSIS
154	DATA MINING MSOM , HEALTHCARE MACHINE LEARNING IN OPERATIONS
155	THE DIVORCE OF WORD AND DEED A DATA MINING APPROACH TO IDENTIFY AND EVALUATE CUSTOMER REQUIREMENTS
155	WE ENHANCE EXISTING LITERATURE ON CUSTOMER REQUIREMENTS BY INTEGRATING PURCHASE RECORDS ALONGSIDE ONLINE REVIEWS
155	THIS ENABLES US TO SCRUTINIZE THE LINK BETWEEN CUSTOMERS EXPRESSED SATISFACTION , WORDS , AND THEIR ACTUAL PURCHASE BEHAVIOR , DEEDS , 
155	USING UNIQUE CELL PHONE MARKET DATA , WE ANALYZE PRODUCT FEATURES WITHIN A TWO DIMENSIONAL MODEL BASED ON THEIR SIGNIFICANCE TO CUSTOMER SATISFACTION AND PURCHASE DECISIONS
155	SURPRISINGLY , WE OBSERVE INCONSISTENCIES BETWEEN CUSTOMERS WORDS AND DEEDS
155	SOME SATISFACTION ORIENTED REQUIREMENTS LACK INFLUENCE ON PURCHASES , WHILE UNDERESTIMATED FACTORS HOLD SIGNIFICANCE DURING THE PURCHASE PROCESS
155	INCORPORATING THE DEED DIMENSION IS PIVOTAL FOR UNDERSTANDING CUSTOMER REQUIREMENTS , GUIDING PRODUCT DESIGN IMPROVEMENTS , AND DIFFERENTIATION FROM COMPETITORS
155	DATA MINING NEW PRODUCT DEVELOPMENT 
156	DATA ADAPTIVE THRESHOLD SELECTION FOR QUANTILE FEATURE SCREENING WITH FDR ERROR RATE CONTROL
156	SELECTING AN APPROPRIATE THRESHOLD IS OF UTMOST IMPORTANCE WHEN CONDUCTING FEATURE SCREENING IN ULTRAHIGH DIMENSIONAL DATA
156	IDENTIFYING RELEVANT PREDICTORS IN SUCH DATASETS CAN BE HIGHLY CHALLENGING WITH HETEROGENEITY AND POTENTIAL OLS ASSUMPTION VIOLATIONS
156	WE PROPOSE THE QUANTILE DATA ADAPTIVE THRESHOLD SELECTION , QDATS , , A DATA DRIVEN AND SYSTEMATIC APPROACH FOR THRESHOLD SELECTION WITH ERROR RATE CONTROL
156	WE UTILIZE A SAMPLE SPLITTING APPROACH AND QUANTILE CORRELATION TO DIFFERENTIATE BETWEEN RELEVANT AND IRRELEVANT PREDICTORS BASED ON MARGINALLY SYMMETRIC STATISTICS
156	THE PERFORMANCE OF QDATS IS DEMONSTRATED ON ULTRAHIGH DIMENSIONAL GENETIC DATA WITH BLOOD PRESSURE MEASUREMENTS AND SIMULATION STUDIES , ACHIEVING RELIABLE TRUE POSITIVE RATE AND FALSE DISCOVERY RATE CONTROL WHILE SATISFYING THE SURE SCREENING PROPERTY UNDER SUITABLE CONDITIONS
156	DATA MINING OPT , MACHINE LEARNING HEALTH APPLICATIONS SOCIETY
157	EXPLORING A RELATIONSHIP BETWEEN TUMOR CHARACTERISTICS SURVIVAL TIME IN BREAST CANCER PATIENTS , A MULTIVARIATE ANALYSIS MACHINE LEARNING APPROACH
157	CANCER IS A COMPLEX GROUP OF DISEASES CHARACTERIZED BY THE UNCONTROLLED GROWTH AND SPREAD OF ABNORMAL CELLS
157	THE ACCURATE DIAGNOSIS OF CANCER IS AN ACTIVE AND CHALLENGING TASK IN THE MEDICAL DOMAIN DUE TO THE VAST AMOUNT OF MEDICAL DATA AVAILABLE IN DIAGNOSTIC CENTERS , HOSPITALS , RESEARCH CENTERS , AND WEBSITES
157	DISEASE DIAGNOSIS TYPICALLY RELIES ON THE KNOWLEDGE AND SKILLS OF MEDICAL PROFESSIONALS , WHICH CAN OCCASIONALLY RESULT IN ERRORS , UNINTENDED BIASES , AND LONGER DIAGNOSTIC TIMES
157	IN THIS RESEARCH , WE HAVE IMPLEMENTED A COMBINATION OF SURVIVAL ANALYSIS , MULTIVARIATE DATA ANALYSIS , AND MACHINE LEARNING ALGORITHMS TO INVESTIGATE THE RELATIONSHIP BETWEEN TUMOR CHARACTERISTICS AND SURVIVAL TIME IN BREAST CANCER PATIENTS
157	DATA MINING OPT , MACHINE LEARNING HEALTH APPLICATIONS SOCIETY
158	A NEW CLASSIFICATION METHOD BASED ON TUNING OF HYPER PARAMETER AND DECISION THRESHOLD FOR IMBALANCE DATA
158	IN MANY REAL WORLD TWO CLASS CLASSIFICATION PROBLEMS , THE DATA ARE IMBALANCED
158	THIS SOMETIMES LEADS TO NAÏVE CLASSIFIERS OF PREDICTING ALL THE SAMPLES AS THE MAJORITY CLASS AND MAY RESULT INTO MISLEADING ACCURACY , POOR PRECISION , AND CONFUSING CONCLUSIONS
158	ONE OF THE KEY REASONS FOR THE POOR PERFORMANCE IS RELATED TO THE INAPPROPRIATE DECISION THRESHOLD
158	CONVENTIONALLY , THE DECISION THRESHOLD OF A TWO CLASS CLASSIFICATION PROBLEM IS SET TO , WHICH MAY NOT BE THE BEST CHOICE FOR IMBALANCE DATA
158	IN THIS PAPER , WE PROPOSE A SIMULTANEOUS TUNING METHOD THAT TUNES THE MODEL HYPER PARAMETER ALONG WITH THE DECISION THRESHOLD
158	WE SELECT COHEN S KAPPA AS THE TUNING METRIC AND RE INTERPRET COHEN S KAPPA AS MEASURING THE IMPROVEMENT OVER A BASELINE CLASSIFIER CALLED P NAÏVE CLASSIFIER
158	FINALLY , WE EXTEND THE IDEA OF KAPPA TO OTHER STANDARD CLASSIFICATION METRICS SUCH AS F SCORE
158	DATA MINING OPT , MACHINE LEARNING QUALITY , STATISTICS AND RELIABILITY
158	THE PROPOSED METHOD AIMS TO IMPROVE IMBALANCE DATA CLASSIFICATION AND DATA DRIVEN DECISION MAKING 
159	PARTITIONING OBSERVATION NOISE FROM SYSTEM DYNAMICS USING DEEP LEARNING 
159	WHILE MOST OF THE TIME SERIES MODELS AIM TO LEARN THE SYSTEM BEHAVIORS FROM THE DATA , THE SENSOR NOISE OFTEN MAKES IT CHALLENGING TO ACCURATELY IDENTIFY THE SYSTEM DYNAMICS
159	HERE , WE PRESENT A DEEP LEARNING MODEL THAT AIMS TO PARTITION THE NOISY OBSERVATION INTO THE INHERENT RANDOM DYNAMICS OF THE SYSTEM AND THE OBSERVATION NOISE , OF WHICH MAGNITUDE IS INVARIANT IN TIME
159	THE PROPOSED MODEL CONSISTS OF TWO RECURRENT NEURAL NETWORKS , RNN , , PRIOR RNN AND DYN RNN
159	THE STANDARD RNN WITH A PARAMETRIC DISTRIBUTION , PRIOR RNN , IS USED TO PROVIDE A PRIOR DISTRIBUTION OF THE SYSTEM STATE , AND DYN RNN IS USED TO LEARN THE SYSTEM DYNAMICS BY A MIXTURE OF GAUSSIAN DISTRIBUTIONS BY MINIMIZING THE MISMATCH BETWEEN THE MOMENTS OF THE DATA GENERATING DISTRIBUTION AND THE APPROXIMATE DISTRIBUTION
159	THE PROPOSED METHOD IS TESTED AGAINST NOISY OBSERVATION OF NONLINEAR DYNAMICAL SYSTEMS
159	DATA MINING QUALITY , STATISTICS AND RELIABILITY ARTIFICIAL INTELLIGENCE
160	A TWO STAGE SPATIOTEMPORAL PREDICTIVE FRAMEWORK TO FORECAST MOBILITY PATTERNS AT CRITICAL FACILITIES
160	ACCURATE DEMAND FORECASTS FOR CRITICAL FACILITIES ARE FUNDAMENTAL TO PROVIDING ESSENTIAL SERVICES TO PEOPLE , YET HAVE RECEIVED LITTLE ATTENTION IN THE LITERATURE DUE TO DATA UNAVAILABILITY AND LACK OF SOPHISTICATED PREDICTIVE TOOLS
160	THUS , WE PROVIDE A NEW PERSPECTIVE FOR DEMAND FORECASTS AT CRITICAL FACILITIES LEVERAGING HUMAN MOBILITY PATTERNS , AND PROPOSE A NOVEL TWO STAGE DATA DRIVEN FRAMEWORK MOBILITY PREDICTION
160	THE FIRST STAGE IS TO DECOMPOSE THE MOBILITY DATA INTO SPATIAL AND TEMPORAL PATTERNS , WHEREAS THE SECOND STAGE IS TO MODEL TEMPORAL DYNAMICS USING MULTIVARIATE TIME SERIES ANALYSIS
160	THE RESULTS SHOW THAT OUR MODEL DEMONSTRATES THE BEST PREDICTIVE PERFORMANCE OVER MULTIPLE BENCHMARK MODELS FOR VARYING FORECAST HORIZONS
160	THE STABILITY AND RELIABILITY OF THE FRAMEWORK ARE ALSO INVESTIGATED THROUGH SENSITIVITY ANALYSIS AND ROBUSTNESS CHECKS
160	DATA MINING SOCIAL OPERATIONS MANAGEMENT TSL , URBAN TRANSPORTATION PLANNING AND MODELING
161	THE CONSEQUENCES OF THE ECONOMIC CRISIS ON THE NUMBER OF DEATHS RESULTING FROM ACCIDENTS
161	THIS PAPER DELVES INTO A COMPREHENSIVE EXAMINATION OF THE IMPACT OF THE ANNUAL INFLATION RATE ON TRAFFIC FATALITIES
161	BY ANALYZING A RICH DATASET ENCOMPASSING THE YEARS TO IN THE UNITED STATES , THE STUDY EXPLORES THE INTRICATE RELATIONSHIP BETWEEN THE TOTAL NUMBER OF TRAFFIC RELATED DEATHS AND THE AVERAGE ANNUAL INFLATION RATE OVER THIS PERIOD
161	THE AIM IS TO UNCOVER PATTERNS AND TRENDS THAT COULD SHED LIGHT ON THE POTENTIAL FORECASTING OF YEARLY FATALITIES
161	DATA MINING TSL , URBAN TRANSPORTATION PLANNING AND MODELING TRANSPORTATION SCIENCE AND LOGISTICS , TSL , 
162	LEVENT BULUT
162	IN THIS STUDY , WE INCORPORATE THE GENERALIZED ADDITIVE MODEL , GAM , INTO THE TIME SERIES MODELS TO FORECAST AND NOWCAST THE MONTHLY STATE LEVEL UNEMPLOYMENT RATE STATISTICS IN THE U S FROM JANUARY TO APRIL OUR FOCUS IS ON UTILIZING GOOGLE TRENDS DATA , WHICH PROVIDES REAL TIME , HIGH FREQUENCY , AND STATE SPECIFIC INFORMATION
162	AS JOB SEARCH IS A REQUIREMENT FOR ELIGIBILITY TO RECEIVE UNEMPLOYMENT INSURANCE BENEFITS IN OUT OF THE STATES , WE EXPLORE WHETHER GOOGLE TRENDS DATA CAN ENHANCE THE ACCURACY OF STATE LEVEL UNEMPLOYMENT RATE FORECASTS COMPARED TO DATA ON INITIAL CLAIMS AND OTHER FACTORS
162	OUR FINDINGS INDICATE A SIGNIFICANT CORRELATION BETWEEN SEARCHES FOR UNEMPLOYMENT RELATED PHRASES AND STATE LEVEL UNEMPLOYMENT RATES
162	DATA MINING 
163	A NOVEL DISCRETIZATION METHOD BASED ON CACC AND ANT COLONY OPTIMIZATION
163	IN THIS PAPER , WE PRESENT A NOVEL MULTIVARIATE DISCRETIZATION APPROACH THAT CONSIDERS FEATURE INTERACTIONS
163	OUR METHOD BEGINS BY GENERATING CANDIDATE SETS OF CUT POINTS FOR EACH FEATURE USING CACC , A POPULAR DISCRETIZATION METHOD
163	WE THEN EMPLOY ANT COLONY OPTIMIZATION TO SEARCH FOR THE OPTIMAL DISCRETIZATION SCHEME BY COMBINING THESE CANDIDATES
163	THE MAIN ADVANTAGE OF OUR METHOD IS ITS ABILITY TO ADDRESS THE LIMITATIONS OF CACC , EXCESSIVE SPLITTING OF CONTINUOUS FEATURES AND PREMATURE TERMINATION OF THE DISCRETIZATION PROCESS , BOTH OF WHICH ARE UNDESIRABLE FOR CONSTRUCTING EFFECTIVE DISCRETIZATION SCHEMES
163	TO EVALUATE OUR APPROACH , WE COMPARED IT WITH THREE OTHER DISCRETIZATION METHODS USING DIFFERENT DATASETS
163	THE RESULTS DEMONSTRATE THAT OUR PROPOSED METHOD GENERATES MORE SUITABLE DISCRETIZATION SCHEMES , LEADING TO IMPROVED CLASSIFICATION PERFORMANCE
163	DATA MINING 
164	NONLINEAR BINARY CLASSIFICATION WITH IMBALANCED DATASET USING PERFORMANCE BASED ACTIVE LEARNING
164	THIS RESEARCH ADDRESSES THE ISSUE OF SKEWED DISTRIBUTION IN REAL WORLD DATA , WHICH CAN NEGATIVELY IMPACT CLASSIFICATION MODEL PERFORMANCE
164	THE STUDY PROPOSES A PERFORMANCE BASED ACTIVE LEARNING , PBAL , SCHEME USING NONPARAMETRIC LOGISTIC REGRESSION TO HANDLE THE IMBALANCE PROBLEM AND NONLINEAR DECISION BOUNDARIES
164	PBAL SELECTS INFORMATIVE SAMPLES SEQUENTIALLY BY EVALUATING A PERFORMANCE METRIC ON A POOL SET
164	THE NONPARAMETRIC LOGISTIC REGRESSION MODEL WITH SMOOTHING SPLINES ENABLES FLEXIBLE CLASSIFICATION BOUNDARIES
164	EXPERIMENTAL RESULTS DEMONSTRATE THAT PBAL OUTPERFORMS TRADITIONAL ACTIVE LEARNING APPROACHES AND OTHER RESAMPLING TECHNIQUES FOR IMBALANCED CLASSIFICATION PROBLEMS , EVEN WITH SMALLER SAMPLE SIZES
164	PBAL EFFECTIVELY MITIGATES BIAS , IMPROVING MODEL PERFORMANCE WITH LIMITED INITIAL TRAINING DATA
164	DATA MINING 
165	PREDICTION OF ADVERSE DRUG REACTIONS USINGDEMOGRAPHIC AND NON CLINICAL DRUG CHARACTERISTICS IN FAERS DATA DATA MINING 
166	FAIRPILOT , AN EXPLORATIVE SYSTEM FOR HYPERPARAMETER TUNING THROUGH THE LENS OF FAIRNESS
166	DESPITE THE POTENTIAL BENEFITS OF MACHINE LEARNING , ML , IN HIGH RISK DECISION MAKING DOMAINS , THE DEPLOYMENT OF ML IS NOT ACCESSIBLE TO PRACTITIONERS , AND THERE IS A RISK OF DISCRIMINATION
166	TO ESTABLISH TRUST AND ACCEPTANCE OF ML IN SUCH DOMAINS , DEMOCRATIZING ML TOOLS AND FAIRNESS CONSIDERATION ARE CRUCIAL
166	IN THIS PAPER , WE INTRODUCE FAIRPILOT , AN INTERACTIVE SYSTEM DESIGNED TO PROMOTE THE RESPONSIBLE DEVELOPMENT OF ML MODELS BY EXPLORING A COMBINATION OF VARIOUS MODELS , DIFFERENT HYPERPARAMETERS , AND A WIDE RANGE OF FAIRNESS DEFINITIONS
166	WE EMPHASIZE THE CHALLENGE OF SELECTING THE BEST ML MODEL AND DEMONSTRATE HOW FAIRPILOT ALLOWS USERS TO SELECT A SET OF EVALUATION CRITERIA AND THEN DISPLAYS THE PARETO FRONTIER OF MODELS AND HYPERPARAMETERS
166	FAIRPILOT OFFERS A UNIQUE OPPORTUNITY FOR USERS TO RESPONSIBLY CHOOSE THEIR MODEL
166	DATA , OR , AND SOCIAL JUSTICE DATA MINING ARTIFICIAL INTELLIGENCE
167	UNLEASHING THE POTENTIAL OF PREDICTIVE ANALYTICS WITH FAIR MARS , A STATISTICAL MODEL THAT PRIORITIZES EQUITY AND TRANSPARENCY
167	THIS PROJECT AIMS TO DEVELOP A FAIR MULTIVARIATE ADAPTIVE REGRESSION SPLINES , MARS , MODEL THAT REDUCES BIAS TOWARDS SENSITIVE ATTRIBUTES LIKE RACE OR GENDER ACROSS ACHIEVING MORE EQUITABLE OUTCOMES
167	MARS IS A NON PARAMETRIC REGRESSION MODEL WITH A BUILT IN FEATURE SELECTION STEP
167	OUR FAIR MARS MODEL PRIORITIZES FAIRNESS AS WELL AS ACCURACY VIA PRE PROCESSING , DECORRELATING SENSITIVE AND NON SENSITIVE ATTRIBUTES , AND IN PROCESSING , INCORPORATING FAIRNESS CONSTRAINTS DURING KNOT OPTIMIZATION , 
167	ADDING THE FAIRNESS COMPONENT TO THE TRAINING PROCESS NOT ONLY PRODUCES LESS BIASED PREDICTIONS BUT ALSO GENERATES A FAIR SET OF DECISION RULES BASED ON THE SPLITTING CRITERIA FOR THE SELECTED VARIABLES
167	BY DEVELOPING AND SHARING THIS MODEL , WE OFFER A MORE INTERPRETABLE AND ACCESSIBLE PREDICTION MODEL , ENHANCING THE UTILITY OF PREDICTIVE ANALYTICS IN PRACTICE
167	DATA , OR , AND SOCIAL JUSTICE DATA MINING DIVERSITY , EQUITY , AND INCLUSION
168	A STUDY ON DISTRIBUTIONALLY ROBUST OPTIMIZATION WITH CHANGEABLE AMBIGUITY SETS
168	WE STUDY DRO , DISTRIBUTIONALLY ROBUST OPTIMIZATION , MODELS WITH COMPLEX AMBIGUITY SETS THAT CAN BE MODIFIED , INCLUDING THOSE DEFINED BY MOMENT INEQUITIES AND THE WASSERSTEIN METRIC
168	DATA , OR , AND SOCIAL JUSTICE DECISION ANALYSIS SOCIETY DATA DRIVEN INNOVATIONS IN OR EDUCATION
169	IMPLICATIONS OF IBUYER INTERMEDIATION ON PRICE DISCRIMINATION IN THE HOUSING MARKET
169	WE STUDY WHETHER IBUYING , A TECHNOLOGY DRIVEN BUSINESS MODEL , ATTENUATE OR EXACERBATE THE EXISTING PRICE DISCRIMINATION IN THE HOUSING MARKET
169	USING HOUSING TRANSACTION AND MORTGAGE DATA OF TOP IBUYING MARKETS , WE QUANTIFY THE IMPACT OF IBUYER ACTIVITIES ON THE PRICE DISCRIMINATION USING A REPEAT SALES FRAMEWORK
169	WE DOCUMENT THAT BLACK AND HISPANIC BUYERS PAY PRICE PREMIA COMPARED TO THEIR WHITE COUNTERPARTS FOR COMPARABLE HOUSING IN THE STUDIED METRO AREAS
169	FURTHER WE EXAMINE IBUYER S ROLE IN ATTENUATING THE PRICE DISCRIMINATION IN THE HOUSING MARKET AND INVESTIGATE THE CORRESPONDING MECHANISM
169	DATA , OR , AND SOCIAL JUSTICE EMERGING TECHNOLOGIES AND APPLICATIONS INFORMATION SYSTEMS
169	WE CONTRIBUTE TO THE LITERATURE ON THE SOCIETAL IMPACT OF DATA REVOLUTION ENABLED BUSINESS MODELS 
170	OL LI DATA DRIVEN OL LI DATA DRIVEN RESOURCE ALLOCATION FOR THE OPIOID CRISIS IN CHICAGO LI OL LI OL 
170	THE OPIOID CRISIS HAS EMERGED AS A SERIOUS PROBLEM ACROSS THE USA , WITH FATALITIES FROM OPIOID OVERDOSES SOARING RAPIDLY OVER TIME
170	THIS NECESSITATES A CAREFUL EVALUATION OF ALLOCATION STRATEGIES FOR DIFFERENT RESOURCES , E G , NARCAN , TO HELP INDIVIDUALS WITH OPIOID OVERDOSE AND MISUSE
170	IN THIS TALK , WE DISCUSS A DATA DRIVEN APPROACH TO ACCURATELY FORECAST THE DEMANDS FOR SUCH RESOURCES AND DESIGN AN INTEGER PROGRAMMING BASED ALLOCATION SCHEME TO ENSURE FAIRNESS OF BENEFITS ACROSS DIFFERENT REGIONS
170	WE ILLUSTRATE THE EFFICACY OF OUR APPROACH IN THE CONTEXT OF CHICAGO S NEIGHBORHOOD COMMUNITIES
170	DATA , OR , AND SOCIAL JUSTICE OPT , MACHINE LEARNING OPTIMIZATION , OPT , 
171	A DATA DRIVEN ALGORITHM TO RELLOCATE IMMIGRANTS , A CHALLENGUE WITH DATA CHANGES AND CONCEPT DRIFT
171	A DATA DRIVEN APPROACH IS USED TO SUGGEST LOCATIONS FOR IMMIGRANTS IN A NEW COUNTRY
171	WE EVALUATE DIFFERENT ALTERNATIVES TO COPE WITH DATA CHANGES AND MODEL PERFORMANCE VARIATIONS
171	THE ALTERNATIVES INCLUDE DATA BALANCING , TRAINING MODELS WITH THE LATEST DATA , AND MIXED STRATEGIES
171	THE ALGORITHM AND THE STRATEGIES ARE EVALUATED ON A TESTBED WITH INFORMATION FROM COLOMBIA AND VENEZUELAN IMMIGRANTS
171	DATA , OR , AND SOCIAL JUSTICE WE USE DATA DRIVEN ALGORITHMS TO ASSIST IMMIGRANTS LOCATIONS IN A NEW COUNTRY 
172	PERSONALIZED LEARNING IN PARTIALLY OBSERVABLE ENVIRONMENTS
172	PERSONALIZED LEARNING , PL , AIMS TO IMPROVE LEARNING OUTCOMES BY ADAPTING TO LEARNERS UNIQUE NEEDS
172	EXISTING WORK ON PL TYPICALLY FACES A TRADE OFF BETWEEN ADAPTING TO PARTIALLY OBSERVABLE ENVIRONMENTS AND MAINTAINING TRACTABILITY
172	IN THIS PAPER , WE PROPOSE A DATA DRIVEN APPROACH TO ESTIMATE LEARNERS SKILL LEVELS BY UTILIZING MULTIPLE INFORMATION SOURCES SUCH AS INSTANT SKILLS ASSESSMENT AND INSTRUCTORS FORWARD LOOKING VIEWS
172	WE FORMULATE THE PROBLEM AS A CONSTRAINED MARKOV DECISION PROCESS AND THEN PROPOSE A MODEL FREE DEEP REINFORCEMENT LEARNING ALGORITHM TO APPROXIMATE THE SOLUTION
172	WE SHOW THAT OUR APPROACH CAN HANDLE SUCH ENVIRONMENTS BY USING REAL WORLD DATA
172	DATA DRIVEN INNOVATIONS IN OR EDUCATION ARTIFICIAL INTELLIGENCE APPLIED PROBABILITY 
172	PAPER TALKS ABOUT HOW TO USE DATA PROPERLY TO IMPROVE THE LEARNING EXPERIENCE 
173	USING GENERATIVE AI TO BUILD REALISTIC CLASSROOM CASE STUDIES
173	AS EDUCATORS , WE STRIVE TO CREATE LEARNING OPPORTUNITIES THAT MIMIC CHALLENGES FACED IN INDUSTRY
173	WE WANT OUR STUDENTS TO BE PREPARED
173	HOWEVER , STUDENTS SOMETIMES FEEL THAT ACADEMIA AND INDUSTRY ARE OUT OF ALIGNMENT
173	WHILE BEING TAUGHT , THEY MIGHT SAY , WHEN WILL I EVER USE THIS IN MY CAREER
173	AS AN EXAMPLE , WHILE PERFORMING DATA ANALYSIS ON AN ASSIGNMENT , STUDENTS MAY FEEL THE DATA IS CLEANER AND MORE COMPLETE THAN DATA THEY WOULD ENCOUNTER IN THE REAL WORLD , WHICH COULD BE MESSY AND POORLY DOCUMENTED
173	THESE EXPERIENCES CAN BE FRUSTRATING FOR STUDENTS
173	TO ADDRESS THESE CONCERNS , EDUCATORS CAN USE GENERATIVE AI TO CREATE MORE REALISTIC ASSIGNMENTS
173	FOR INSTANCE , GENERATIVE AI CAN BE USED TO CREATE SYNTHETIC DATASETS , WHICH ARE MODELED AFTER REAL DATASETS , OR TO CREATE VIDEO AVATARS THAT REPRESENT DIFFERENT BUSINESS STAKEHOLDERS WHO CAN PROVIDE BUSINESS CONTEXT FOR STUDENTS
173	DATA DRIVEN INNOVATIONS IN OR EDUCATION ARTIFICIAL INTELLIGENCE 
173	DEALS WITH USING AI TO IMPROVE THE CLASSROOM
174	A CERTIFICATE FOCUSED MAJOR IN BUSINESS ANALYTICS
174	AS ORGANIZATIONS ATTEMPT TO HARNESS THE POWER OF DATA , THERE WE HAVE SEEN A SIGNIFICANT INCREASE IN USE OF ANALYTICS IN BUSINESS AND THE PROLIFERATION OF CURRICULA WHICH FEATURE ANALYTICS
174	THUS , IT IS IMPORTANT FOR EDUCATORS AND ACADEMIC ADMINISTRATORS TO EVALUATE AND IMPROVE THEIR ACADEMIC OFFERINGS IN THIS AREA
174	WHETHER FOR COMPETITIVE REASONS OR TO EXHIBIT THE CONTINUOUS IMPROVEMENT REQUIRED BY ACCREDITATION AGENCIES , IT IS ESSENTIAL THAT THE ACADEMIC PROGRAMS THAT WE CREATE ARE BOTH MEANINGFUL AND DISTINCTIVE
174	THIS PAPER OFFERS AN EXAMPLE OF AN ACADEMIC MAJOR IN BUSINESS ANALYTICS THAT OFFERS ADDED VALUE TO THE CURRICULUM AND COURSE OFFERINGS BY FOCUSING ON THE ATTAINMENT OF CERTIFICATES BY THE STUDENTS PARTICIPATING IN THE MAJOR I I 
174	DATA DRIVEN INNOVATIONS IN OR EDUCATION INFORMS COMMITTEE ON TEACHING AND LEARNING AND EDUCATION OUTREACH SOCIAL MEDIA ANALYTICS
174	ANALYTICS ALLOWS US TO USE DATA TO SUPPORT DECISION MAKING AND PROVIDE MEANING IN ORGANIZATIONS
175	A DATA DRIVEN STRATEGY TO PREDICT INCIDENT HOTSPOTS
175	THIS STUDY PREDICTS INCIDENT HOTSPOT LOCATIONS USING DEEP LEARNING TECHNIQUES INCLUDING NEURAL NETWORKS AND LONG SHORT TERM MEMORY , LSTM , NETWORK METHODS
175	THE PROPOSED STUDY VALIDATES THE MODELS USING REAL WORLD INCIDENT DATA IN NORTH CAROLINA AND INCORPORATING ADDITIONAL VARIABLES SUCH AS WEATHER INFORMATION , HOLIDAYS , UNUSUAL EVENTS , AND ANNUAL AVERAGE DAILY TRAFFIC , AADT , INDEX THAT AFFECT THE LIKELIHOOD OF A CRASH
175	THE ERROR ESTIMATES ARE COMPARED AGAINST THOSE OF OTHER MACHINE LEARNING TECHNIQUES
175	NUMERICAL EXPERIMENTS INDICATE THAT THE PROPOSED APPROACH PROVIDES BETTER PREDICTIONS WITH HIGHER ACCURACY COMPARED TO BENCHMARKS
175	DATA DRIVEN INNOVATIONS IN OR EDUCATION MACHINE LEARNING IN OPERATIONS DATA , OR , AND SOCIAL JUSTICE
176	EXPANDING STUDENTS SOCIAL NETWORKS VIA OPTIMIZED SEATING ASSIGNMENTS
176	A STRONG AND DIVERSE PEER NETWORK IS IMPORTANT FOR STUDENTS EDUCATIONAL , PERSONAL , AND PROFESSIONAL SUCCESS
176	WE PRESENT A NOVEL METHOD FOR ASSIGNING STUDENTS TO SEATS USING SOCIAL NETWORK ANALYSIS AND OPTIMIZATION
176	WE AIM AT AUGMENTING STUDENTS TIES THROUGH OPTIMIZED SEATING , AND SUGGEST A PROCESSES FOR SURVEYING EXISTING CONNECTIONS AND REPRESENTING ARBITRARY CLASSROOM LAYOUTS
176	WE SHOW THAT THE UNDERLYING DIFFICULT COMBINATORIAL PROBLEM , A VARIANT OF THE ASSIGNMENT PROBLEM , CAN BE FORMULATED AS AN INTEGER PROGRAM AND SOLVED TO OPTIMALITY USING MATHEMATICAL OPTIMIZATION
176	WE ALSO ACCOUNT FOR CLASSROOM BALANCING AND VARIOUS STUDENT NEEDS
176	IN A CASE STUDY INCLUDING MORE THAN STUDENTS , WE ANALYZE POTENTIAL AND IMPACT
176	COMPARED TO SELF SELECTION , THE NEW TIES CAN CLEARLY BE INCREASED
176	STUDENT AND INSTRUCTOR FEEDBACK SUPPORT THE USEFULNESS OF OUR APPROACH
176	DATA DRIVEN INNOVATIONS IN OR EDUCATION OPT , INTEGER AND DISCRETE OPTIMIZATION DIVERSITY , EQUITY , AND INCLUSION
177	ENABLING AND MAXIMIZING DATA POTENTIAL FOR MAPPING RESEARCH IMPACT
177	THIS PAPER AIMS TO SHARE INSTITUTIONAL EXPERIENCE OF AGBIORESEARCH RESEARCH ARM OF MICHIGAN STATE UNIVERSITY S COLLEGE OF AGRICULTURE AND NATURAL RESOURCES , IN BUILDING AND MAINTAINING INTEGRATED AND INCLUSIVE RESEARCH EVALUATION AND DATA ANALYTICS SYSTEMS THAT SUPPORT A THRIVING ACADEMIC RESEARCH ENTERPRISE
177	IT WILL SHOWCASE HOW MODERN INFORMATION MANAGEMENT SYSTEMS AND ASSOCIATED DATA AND DATA ANALYTICS ARE USED TO TRACK AND EVALUATE RESEARCH PERFORMANCE , PRODUCTIVITY , QUALITY , AND RETURN ON INVESTMENTS EXPECTATIONS FOR ACADEMIC RESEARCH
177	THIRDLY , IT WILL ALSO SHOWCASE A FRAMEWORK ON HOW THESE SYSTEMS SUPPORT FACULTY RECRUITMENT AND RETENTION , PROFESSIONAL DEVELOPMENT , AND DIVERSITY , EQUITY , AND INCLUSION
177	FINALLY , THIS PAPER WILL SHOWCASE SOME OF THE REQUIREMENTS AND PRINCIPLES THAT UNDERPIN A THRIVING DATA AND ANALYTICS CULTURE AT MSU AGBIORESEARCH
177	DATA DRIVEN INNOVATIONS IN OR EDUCATION PRACTICE DIVERSITY , EQUITY , AND INCLUSION
177	THIS PAPER RELATES TO USE OF MODERN DATA AND DATA ANALYTICS SYSTEMS FOR THE ACADEMIC ENTERPRISE 
178	CASE , USING TEXT ANALYSIS TO INVESTIGATE FRAUD
178	WE DESCRIBE A CASE STUDY THAT INTRODUCES BUSINESS STUDENTS TO TEXT ANALYSIS IN THE CONTEXT OF FRAUD
178	AFTER REVIEWING THE FRAUD TRIANGLE , STUDENTS USE PYTHON TO READ , ANALYZE , AND SIFT THROUGH A SAMPLE OF THE COMPANY S EMAILS ATTEMPTING TO FIND THE CULPRITS
178	THE CASE HAS BEEN USED IN BOTH MBA AND MACC CLASSES
178	WE COLLECTED STUDENT SURVEY DATA OVER MULTIPLE OFFERINGS AND PROVIDE SOME ANALYSIS AND INSIGHTS INTO THE STUDENTS PERCEPTIONS OF THE CASE AND ITS ABILITY TO HELP THEM UNDERSTAND TEXT ANALYSIS
178	DATA DRIVEN INNOVATIONS IN OR EDUCATION 
179	PARTITION BASED STABILITY OF COALITIONAL GAMES
179	WE ARE CONCERNED WITH THE STABILITY OF A COALITIONAL GAME
179	FIRST , THE CONCEPT OF CORE CAN BE WEAKENED SO THAT THE BLOCKING OF CHANGES IS LIMITED TO ONLY THOSE WITH MULTILATERAL BACKINGS
179	THIS PRINCIPLE OF CONSENSUAL BLOCKING ALONG WITH OTHERS CAN BE APPLIED TO PARTITION ALLOCATION PAIRS
179	EACH SUCH PAIR IS MADE UP OF A PARTITION OF THE GRAND COALITION AND A CORRESPONDING ALLOCATION VECTOR WHOSE COMPONENTS ARE INDIVIDUALLY RATIONAL AND EFFICIENT FOR THE VARIOUS CONSTITUENT COALITIONS OF THE GIVEN PARTITION
179	THE RESULTING STABILITY CONCEPTS ARE COMPATIBLE WITH CORE RELATED CONCEPTS
179	PROBABLY MORE IMPORTANTLY , TWO OF THEM ARE UNIVERSAL MEANING THAT ANY GAME , NO MATTER HOW POOR IT IS , HAS ITS FAIR SHARE OF STABLE SOLUTIONS
179	THERE IS ALSO A STEEPEST ASCENT METHOD TO GUIDE THE CONVERGENCE PROCESS TO A STABLE PARTITION ALLOCATION PAIR FROM ANY STARTING PARTITION
179	DECISION ANALYSIS SOCIETY APPLIED PROBABILITY AUCTIONS AND MARKET DESIGN
180	A DYNAMIC CHOICE MODEL BASED EXPLICIT STATED PREFERENCE ANALYSIS STUDY FOR TRADABLE GOODS
180	CHOICE MODELS ARE WIDELY USED TO ASSESS THE MONETARY VALUE OF GOODS AND SERVICES BASED ON CONSUMER PREFERENCE ANALYSIS
180	THIS STUDY , AMONG THEM , PRESENTS A DYNAMIC CHOICE MODEL THAT DEPICTS THE STRATEGIC MULTI AND FUTURE OWNERSHIP BEHAVIOR OF INDIVIDUALS
180	THE MODEL CAN EVALUATE THE IMPACT OF PURCHASE AND SALE DECISIONS INDEPENDENTLY
180	IN ADDITION , THE MODEL CAN DERIVE THE PHENOMENA OF WAITING DEMAND , WHICH MOVES CURRENT CONSUMPTION INTO THE FUTURE , AND DEMAND SELF CANNIBALISM , WHICH DRAWS FUTURE DEMAND INTO THE PRESENT , AS A REFLECTION OF CONSUMERS FORWARD LOOKING BEHAVIOR
180	IN THIS STUDY , THE MODEL IS APPLIED TO THE VEHICLE MARKET , BUT IT CAN ALSO BE USED TO ANALYZE REAL ESTATE , MOBILE PHONES , AND SUBSCRIPTION SERVICES
180	DECISION ANALYSIS SOCIETY APPLIED PROBABILITY TECHNOLOGY , INNOVATION MANAGEMENT AND ENTREPRENEURSHIP
180	STATISTIC 
181	FAIR SKILL BRIER SCORE , EVALUATING PROBABILISTIC FORECASTS OF ONE OFF EVENTS WITH DIFFERENT NUMBERS OF CATEGORICAL OUTCOMES
181	EXPERTS ABILITIES TO MAKE ACCURATE PROBABILISTIC FORECASTS ARE OFTEN EVALUATED WITH PROPER SCORING RULES
181	THE BRIER SCORE IS ONE OF THE MOST COMMONLY USED SCORING RULES WHEN THE TARGET OUTCOMES ARE CATEGORICAL
181	THE SCORE , HOWEVER , IS NOT ONLY INFLUENCED BY THE EXPERT S FORECASTING SKILL BUT ALSO BY THE INHERENT UNCERTAINTY OF THE EVENTS
181	FOR INSTANCE , AN EVENT WITH MORE OUTCOMES IS TYPICALLY MORE DIFFICULT TO FORECAST
181	IT IS THEN UNFAIR TO COMPARE THE BRIER SCORES OF EXPERTS WHO FORECAST EVENTS WITH DIFFERENT NUMBERS OF OUTCOMES
181	IN THIS PAPER , WE INTRODUCE A SIMPLE FAIR SKILL ADJUSTMENT TO THE BRIER SCORE TO REFINE SUCH COMPARISONS
181	WE INTRODUCE A BEHAVIORAL MODEL OF EXPERTS FORECASTS AND SHOW THAT THE FAIR SKILL BRIER SCORE IS A MORE RELIABLE MEASURE OF EXPERTS FORECASTING SKILLS IN GENERAL
181	WE THEN FIND EMPIRICAL SUPPORT FOR OUR THEORETICAL RESULTS FROM EXPERIMENTAL DATA
181	DECISION ANALYSIS SOCIETY APPLIED PROBABILITY OUR WORK RELATES TO THE THEME IN THE CONTEXT OF CROWDSOURCING AND INFORMATION ELICITATION 
182	A SIMULATED ANNEALING APPROACH TO DESIGNING OPTIMAL DECISION TREES FOR CLASSIFICATION , PRESCRIPTIVE , AND SURVIVAL ANALYSIS 
182	BINARY DECISION TREE IS A HIGHLY INTERPRETABLE MACHINE LEARNING MODEL AS HUMANS CAN EASILY UNDERSTAND HOW A PREDICTION IS MADE BY ANSWERING A SERIES OF BINARY QUESTIONS
182	INTERPRETABLE AI HAS PROVIDED A POWERFUL FRAMEWORK FOR CONSTRUCTING OPTIMAL DECISION TREES BY UTILIZING MULTIPLE RANDOM WARM STARTS AND LOCAL SEARCH TO ITERATIVELY IMPROVE EACH WARM START UNTIL A LOCALLY OPTIMAL DECISION TREE IS FOUND
182	HOWEVER , LOCAL SEARCH DOES NOT GUARANTEE GLOBAL OPTIMALITY
182	HENCE , WE PROPOSE TO INCORPORATE SIMULATED ANNEALING INTO DECISION TREE CONSTRUCTION AS SOME WORSE TRANSFORMATIONS COULD LEAD TO A BETTER FINAL MODEL
182	WE FOCUS ON THREE PROBLEM DOMAINS INCLUDING CLASSIFICATION , PRESCRIPTIVE AND SURVIVAL ANALYSIS TO PRODUCE OCT SA , OPT SA AND OST SA WHICH FURTHER IMPROVE ON OCT , OPT , AND OST BY PROBABILISTICALLY ALLOWING A TREE TO MOVE TO A TREE WITH A WORSE OBJECTIVE VALUE
182	DECISION ANALYSIS SOCIETY ARTIFICIAL INTELLIGENCE HEALTH APPLICATIONS SOCIETY
182	DECISION TREES CAN SERVE AS EFFECTIVE AND INTERPRETABLE OR MS TOOLS TO HARNESS THE DATA REVOLUTION
183	THOMPSON SAMPLING WITH DISCRETE SUPPORT
183	THOMPSON SAMPLING IS A POPULAR ALGORITHM FOR MULTI ARMED BANDIT PROBLEMS , BUT ITS BAYESIAN POSTERIOR UPDATE CAN BE COMPUTATIONALLY EXPENSIVE FOR COMPLEX REWARD DISTRIBUTIONS
183	RECENTLY , PRIOR DISCRETIZATION HAS BEEN PROPOSED TO ADDRESS THIS ISSUE
183	IN THIS PAPER , WE PROPOSE A NEW PRIOR DISCRETIZATION METHOD THAT GUARANTEES THE SAME REGRET RATE WITHOUT REQUIRING THE UNREALISTIC ASSUMPTION THAT THE TRUE PARAMETER IS WITHIN THE DISCRETE PRIOR SUPPORT
183	MOREOVER , WE INTRODUCE A MODIFIED POSTERIOR UPDATE APPROACH THAT FURTHER IMPROVES THE PERFORMANCE OF DISCRETE PRIOR THOMPSON SAMPLING
183	WE PROVE THAT THE ACCUMULATED REGRET IS BOUNDED BY O , LOG , T , , WITH HIGH PROBABILITY
183	IN ADDITION , WE CONDUCT NUMERICAL EXPERIMENTS TO VALIDATE OUR THEORETICAL ANALYSIS AND DEMONSTRATE THE PERFORMANCE OF OUR PROPOSED ALGORITHM
183	DECISION ANALYSIS SOCIETY ARTIFICIAL INTELLIGENCE MACHINE LEARNING FOR OPTIMIZATION
183	THOMPSON SAMPLING IS AN EFFECTIVE OPTIMIZATION ALGORITHM FOR DATA DRIVEN DECISION MAKING
184	DYNAMIC CONCERN FOR MISSPECIFICATION
184	WE CONSIDER AN AGENT WHO POSITS A SET OF PROBABILISTIC MODELS FOR THE PAYOFF RELEVANT OUTCOMES
184	THE AGENT HAS A PRIOR OVER THIS SET BUT FEARS THE ACTUAL MODEL IS OMITTED AND HEDGES AGAINST THIS POSSIBILITY
184	THE CONCERN FOR MISSPECIFICATION IS ENDOGENOUS , IF A MODEL EXPLAINS THE PREVIOUS OBSERVATIONS WELL , THE CONCERN ATTENUATES
184	WE SHOW THAT DIFFERENT STATIC PREFERENCES UNDER UNCERTAINTY , SUBJECTIVE EXPECTED UTILITY , MAXMIN , ROBUST CONTROL , ARISE IN THE LONG RUN , DEPENDING ON HOW QUICKLY THE AGENT BECOMES UNSATISFIED WITH UNEXPLAINED EVIDENCE AND WHETHER THEY ARE MISSPECIFIED
184	THE MISSPECIFICATION CONCERN S ENDOGENEITY NATURALLY INDUCES BEHAVIOR CYCLES , AND WE CHARACTERIZE THE LIMIT ACTION FREQUENCY
184	THIS MODEL IS CONSISTENT WITH THE EMPIRICAL EVIDENCE ON MONETARY POLICY CYCLES AND CHOICES IN THE FACE OF COMPLEX TAX SCHEDULES
184	DECISION ANALYSIS SOCIETY BEHAVIORAL OPERATIONS MANAGEMENT APPLIED PROBABILITY 
185	AS IF AND PROCESS MODELS OF LABOR PROVISION , A CASE STUDY OF THE TAXI MARKET
185	A FUNDAMENTAL ASSUMPTION OF EXPECTED UTILITY MODELS IS THAT AGENTS MAKE PREDICTIONS BY FORMULATING RATIONAL EXPECTATIONS
185	BUILDING ON THIS ASSUMPTION , THE LITERATURE HAS ADDRESSED TO WHAT EXTENT NEOCLASSICAL OR BEHAVIORALLY INFORMED UTILITY MODELS BEST DESCRIBE INTERTEMPORAL SUBSTITUTION OF LABOR AND LEISURE , FOCUSING ON THE TAXI MARKET
185	USING DATA FROM MILLION TAXI TRIPS , WE FIND THAT HOURLY EARNINGS ARE BARELY PREDICTABLE
185	UNDER SUCH UNCERTAINTY , SATISFICING MODELS PREDICT BEHAVIOR OF DRIVERS BETTER THAN UTILITY MODELS
185	THESE MODELS DO NOT REQUIRE CALCULATING EXPECTED EARNINGS AND TERMINATE SHIFTS WHEN REACHING AN ASPIRATION LEVEL ON SHIFT DURATION OR EARNINGS
185	DECISION ANALYSIS SOCIETY BEHAVIORAL OPERATIONS MANAGEMENT 
186	EVALUATING THE EFFECTIVENESS OF HURRICANE EVACUATION ORDERS BY LEVERAGING LARGE SCALE HUMAN MOBILITY PATTERNS
186	EVACUATION ORDERS ARE VITAL FOR EMERGENCY PREPAREDNESS , YET THEIR EFFECTIVENESS IN INCREASING EVACUATION RATES REMAINS UNCERTAIN
186	THIS STUDY EXAMINES THE CAUSAL EFFECT OF EVACUATION ORDERS USING PASSIVELY COLLECTED HIGH FIDELITY MOBILITY DATA
186	BY EMPLOYING CAUSAL INFERENCE METHODS , WE ESTIMATE THE EFFECTIVENESS OF MANDATORY EVACUATION ORDERS DURING HURRICANE DORIAN ACROSS , CENSUS BLOCK GROUPS IN FLORIDA
186	WE FURTHER INVESTIGATED SHADOW EVACUATION PATTERNS TO UNDERSTAND EVACUATION ORDER RESPONSES IN AREAS WITHOUT EVACUATION ZONES AND AREAS WITH EVACUATION ZONES BUT NO ORDERS
186	THE FINDINGS SHED LIGHT ON THE EFFICACY OF EVACUATION ORDERS AND THEIR BROADER IMPLICATIONS FOR COMMUNITY RESPONSES
186	DECISION ANALYSIS SOCIETY DATA MINING DATA , OR , AND SOCIAL JUSTICE
186	MOBILITY DATA TO STUDY EVACUATION ORDER EFFECTIVENESS AND SHADOW EVACUATION IN DISASTER RESPONSE 
187	MINING SEQUENTIAL DECISION MAKING BEHAVIOR BASED ON LATENT STATES
187	WE PROPOSE AN INFLUENCE DIAGRAM MODEL REPRESENTING SEQUENTIAL DECISION MAKING BEHAVIOR WITH UNDERLYING LATENT STATES
187	THE MODEL UTILIZES A GENERALIZED REWARD FUNCTION TO CAPTURE STATIONARY DECISION RULES , WHETHER NORMATIVE OR DESCRIPTIVE
187	WE THEN TRANSFORM THE INFLUENCE DIAGRAM INTO A HIDDEN MARKOV CHAIN WITH NEURAL NETWORKS FOR ESTIMATION
187	CASE STUDIES ON THE CLICK DATA OF ONLINE SHOPPING FROM K CUSTOMERS AND THE PILOT LANDING OPERATIONS OF ABOUT FLIGHTS SHOW SURPRISINGLY GOOD PREDICTABILITY AND EXPLAINABLE LATENT STATES
187	DECISION ANALYSIS SOCIETY DATA MINING 
188	EMPATHY , MOTIVATED REASONING , AND REDISTRIBUTION I INVESTIGATE BOTH THEORETICALLY AND EXPERIMENTALLY THE ECONOMICS OF EMPATHY AND ITS IMPLICATIONS FOR REDISTRIBUTION
188	I FIRST DEFINE EMPATHY AS AN ACCURATE SIMULATION OF HOW ONE WOULD FEEL IF THEY WERE IN ANOTHER S POSITION , DISTINGUISHING IT FROM ALTRUISM
188	I PROPOSE A NOVEL MECHANISM BY WHICH PERSONAL EXPERIENCE AFFECTS DISTRIBUTIONAL MOTIVES THROUGH EMPATHY , WEALTHY INDIVIDUALS HAVE SELFISH MOTIVATION NOT TO BE EMPATHETIC TOWARDS THE POOR IN ORDER TO JUSTIFY LESS REDISTRIBUTION , IN ADDITION , MORE VARIED PERSONAL EXPERIENCE OF CONSUMPTION CONSTRAINS SUCH MOTIVATED REASONING , THEREFORE INCREASING EMPATHY AND REDISTRIBUTION
188	I PROVIDE A TEST OF THE MECHANISM IN A LABORATORY SETTING AND FIND STRONG SUPPORT FOR THE VALIDITY OF THE MECHANISM DECISION ANALYSIS SOCIETY DIVERSITY , EQUITY , AND INCLUSION 
188	WE NEED TO INTERPRET THE DATA ABOUT OTHER PEOPLE S WELLBEING WITH EMPATHY TO FORM A GOOD POLICY 
189	HARNESSING COLLECTIVE INTELLIGENCE UNDER A LACK OF CULTURAL CONSENSUS
189	WE PRESENT A NONPARAMETRIC BAYESIAN MODEL THAT EXTENDS CULTURAL CONSENSUS THEORY , A MATHEMATICAL FRAMEWORK FOR INFERRING GROUP CONSENSUS , BY INTRODUCING A LATENT CONSTRUCT THAT MAPS BETWEEN PRE TRAINED DEEP NEURAL NETWORK EMBEDDINGS OF AN ENTITY AND THE CONSENSUS BELIEF AMONGST ONE OR MORE SUBSETS OF RESPONDENTS REGARDING THOSE ENTITIES
189	WE APPLIED OUR EXTENDED CCT TO VARIOUS DOMAINS , INCLUDING RISK PERCEPTIONS OF TECHNOLOGIES , LEADERSHIP PERCEPTION , FIRST IMPRESSIONS OF FACES , AND HUMOR PERCEPTION COMPARED TO EXISTING METHODS , OUR APPROACH BETTER LEVERAGES THE UNDERLYING STRUCTURE AND INTERCONNECTEDNESS OF BELIEFS , CONTRIBUTING TO A MORE COMPREHENSIVE UNDERSTANDING OF COLLECTIVE INTELLIGENCE AND SERVING AS A POTENTIAL FOUNDATION FOR CONSENSUS AWARE INFORMATION TECHNOLOGIES
189	DECISION ANALYSIS SOCIETY EMERGING TECHNOLOGIES AND APPLICATIONS ARTIFICIAL INTELLIGENCE
189	IN THIS PROJECT , WE HARNESS COLLECTIVE INTELLIGENCE FROM LARGE SCALE HUMAN BEHAVIORAL DATA
189	OUR METH 
190	USING REAL OPTION TO EVALUATE A CAP AND FLOOR COMPENSATION MODEL FOR A DC CONNECTION BETWEEN ERCOT AND THE WESTERN GRID
190	WE WILL DESCRIBE THE USE OF REAL OPTION PRICING CONCEPTS TO VALUE A PROPOSED TRANSMISSION LINE LINKING THE ELECTRIC POWER GRIDS IN ERCOT , TEXAS , AND THE WESTERN INTERCONNECTION , CALIFORNIA AND THE WEST COAST , 
190	THIS STUDY WILL EXAMINE NOVEL PATHWAYS FOR THE FINANCING OF TRANSMISSION ASSETS , INCLUDING A CAP AND FLOOR COST RECOVERY SYSTEM SUCH AS THOSE USED FOR INTER GRID FACILITIES IN EUROPE AND FOR MAJOR INFRASTRUCTURE PROJECTS IN OTHER COUNTRIES
190	THESE CAP AND FLOOR COMPENSATION MODELS HAVE CHARACTERISTICS SIMILAR TO CALL OPTIONS AND PUT OPTIONS ON UNCERTAIN STOCK PRICES , AND THEIR VALUE CAN BE ESTIMATED IN MUCH THE SAME WAY
190	DECISION ANALYSIS SOCIETY ENRE , ELECTRICITY FINANCE
191	PRIDE AND PROGRAM , HOW OVERCONFIDENCE DRIVES CRYPTO ASSET ADOPTION
191	DESPITE LARGE AND PERSISTENT VOLATILITY , CRYPTO ASSETS HAVE BECOME AN IMPORTANT INVESTMENT TOOL OVER THE PAST DECADE
191	HOWEVER , LITTLE IS KNOWN ABOUT THE DRIVERS OF ADOPTION OF SUCH ASSETS AND THE REASONS WHY SOME INVESTORS CHOOSE TO BANK ON CRYPTO ASSETS IN AN EARLY MARKET WITH A LACK OF INFORMATION AND HIGH VOLATILITY
191	WE SHOW THAT OVERCONFIDENT INVESTORS DRIVE THE EXPANSION OF CRYPTO ASSETS BY EXPECTING HIGHER RETURNS THAN MASS MARKET INVESTORS
191	USING DATA FROM APPROXIMATELY , INVESTORS , EXPERIMENTAL PARTICIPANTS , AND MORE THAN MILLION TRANSACTIONS , WE SHOW THAT CONFIDENCE IN INVESTMENT KNOWLEDGE SIGNIFICANTLY INCREASES THE CHANCES OF INVESTING IN AN EARLY CRYPTO MARKET
191	HOWEVER , OBJECTIVE KNOWLEDGE HAS THE OPPOSITE EFFECT
191	FURTHERMORE , OVERCONFIDENT EARLY INVESTORS OVERTRADE CRYPTO ASSETS AND HURT THEIR BOTTOM LINE WITH EVERY ADDITIONAL TRANSACTION
191	DECISION ANALYSIS SOCIETY FINANCE MSOM , TECHNOLOGY , INNOVATION AND ENTREPRENEURSHIP
191	WE USE LARGE SCALE API DATA FROM CRYPTO TRADERS 
192	MARKET AMBIGUITY ATTITUDE AND THE RISK RETURN TRADEOFF
192	THE RISK RETURN TRADEOFF FOR THE AGGREGATE STOCK MARKET PREDICTS THAT PERIODS OF HIGH MARKET VOLATILITY ARE FOLLOWED BY PERIODS WITH HIGHER AVERAGE MARKET EXCESS RETURNS
192	DESPITE BEING VIEWED AS A FUNDAMENTAL LAW OF FINANCE , THE RISK RETURN TRADEOFF HAS BEEN DIFFICULT TO IDENTIFY IN THE DATA , WITH SOME STUDIES FINDING NO RELATION OR EVEN A NEGATIVE RELATION BETWEEN MARKET VOLATILITY AND FUTURE EXCESS RETURNS
192	MOTIVATED BY A REPRESENTATIVE AGENT ASSET PRICING MODEL IN THE PRESENCE OF KNIGHTIAN UNCERTAINTY , WE OBTAIN THE THEORETICAL PREDICTION THAT MARKET AMBIGUITY ATTITUDE MODERATES THE RISK RETURN TRADEOFF
192	WE INTRODUCE A METHODOLOGY FOR MEASURING MARKET AMBIGUITY ATTITUDE AND TEST ITS RELEVANCE FOR EXPLAINING THE RISK RETURN TRADEOFF IN IN SAMPLE AND OUT OF SAMPLE TESTS
192	WE FIND SUPPORT FOR THE THEORETICAL PREDICTIONS
192	DECISION ANALYSIS SOCIETY FINANCE 
193	METAWISDOM OF THE CROWD , HOW CHOICE WITHIN AIDED DECISION MAKING CAN MAKE CROWD WISDOM ROBUST
193	DECISION SUPPORT SYSTEMS PRESENT INDIVIDUALS WITH DECISION AIDS DISCRETE PRESENTATIONS OF RELEVANT INFORMATION , FRAMES , OR HEURISTICS TO ENHANCE THE QUALITY AND SPEED OF DECISION MAKING , BUT HAVE THE POTENTIAL TO BIAS GROUP JUDGMENTS BY LIMITING PREDICTIVE DIVERSITY
193	WE REDESCRIBE THE WISDOM OF THE CROWD AS OFTEN STARTING WITH THE CHOICE OF DECISION AIDS AND DEFINE METAWISDOM OF THE CROWD AS WHEN COLLECTIVE CHOICE OF AIDS LEADS TO HIGHER CROWD ACCURACY THAN RANDOMIZED ASSIGNMENT TO THE SAME AIDS , A COMPARISON THAT ACCOUNTS FOR THE INFORMATION CONTENT OF THE AIDS
193	IN TWO EXPERIMENTS WE FIND STRONG EVIDENCE OF METAWISDOM
193	IT COMES ABOUT THROUGH DIVERSE ERRORS ARISING THROUGH THE USE OF DIVERSE AIDS , NOT THROUGH WIDESPREAD USE OF THE AIDS THAT INDUCE THE MOST ACCURATE ESTIMATES , THE MICROFOUNDATIONS OF CROWD WISDOM APPEAR IN THE FIRST CHOICE
193	DECISION ANALYSIS SOCIETY GROUP DECISION AND NEGOTIATION 
193	WE PRESENT A DESIRABLE CROWD WISDOM EFFECT FOR THE CONSUMPTION OF THE PRODUCTS OF THE DATA REVOLUTIO 
194	ON THE DISCLOSURE OF DEFENSIVE POSTURE , ADVERSARIAL BELIEF FORMATION AND TARGET SELECTION DECISIONS
194	WE FOCUS ON THE PROBLEM OF TECHNOLOGY DEPLOYMENT AND INFORMATION DISCLOSURE IN SECURITY AND DEFENSE SETTINGS
194	WE CONDUCT HUMAN SUBJECT EXPERIMENTS , N , TO STUDY , I , ADVERSARIAL BELIEFS REGARDING WHERE NEW DEFENSE TECHNOLOGY IS DEPLOYED , INCLUDING HOW SUCH BELIEFS ARE FORMED , AND , II , TARGET SELECTION ATTACK DECISIONS
194	IN THE EXPERIMENTS , THE PARTICIPANTS PLAYED THE ROLE OF AN ADVERSARY , AND WERE TASKED WITH MAKING TARGET SELECTION DECISIONS IN RESPONSE TO , POTENTIALLY DECEPTIVE , INFORMATION RELEASED BY A DEFENDER
194	AMONG MANY INTERESTING INSIGHTS , WE FIND THAT THE INFORMATION RELEASED BY THE DEFENDER , AND THE DEFENDER S TARGET VALUATIONS , WHICH IS TREATED AS COMMON KNOWLEDGE , , HAVE A SIGNIFICANT EFFECT ON THE PARTICIPANTS BELIEFS REGARDING WHERE THE NEW TECHNOLOGY IS DEPLOYED
194	THESE BELIEFS ALSO TRANSFER TO THE PARTICIPANTS TARGET SELECTION DECISIONS
194	DECISION ANALYSIS SOCIETY MILITARY AND SECURITY BEHAVIORAL OPERATIONS MANAGEMENT
195	INTERDEPENDENCE ACROSS NATIONAL CRITICAL FUNCTIONS
195	IN , CISA INTRODUCED NATIONAL CRITICAL FUNCTIONS , NCFS , FOR MANAGING RISKS TO ECONOMIC AND NATIONAL SECURITY
195	NCFS EMPHASIZE INTERDEPENDENCE AND SYSTEMIC RISKS IN CRITICAL INFRASTRUCTURE
195	CASCADING AND COMMON CAUSE FAILURES CAN PROPAGATE ACROSS NCFS , SPANNING ECONOMIC , SOFTWARE , AND POLICY DOMAINS
195	NCF INTERDEPENDENCIES OFFER RESILIENCE AND ALTERNATIVE SOLUTIONS
195	THIS PAPER ENHANCES NCF RESEARCH BY PROVIDING A FRAMEWORK , MAPPING NCFS TO ECONOMIC SECTORS , AND RANKING THEIR INTERDEPENDENCE
195	KEY NCFS INCLUDE OPERATE CORE NETWORK , PROVIDE CAPITAL MARKETS , PROVIDE RADIO BROADCAST ACCESS NETWORK SERVICES , AND EDUCATE AND TRAIN
195	WE HIGHLIGHT THE ROLE INTERDEPENDENCE ROLE AND OFFER RECOMMENDATIONS FOR POLICYMAKERS AND ANALYSTS IN MODELING NCFS
195	DECISION ANALYSIS SOCIETY MILITARY AND SECURITY PUBLIC SECTOR OR 
195	WE USE DATA ANALYTICS TO ANALYZE NETWORKS OF INTERDEPENDENCIES ACROSS CRITICAL INFRASTRUCTURE
196	SUPPLIER S RISK PREFERENCE AND SUPPLY NETWORK PERFORMANCE UNDER EXTREME UNCERTAINTIES
196	FIRMS REQUIRE FREQUENT OPERATIONAL DECISION MAKING TO ADAPT TO THE VOLATILE BUSINESS ENVIRONMENT
196	HOWEVER , SUCH SHORT TERM DECISION MAKING IS CHALLENGING AS DECISION MAKERS HAVE LIMITED KNOWLEDGE OF POTENTIAL RISKS
196	IN THIS STUDY , WE FOCUS ON THE EFFECT OF SUPPLIERS RISK PREFERENCE , A CRITICAL FIRM STRATEGY THAT INFLUENCES DECISION MAKING , ON SUPPLY NETWORK PERFORMANCE
196	WE ADOPT A MULTI METHOD APPROACH , SUCH AS TEXT ANALYSIS AND SIMULATIONS TO GAIN INSIGHTS INTO THE EFFECTS OF SUPPLIERS RISK PREFERENCE ON NETWORK PERFORMANCE
196	THE RESULTS SHOW THE APPROPRIATE LEVEL OF SUPPLIER S RISK PREFERENCE
196	THE FINDINGS ALSO SUGGEST THAT NETWORK PERFORMANCE CAN FURTHER IMPROVE WHEN DIFFERENTIATING RISK PREFERENCES ACROSS DIFFERENT SUPPLIER POSITIONS
196	THESE FINDINGS PROVIDE INSIGHTS FOR ADDRESSING EXTREME CONDITIONS BY MANAGING RISK PREFERENCE
196	DECISION ANALYSIS SOCIETY MSOM , SUPPLY CHAIN 
197	LIPSCHITZ BANDITS WITH BATCHED FEEDBACK
197	WE STUDY LIPSCHITZ BANDIT PROBLEMS WITH BATCHED FEEDBACK , WHERE THE EXPECTED REWARD IS LIPSCHITZ AND THE REWARD OBSERVATIONS ARE COMMUNICATED TO THE PLAYER IN BATCHES
197	WE INTRODUCE A NOVEL LANDSCAPE AWARE ALGORITHM , CALLED BATCHED LIPSCHITZ NARROWING , BLIN , , THAT OPTIMALLY SOLVES THIS PROBLEM
197	SPECIFICALLY , WE SHOW THAT FOR A T STEP PROBLEM WITH LIPSCHITZ REWARD OF ZOOMING DIMENSION D Z , OUR ALGORITHM ACHIEVES THEORETICALLY OPTIMAL , UP TO LOGARITHMIC FACTORS , REGRET RATE WIDETILDE , MATHCAL , O , , LEFT , T , FRAC , D Z , , D Z , , RIGHT , USING ONLY MATHCAL , O , LEFT , LOG LOG T RIGHT , BATCHES
197	WE ALSO PROVIDE COMPLEXITY ANALYSIS FOR THIS PROBLEM
197	OUR THEORETICAL LOWER BOUND IMPLIES THAT OMEGA , LOG LOG T , BATCHES ARE NECESSARY FOR ANY ALGORITHM TO ACHIEVE THE OPTIMAL REGRET
197	THUS , BLIN ACHIEVES OPTIMAL REGRET RATE USING MINIMAL COMMUNICATION W DECISION ANALYSIS SOCIETY OPT , MACHINE LEARNING 
198	EPIDEMIC DYNAMICS OF NETWORK IN DETERMINING OPTIMAL HUMAN MOBILITY
198	EPIDEMICS ARE A SEVERE PUBLIC HEALTH CONCERN DUE TO THEIR ABILITY TO CAUSE WIDESPREAD ILLNESS , DEATH , AND ECONOMIC DISRUPTION
198	THE EMERGENCE OF NEW INFECTIOUS AGENTS , SUCH AS THE COVID PANDEMIC , HAS HIGHLIGHTED THE NEED FOR EFFECTIVE INTERVENTION STRATEGIES TO CONTROL THE CONTAGION DYNAMICS
198	THIS RESEARCH PRESENTS A NETWORK AGENT BASED MODEL TO SIMULATE THE SPREAD OF INFECTIOUS DISEASES IN TWO SPATIAL REGIONS UNDER DIFFERENT LOCKDOWNS
198	IT USES DATA SCIENCE TECHNIQUES TO PREDICT THE DYNAMICS OF THE SIRS RE MODEL AND EXPLORE THE OPTIMAL FREQUENCY OF INTERACTIONS BETWEEN INDIVIDUALS TO REDUCE THE EFFECT OF INFECTIOUS DISEASES
198	DECISION ANALYSIS SOCIETY OPT , NETWORK OPTIMIZATION MACHINE LEARNING IN OPERATIONS
199	QUASI SEQUENTIAL EQUILIBRIUM AND ITS SMOOTH PATH SELECTION
199	BY SLIGHTLY RELAXING THE REQUIREMENTS OF SEQUENTIAL RATIONALITY AND CONSISTENCY ON BELIEFS IN A SEQUENTIAL EQUILIBRIUM WHILE RETAINING SUBGAME PERFECTION , WE ESTABLISH THE CONCEPT OF QUASI SEQUENTIAL EQUILIBRIUM THROUGH THE INTRODUCTION OF COMMON ACTION AND BELIEF INDEPENDENT CONSISTENCY
199	THIS RELAXATION ALLOWS AN EXPLICIT MATHEMATICAL CHARACTERIZATION THROUGH LOCAL SEQUENTIAL RATIONALITY , WHICH DIRECTLY YIELDS A POLYNOMIAL SYSTEM AS A NECESSARY AND SUFFICIENT CONDITION FOR A QUASI SEQUENTIAL EQUILIBRIUM
199	FOR MANY WELL KNOWN GAMES , A QUASI SEQUENTIAL EQUILIBRIUM IS IDENTICAL TO A SEQUENTIAL EQUILIBRIUM
199	TO COMPUTE SUCH AN EQUILIBRIUM , WE DEVELOP A DIFFERENTIABLE PATH FOLLOWING METHOD BY CONSTITUTING A SQUARE ROOT BARRIER AGENT EXTENSIVE FORM GAME
199	NUMERICAL RESULTS FURTHER CONFIRM THE EFFECTIVENESS AND EFFICIENCY OF THE METHOD
199	DECISION ANALYSIS SOCIETY OPT , NONLINEAR OPTIMIZATION 
200	PORTFOLIO OPTIMIZATION WITH PROBABILITY ESTIMATED CVAR OBJECTIVE AND RETURN CONSTRAINTS
200	BUSINESS INTELLIGENCE ANALYSIS FOR FINANCIAL ASSET MANAGEMENT IS WELL DEVELOPED WITH MANY APPLICATIONS NOWADAYS
200	PORTFOLIO OPTIMIZATION IS TRADITIONALLY STIMULATED BY ADEQUATELY MODELING THE REQUIREMENTS , INCLUDING RISKS , RETURNS , AND COMPUTATIONAL EFFICIENCY
200	HOWEVER , THE OPTIMIZATION FRAMEWORK STRICTLY RELIES ON STATISTICAL PRINCIPLES AND DISTRIBUTION ASSUMPTIONS , WHICH CONTAIN NO FUTURE INFORMATION
200	IN THIS WORK , WE PROPOSE A THREE PHASES PREDICT THEN OPTIMIZE FRAMEWORK USING AI AND CVAR OPTIMIZATION
200	IN PARTICULAR , THE APPROACH CAN BE USED FOR MAXIMIZING EXPECTED PREDICTED RETURNS WHILE MINIMIZING THE RISK MEASURED BY THE CVAR OBJECTIVE SIMULTANEOUSLY
200	A CASE STUDY FOR THE PORTFOLIO OF MULTIPLE US STOCKS IS PERFORMED TO DEMONSTRATE THIS NEW TECHNIQUE CAN BE IMPLEMENTED
200	DECISION ANALYSIS SOCIETY OPT , OPTIMIZATION UNDER UNCERTAINTY ARTIFICIAL INTELLIGENCE
201	VALUATION OF A SEQUENTIAL COMPOUND OPTION CONSIDERING GENERATION AND TRANSMISSION EXPANSIONS
201	THIS STUDY ADDRESSES AN ELECTRIC POWER DECISION MAKER WHO HAS TO DECIDE ON GENERATION EXPANSION IN THE SHORT RUN AND TRANSMISSION EXPANSION IN THE LONG RUN
201	TO AID THE DECISION MAKER , WE MODEL AN ELECTRICAL EXPANSION PROBLEM USING A SEQUENTIAL COMPOUND OPTION WHICH INCLUDES A GENERATION ADDITION OPTION FOLLOWED BY A TRANSMISSION LINE ADDITION OPTION
201	ELECTRICITY DEMAND IS UNCERTAIN , AND WE ASSUME IT FOLLOWS GEOMETRIC BROWNIAN MOTION
201	WHEN DEMAND INCREASES , IT CREATES A NECESSITY FOR ADDITIONAL GENERATION CAPACITY
201	THE NETWORK OFTEN NEEDS A NEW TRANSMISSION LINE TO CIRCULATE THIS ADDITIONAL ELECTRICITY
201	THUS , THE DEMAND AND EXISTING ELEMENTS IN THE NETWORK INFLUENCE LATER EXPANSION DECISIONS
201	WE CALCULATE THE OPTION VALUE BASED ON THE BENEFIT OF THE ADDED COMPONENTS , AND THE BENEFIT IS DETERMINED FROM THE REDUCTION IN LOCATIONAL MARGINAL PRICE AFTER THE SUPPLEMENTS
201	DECISION ANALYSIS SOCIETY OPT , OPTIMIZATION UNDER UNCERTAINTY OPTIMIZATION , OPT , 
202	REMANUFACTURING FACILITY INSTALLATION DECISIONS UNDER UNCERTAIN NEW PRODUCT PURCHASING COST AND RETURN PRODUCTS REMANUFACTURING COST
202	IN THIS PAPER , WE CONSIDER A COMPANY THAT CURRENTLY RELIES ON EXTERNAL PURCHASES TO MEET CUSTOMER DEMAND AND HAS THE FLEXIBILITY TO INSTALL A REMANUFACTURING FACILITY
202	WITH THE KEY ASSUMPTION THAT THE REMANUFACTURED PRODUCTS CAN FULLY SUBSTITUTE NEW PRODUCTS DEMAND , WE DETERMINE THE VALUE OF SUCH FLEXIBILITY AND IDENTIFY THE OPTIMAL SIZE AND TIMING FOR INSTALLING THE REMANUFACTURING FACILITY UNDER THE UNCERTAIN EXTERNAL PURCHASING PRICES AND RETURN PRODUCTS REMANUFACTURING COSTS
202	TO ADDRESS THIS PROBLEM , WE ADOPT A PROFIT MAXIMIZATION CRITERION AND EMPLOY THE REAL OPTIONS THEORY AS OUR MODELING FRAMEWORK
202	SPECIFICALLY , WE UTILIZE A LEAST SQUARE MONTE CARLO SIMULATION APPROACH TO OBTAIN A SOLUTION
202	THE STUDY AIMS TO PROVIDE VALUABLE INSIGHTS INTO THE STRATEGIC CONSIDERATIONS AND POTENTIAL ECONOMIC BENEFITS OF INSTALLING A REMANUFACTURING FACILITY
202	DECISION ANALYSIS SOCIETY OPT , OPTIMIZATION UNDER UNCERTAINTY OPTIMIZATION , OPT , 
203	INTERACTIVE OPTIMIZATION WITH ADAPTIVE REFINEMENT ACTIONS FOR SUPPLY CHAIN DESIGN
203	WE PROPOSE AN INTERACTIVE OPTIMIZATION FRAMEWORK THAT ADAPTIVELY AND HOLISTICALLY INTERACTS WITH A HUMAN USER TO RECOMMEND A SUPPLY CHAIN DESIGN , THE DESIGN S EXPECTED SYSTEMATIC PERFORMANCE AND ASSOCIATED CONFIDENCE INTERVALS
203	OUR FRAMEWORK ADAPTIVELY ASKS THE HUMAN USER QUESTIONS BASED ON THE MATH PROGRAM S CURRENT SOLUTION , CONFIDENCE INTERVALS , AND AUXILIARY INFORMATION , E G , DUAL VARIABLES , TO GAIN ACCESS TO MORE OR BETTER QUALITY DATA , PROBLEM DOMAIN KNOWLEDGE , OR UPDATED PREFERENCE WEIGHTS
203	THE HUMAN USER S RESPONSES ARE INTERPRETED TO MAKE ADAPTIVE REFINEMENT ACTIONS THAT IMPROVE THE SOLUTION QUALITY , REDUCE THE REALITY GAP , OR IMPROVE THE CONFIDENCE IN THE SYSTEM PERFORMANCE ESTIMATES
203	DECISION ANALYSIS SOCIETY OPT , OPTIMIZATION UNDER UNCERTAINTY 
204	INVESTIGATING THE FINANCING MECHANISM IN A PUSH OR PULL SUPPLY CHAIN
204	CAPITAL CONSTRAINED PARTICIPANTS MAY BEHAVE DIFFERENTLY IN A PUSH OR PULL SUPPLY CHAIN
204	ACCORDINGLY , SUPPLY CHAIN FINANCE MECHANISMS CAN BE DIFFERENT GIVEN THE DIFFERENT SUPPLY CHAIN MODES
204	THIS STUDY EXAMINES AND COMPARES THE VARIOUS SUPPLY CHAIN FINANCE MECHANISMS IN A PUSH OR PULL SUPPLY CHAIN TO ALLEVIATE PARTICIPANTS CAPITAL CONSTRAINTS AND IMPROVE THEIR PROFIT
204	DECISION ANALYSIS SOCIETY OPTIMIZATION , OPT , OPT , OPTIMIZATION UNDER UNCERTAINTY
204	USE OPTIMIZATION TO SUPPORT SUPPLY CHAIN PARTICIPANTS OPERATIONAL AND FINANCIAL DECISIONS
205	MEASURING DECENTRALIZED NETWORK EFFICIENCY , A PRE MORTEM STACKELBERG GAME
205	IN THIS RESEARCH , WE PRESENT THE PRE MORTEM STACKELBERG GAME MODEL AS A NON COOPERATIVE GAME APPROACH THAT CAN SERVE AS AN ALTERNATIVE TO THE CONVENTIONAL DECENTRALIZED NETWORK DEA , DATA ENVELOPMENT ANALYSIS , MODEL WHICH SUFFERS FROM INFEASIBILITY
205	WE HAVE IDENTIFIED THE CIRCUMSTANCES THAT GIVE RISE TO THE ISSUE AND RECOMMENDED THE USE OF NON RADIAL SLACKS AS A REMEDY
205	OUR FINDINGS SHOW THAT THE PROPOSED MODEL PROVIDES AN ALTERNATIVE EFFICIENCY MEASURE FOR THE FOLLOWER AND ENABLES AN OPTIMAL ADJUSTMENT OF INTERMEDIATE PRODUCTS , FOR WHICH FEASIBLE SOLUTIONS DO NOT EXIST UNDER THE CONVENTIONAL MODEL
205	THE PROPOSED MODEL PROVIDES EQUIVALENT EFFICIENCY MEASURES TO THE TRADITIONAL MODEL WHEN FEASIBLE SOLUTIONS EXIST
205	IT IS EXPECTED TO FACILITATE THE USE OF NON COOPERATIVE GAMES IN NETWORK DEA WHEN THE VRS ASSUMPTION IS APPROPRIATE FOR PERFORMANCE EVALUATION
205	DECISION ANALYSIS SOCIETY OPTIMIZATION , OPT , PRACTICE 
206	DIFFERENTIAL GAME THEORETIC MODELS FOR DESIGNING CONSERVATION INCENTIVES
206	THE EFFICIENT MANAGEMENT OF WATER RESOURCES IS CRUCIAL FOR ADDRESSING A RANGE OF ENVIRONMENTAL CHALLENGES
206	THIS STUDY APPLIES DIFFERENTIAL GAME THEORETIC MODELS TO DESIGN INCENTIVE SCHEMES FOR FARMERS , GEOGRAPHICALLY DISTRIBUTED ACROSS A RIVER NETWORK
206	THREE MAIN PLAYERS CONSIDERED ARE NON GOVERNMENTAL ORGANIZATIONS , NGOS , , UPSTREAM FARMERS , AND DOWNSTREAM FARMERS WHILE ENVIRONMENTAL AND SOCIAL FEEDBACK LOOPS ARE CAPTURED
206	THE PROPOSED APPROACH ALLOWS FOR ANALYZING THE STRATEGIC BEHAVIOR OF FARMERS IN THEIR DECISION MAKING PROCESS RELATED TO WATER CONSUMPTION AND THE NGOS IN ALLOCATING INCENTIVES
206	THE PROPOSED MODEL IS PARAMETERIZED FOR THE RED RIVER , THE SECOND LARGEST BASIN IN THE SOUTH CENTRAL UNITED STATES , AND DEMONSTRATES OPTIMAL INCENTIVE ALLOCATIONS BALANCING THE ECONOMIC AND ENVIRONMENTAL EFFICIENCY AMONG FARMERS
206	DECISION ANALYSIS SOCIETY OPTIMIZATION , OPT , 
207	GETTING MORE WISDOM OUT OF THE CROWD , THE CASE OF COMPETENCE WEIGHTED AGGREGATES
207	THIS PAPER SHOWS THAT GROUP DISCUSSIONS CAN SERVE AS AN INSTRUMENT TO IMPROVE INDIVIDUALS CALIBRATION , WHICH IN TURN STRONGLY INCREASES THE ACCURACY OF COMPETENCE WEIGHTED , STATISTICAL AGGREGATES
207	WE CONDUCT AN EXPERIMENT IN WHICH PARTICIPANTS ESTIMATE QUANTITIES AND REPORT THEIR SELF PERCEIVED COMPETENCE FOR VARIOUS JUDGMENT PROBLEMS
207	IN ADDITION , THEY ENGAGE IN GROUP DISCUSSIONS WITH OTHER JUDGES ON UNRELATED JUDGMENT TASKS
207	WE FIND THAT PRIOR TO PARTICIPATING IN THE GROUP DISCUSSIONS , JUDGES SELF PERCEIVED COMPETENCE AND THEIR ESTIMATION ACCURACY ARE POORLY ALIGNED
207	HOWEVER , THE INFORMATION EXCHANGE FACILITATED BY THE GROUP DISCUSSIONS IMPROVED JUDGES CALIBRATION , RAISING THE ACCURACY OF COMPETENCE WEIGHTED AGGREGATES ON SUBSEQUENT JUDGMENT PROBLEMS TO PREDICTION MARKET LEVELS AND BEYOND
207	DECISION ANALYSIS SOCIETY 
208	AN APPLICATION OF SMOOTH AMBIGUITY MODEL TO DETERMINE VALUE OF DATA
208	THE PERFORMANCE OF DATA DRIVEN OPTIMIZATION AND CLASSIFICATION PROTOCOLS TYPICALLY DEPENDS ON THE QUANTITY OF DATA AVAILABLE
208	WE USE THE SMOOTH AMBIGUITY MODEL TO PROVIDE A NEW QUANTIFICATION OF THIS PERFORMANCE
208	THIS QUANTIFICATION CAN HELP MANAGERS DETERMINE HOW MUCH DATA TO COLLECT
208	WE ILLUSTRATE THE APPLICATION OF THIS DEVELOPMENT IN AN INDUSTRY SETTING
208	DECISION ANALYSIS SOCIETY OUR MODEL VALUES THE DATA IN DATA DRIVEN OPTIMIZATION MODELS BASED ON DECISION MAKERS UTILITY 
209	DECISION MAKING AS CATEGORIZATION
209	HUMANS CAN MAKE QUICK DECISIONS IN COMPLEX ENVIRONMENTS
209	ONE POSSIBLE EXPLANATION IS THAT , HUMANS PERFORM RULE BASED DECISION MAKING BASED ON THE INFERRED CATEGORY OF THE CONTEXT , WHICH REDUCES TASK IRRELEVANT INFORMATION AND SUPPORTS POWERFUL GENERALIZATION TO DIFFERENT CONTEXTS
209	WE TRANSFORM COMMON DECISION MODELS , INCLUDING TYPICAL NORMATIVE AND DESCRIPTIVE MODELS , INTO CATEGORIZATION TASKS THAT DIRECTLY MAP CONTEXTUAL FEATURES TO DECISION OPTIONS
209	WE PROPOSE A CATEGORIZATION MODEL BASED ON A HIERARCHICAL MIXTURE OF PROBABILISTIC PRINCIPAL COMPONENTS THAT SIMULTANEOUSLY LEARN A PARSIMONIOUS SET OF CATEGORIES AND FEATURES
209	WE VALIDATE THE MODEL THROUGH SIMULATION AND LARGE SCALE BEHAVIORAL EXPERIMENTS
209	DECISION ANALYSIS SOCIETY WE WOULD LIKE TO STUDY HUMAN DECISION MAKING BEHAVIOR USING A DATA DRIVEN METHODS
210	A BAYESIAN NETWORK MODEL FOR EARLY DETECTION OF STUDENTS COURSE FAILURE
210	MOTIVATED BY THE NEED OF EARLY DETECTION OF STUDENTS COURSE FAILURE , WE PROPOSE A HIERARCHICAL BAYESIAN NETWORK MODEL WHICH CAN BE USED AS A SCREENING TOOL TO ASSESS THE IMMEDIATE PROBABILITY OF COURSE FAILURE FOR EACH STUDENT THROUGHOUT THE SEMESTER
210	THE MODEL TAKES INTO CONSIDERATION OF STUDENTS DEMOGRAPHIC INFORMATION , PREVIOUS ACADEMIC RECORDS , TARGET COURSE ATTENDANCE ENGAGEMENT , AND HAS DEMONSTRATED ITS EFFECTIVENESS ON THE UAH ACADEMIA YEAR DATA
210	WE ALSO CONDUCT THE FEATURE IMPORTANCE ANALYSIS , WHICH HELPS US BETTER UNDERSTAND THE MECHANISM OF THE STUDENTS COURSE FAILURE
210	DECISION ANALYSIS SOCIETY USING REAL DATA TO HELP INSTRUCTORS BETTER UNDERSTAND AND DETECT THE POSSIBLE COURSE FAILURE 
211	A STUDY ON THE IMPROVEMENT TARGETS OF DATA ENVELOPMENT ANALYSIS MODELS
211	DEA IS A MATHEMATICAL PROGRAMMING METHODOLOGY FOR THE RELATIVE EFFICIENCY EVALUATION OF DECISION MAKING UNITS , DMUS , WITH MULTIPLE INPUTS AND OUTPUTS
211	BESIDES THE EFFICIENCY SCORE , DEA MODEL CAN PROVIDE AN IMPROVEMENT TARGET FOR EACH INEFFICIENT DMU TO ACHIEVE EFFICIENCY , WHICH IS THE ATTRACTIVE POINT OF DEA
211	THUS , THE IDEA OF LEAST DISTANCE DEA HAS BEEN PROPOSED FOR FINDING THE CLOSEST EFFICIENT TARGET THAT IS SIMILAR TO THE DMU UNDER EVALUATION AND CAN BE ACHIEVED EASILY
211	WE MAKE A COMPARISON BETWEEN IMPROVEMENT TARGETS PROVIDED BY THE CONVENTIONAL ADDITIVE , ADD , MODEL AND LEAST DISTANCE DEA MODEL USING A TIME SERIES DATA SET OF RETAIL BUSINESSES IN JAPAN
211	THE RESULTS OF NUMERICAL EXPERIMENTS SUGGESTS THE SUPERIORITY OF THE IMPROVEMENT TARGET PROVIDED BY THE LEAST DISTANCE DEA MODEL ON THE REALIZATION OF EFFICIENCY FOR THOSE INEFFICIENT DMUS
211	DECISION ANALYSIS SOCIETY 
212	COMBINING FORECASTS FROM MULTIPLE VARIABLES AND INFORMATION SOURCES UNDER CORRELATED FORECAST ERRORS
212	WE ADDRESS THE CHALLENGE OF COMBINING POINT FORECASTS FROM MULTIPLE VARIABLES AND EXPERTS TO DRAW INFERENCE ABOUT AN UNKNOWN VARIABLE
212	WE MODEL THE FORECAST ERRORS AS A SUMMATION OF A VARIABLE SPECIFIC COMPONENT , AN EXPERT SPECIFIC COMPONENT , AND THE IDIOSYNCRATIC NOISE
212	WHEN THE COVARIANCE STRUCTURE OF THE FORECAST ERRORS IS KNOWN , WE SHOW THAT POOLING FORECASTS FROM OTHER VARIABLES IS ALWAYS BENEFICIAL COMPARED TO SEPARATE INFERENCE
212	THIS IS BECAUSE THE POOLED INFERENCE HELPS BETTER IDENTIFY GOOD EXPERTS FROM BAD ONES , AS IT IS STRUCTURALLY EQUIVALENT TO THE SEPARATE INFERENCE BUT WITH A SMALLER IDIOSYNCRATIC NOISE
212	HOWEVER , THE VALUE OF INFORMATION FROM POOLING IS ZERO WHEN EXPERTS ARE EXCHANGEABLE , NO NEED TO DIFFERENTIATE , , OR THERE IS NO IDIOSYNCRATIC NOISE , NO ROOM FOR IMPROVEMENT , 
212	WE EMPIRICALLY VALIDATE OUR THEORETICAL INSIGHTS
212	DECISION ANALYSIS SOCIETY 
213	EQUITY IN AN ONLINE MANAGEMENT SCIENCE COURSE
213	THIS TALK HYPOTHESIZES THAT STUDENT OUTCOMES IN AN ONLINE MANAGEMENT SCIENCE COURSE ARE RELATED TO THE QUALITY OF PREREQUISITE COURSEWORK
213	WE PRESENT EMPIRICAL RESULTS WITH RESPECT TO STUDENT PREPARATION AND TECHNOLOGY READINESS AND DEVELOP A MODEL OF THE RELATIONSHIP BETWEEN THESE VARIABLES AND COURSE PERFORMANCE
213	THE RESULTS INFORM INSTRUCTORS WITH RESPECT TO ACTIONS THAT THEY MAY TAKE TO ADDRESS STUDENT EQUITY
213	DIVERSITY , EQUITY , AND INCLUSION DATA DRIVEN INNOVATIONS IN OR EDUCATION INFORMS COMMITTEE ON TEACHING AND LEARNING AND EDUCATION OUTREACH
214	UNLEASHING THE POWER OF P C MODEL , A NOVEL APPROACH FORGES A BRIDGE BETWEEN MARKETING ANALYSIS AND STRATEGIC BUSINESS DECISIONS INTHE HEAVY MACHINERY INDUSTRY
214	THIS ARTICLE PRESENTS A GROUNDBREAKING APPROACH , THE P C MODEL , PRODUCT , PLACE , PERIOD , PREDICTION , COMPANY , CHART , COMPARISON , AND CLUSTERING DIMENSIONS , , TO ANALYZE SALES DATA OF HEAVY MACHINERY PRODUCTS IN THE UNITED STATES
214	BY EMBRACING A MULTIDIMENSIONAL PERSPECTIVE , THIS NOVEL METHODOLOGY ENABLES A METICULOUS AND ALL ENCOMPASSING EXAMINATION OF THE MARKET , UNVEILING CRUCIAL TRENDS AND PATTERNS THAT MAY ELUDE CONVENTIONAL APPROACHES
214	FURTHERMORE , THROUGH THE DETAILED EXPLORATION OF ESSENTIAL DATA COLLECTION AND ANALYSIS ASPECTS SUCH AS PRODUCT , PLACE , PERIOD , PREDICTION , COMPANY , CHART , COMPARISON , AND CLUSTERING , THE MODEL ACCURATELY SHEDS LIGHT ON AREAS RIPE FOR DATA COLLECTION AND DATA DRIVEN IMPROVEMENT
214	THIS INNOVATIVE APPROACH OFFERS INSIGHTS FOR BUSINESSES AND ORGANIZATIONS , EMPOWERING THEM TO MAKE WELL INFORMED DECISIONS
214	DIVERSITY , EQUITY , AND INCLUSION EMERGING TECHNOLOGIES AND APPLICATIONS BEHAVIORAL OPERATIONS MANAGEMENT , OR MS , IS HIGHLY RELEVANT TO THE P C MODEL AND ITS APPLICATION IN ANALYZING HEAVY MACHINERY SALES 
215	UNMASKING THE SOCIAL CAPITAL GAP , INVESTIGATING GENDER DISPARITIES IN THE BOARDROOMS OF CANADIAN PUBLIC FIRMS
215	DESPITE EFFORTS TO INCREASE GENDER DIVERSITY ON CORPORATE BOARDS , OUR STUDY REVEALS THAT FEMALE DIRECTORS IN CANADIAN PUBLIC FIRMS POSSESS A LARGER SOCIAL NETWORK THAN THEIR MALE COUNTERPARTS OVER THE PAST TWO DECADES
215	THIS SUGGESTS THAT GENDER DIVERSITY DOES NOT AUTOMATICALLY EQUALIZE OPPORTUNITIES
215	WE COLLECTED DATA ON DIRECTORS CAREER PATHS , EDUCATION , AND SOCIAL ENGAGEMENT TO UNDERSTAND THE ROLE OF SOCIAL CAPITAL IN THEIR APPOINTMENTS AND IDENTIFIED BARRIERS WOMEN FACE
215	OUR RESEARCH AIMS TO INFORM POLICIES THAT ADDRESS THESE BARRIERS , PROMOTING A TRULY INCLUSIVE CORPORATE ENVIRONMENT
215	DIVERSITY , EQUITY , AND INCLUSION FINANCE DATA , OR , AND SOCIAL JUSTICE
216	PORTFOLIO DIVERSIFICATION BASED ON TRADIND STRATEGIES
216	RAISING INVESTED NUMBER IS EFFICIENT IN DECREASING PORTFOLIO RISK
216	STUDIES HAVE CONSIDERED A NAIVE PORTFOLIO , WHICH INVESTS STOCKS EQUALLY , OR SHANNON AND YAGER S ENTROPY TO INCREASE THE INVESTMENT NUMBER OF PORTFOLIOS
216	HOWEVER , STUDIES HAVE UNDERESTIMATED THE IMPORTANCE OF FEATURED STOCKS WHILE CONSTRUCTING A PORTFOLIO WITH DIVERSIFICATION
216	WE SHOULD ENFORCE PROFITABLE STOCKS INSTEAD OF ALL THE ALTERNATIVES , EVEN THOUGH INCREASING INVESTMENT IS CRUCIAL FOR LOWER PORTFOLIO RISK
216	THUS , THIS STUDY PROPOSES A DIVERSIFIED PORTFOLIO BASED ON MIXING BENCHMARK PORTFOLIO MODELS AND TRADING STRATEGIES , SUCH AS MOMENTUM AND REVERSAL
216	WE APPLY A PARAMETRIC POLICY TO BETTER MIX THE BENCHMARK PORTFOLIO AND TRADING STRATEGIES AS A CONVEX PROBLEM
216	DIVERSITY , EQUITY , AND INCLUSION FINANCE 
217	MODELING THE RELATIONSHIP BETWEEN SOCIAL DIVERSITY AND ORGANIZATIONAL DECISION MAKING ON OPEN COLLABORATIONS IN INFORMATION SYSTEMS
217	CONTEMPORARY WORK IS OFTEN BASED ON THE OPEN COLLABORATION MODEL AS OBSERVED IN SOFTWARE DEVELOPMENT
217	TRANSPARENCY OF , AND ACCESS TO , INFORMATION SYSTEMS ENABLES WIDESPREAD PARTICIPATION IN THE DEVELOPMENT OF SOFTWARE
217	AT THE SAME TIME , LOW SOCIAL DIVERSITY IN THESE ECOSYSTEMS HAS IMPLICATIONS FOR SOFTWARE AND SOCIETY
217	COMBINING DATA ANALYTICS WITH SURVEY RESEARCH FOR A MIXED METHODS APPROACH , WE USE SYSTEMS THEORY TO STUDY OPEN SOURCE DEVELOPERS DECISION MAKING
217	OUR GOAL IS TO ELUCIDATE THE RELATIONSHIP BETWEEN INDIVIDUAL , COLLECTIVE , AND SOCIETAL FACTORS THAT AFFECT SOCIAL DIVERSITY IN SOFTWARE PROJECTS MAINTAINED BY ORGANIZATIONS AND ONLINE COLLECTIVES
217	WE DISCUSS HOW DISPARITIES DRIVE THE DIRECTION OF TECHNOLOGICAL INNOVATIONS AND EXPLORE THE PROMISES AND PITFALLS OF ORGANIZATIONAL DECISIONS ON ACHIEVING SOCIAL DIVERSITY IN OPEN INFORMATION SYSTEMS
217	DIVERSITY , EQUITY , AND INCLUSION INFORMATION SYSTEMS DATA MINING
217	IN MY TALK , I WILL DESCRIBE RESEARCH WHICH LEVERAGES BIG DATA ANALYTICS TO MODEL INFORMATION SYSTEMS 
218	FOUNDER DIVERSITY , THE KEY TO UNLOCKING A DIVERSE TECH FIRM WORKFORCE
218	OUR STUDY INVESTIGATES HOW FOUNDER GENDER AND ETHNICITY IMPACT HIGH TECH FIRM HIRING PREFERENCES REGARDING CANDIDATE GENDER AND ETHNICITY
218	WE ANALYZED A DATASET OF , JOB CANDIDATES AND , FIRMS FROM A HIGH TECH NETWORKING PLATFORM ACROSS THREE STAGES OF THE RECRUITMENT PROCESS , INITIAL CONTACT , CANDIDATE RESPONSE , AND SUCCESSFUL HIRE
218	THE RESULTS SHOW THAT FIRMS ARE MORE LIKELY TO CONTACT AND RECEIVE RESPONSES FROM FEMALE AND UNDERREPRESENTED MINORITY , URM , CANDIDATES WHEN THE FOUNDING TEAM HAS A HIGHER PROPORTION OF FEMALE OR URM FOUNDERS
218	OUR STUDY HIGHLIGHTS THE IMPRINTING INFLUENCE OF FOUNDER DEMOGRAPHICS ON RECRUITMENT OUTCOMES AND SUGGESTS THAT CREATING A FOUNDATION FOR SUSTAINED DIVERSITY WITHIN THE HIGH TECH WORKFORCE REQUIRES PROVIDING RESOURCES AND OPPORTUNITIES FOR FEMALE AND URM ENTREPRENEURS RIGHT FROM THE ONSET OF THE BUSINESS FORMATION
218	DIVERSITY , EQUITY , AND INCLUSION MSOM , TECHNOLOGY , INNOVATION AND ENTREPRENEURSHIP ARTIFICIAL INTELLIGENCE
219	POISONED APPLES , HOW PROJECT TEAM EXPERIENTIAL DIVERSITY IMPACTS PROJECT PERFORMANCE AND VOLUNTARY TURNOVER
219	EXPERIENTIAL DIVERSITY WITHIN A TEAM OFFERS VALUABLE LEARNING OPPORTUNITIES THAT CAN ENHANCE TEAM PERFORMANCE THROUGH ACCELERATED LEARNING
219	HOWEVER , LEARNING MAY ENHANCE THE VALUE OF THE TEAM MEMBERS TO POTENTIAL RECRUITERS IN THE JOB MARKET , LEADING TO A LOSS OF HUMAN CAPITAL ESPECIALLY FOR FIRMS OPERATING IN HIGHLY COMPETITIVE JOB MARKETS
219	TO INVESTIGATE THE POTENTIAL SIDE EFFECTS OF DIVERSITY , WE ANALYZE PROJECT TEAMS FROM A MULTINATIONAL CONSULTING AND IT SERVICES FIRM
219	OUR STUDY EXAMINES DIVERSITY IN CUSTOMER EXPERIENCE , CLIENT EXPERIENCE DIVERSITY , AND PRIOR COLLABORATIVE EXPERIENCE IN OTHER PROJECTS , CO WORKER EXPERIENCE DIVERSITY , 
219	OUR FINDINGS REVEAL THAT CLIENT EXPERIENCE DIVERSITY IMPROVES PERFORMANCE , WHILE BOTH CLIENT AND CO WORKER EXPERIENCE DIVERSITIES EXHIBIT AN INVERTED U SHAPED RELATIONSHIP WITH VOLUNTARY TURNOVER
219	DIVERSITY , EQUITY , AND INCLUSION SCHEDULING AND PROJECT MANAGEMENT 
220	MEASURING THE IMPACT OF LOGISTICS DEVELOPMENT IN CITIES
220	A SOCIAL SUSTAINABILITY APPROACH
220	THE DEVELOPMENT OF LOGISTICS INFRASTRUCTURE IN CITIES IS GROWING , INTENDING TO MEET THE EXPECTATIONS OF FAST DEMAND
220	IN THIS STUDY , WE MEASURE THE IMPACT OF LOGISTICS FACILITIES PROXIMITY TO URBAN AREAS FROM A SOCIAL SUSTAINABILITY APPROACH
220	WE MEASURE THE SOCIAL VULNERABILITY IN WAREHOUSE PERMITTING AREAS , ANALYZE THE QUALITY OF JOBS OVER TEN YEARS , AND MEASURE THE JOB CREATION NEAR FACILITIES BR RESULTS SHOW THAT WAREHOUSES ARE GENERALLY LOCATED IN VULNERABLE AREAS
220	WORKFORCE INDICATORS SHOW A RISE IN THE NUMBER OF JOBS IN MOST INDUSTRIES RELATED TO THE MOVEMENT OF GOODS BUT A LIMITED INCREASE IN YEARLY EARNINGS
220	FINALLY , THE NUMBER OF LOGISTICS JOBS NEAR LOGISTICS FACILITIES HAS NOT INCREASED SIGNIFICANTLY
220	RESULTS ARE EXPECTED TO INFORM FUTURE PLANNING FOR DELIVERY ACTIVITY AT CITYWIDE LEVELS AND RAISE AWARENESS OF LOGISTICS FACILITIES SOCIAL IMPACT BR DIVERSITY , EQUITY , AND INCLUSION SUPPLY CHAIN AND LOGISTICS IN PRACTICE TRANSPORTATION SCIENCE AND LOGISTICS , TSL , 
221	ENTREPRENEURIALISM AND THE ACCEPTANCE OF INEQUALITY , WHAT CAUSEDIT , WHAT KEEPS IT GOING , AND WHAT TO DO ABOUT IT I WE TAKE UP THOMAS PIKETTY S CHALLENGE TO UNCOVER THE IDEOLOGY THE UNDERPINS AND FACILITATES I I ACCEPTANCE OF THE INEQUALITY WE OBSERVE
221	WE CAPTURE AN EMERGENT ENTREPRENEURIAL IDEOLOGY THAT IS I I A NEW IDEOLOGY THE STABILIZES THE SOCIAL ORDER BY MAKING IT ACCEPTABLE AS TO WHO GARNERS THE BENEFITS I I OF AN ENTREPRENEURIAL SOCIETY AND HOLD OUT HOPE THAT WE ALL MIGHT SOMEDAY BE AN ENTREPRENEURIAL I I SUCCESS
221	THIS NEW ENTREPRENEURIAL IDEOLOGY EXPLAINS AND CREATES A JUSTIFICATION FOR SOCIAL I I INEQUALITY
221	ATTRIBUTING WEALTH TO INDIVIDUAL ACTIONS RATHER THAN PERSONAL ATTRIBUTES ESTABLISHES A I I NARRATIVE THAT MAKES IT MORE CHALLENGING TO ADDRESS THE SYSTEMIC FACTORS CONTRIBUTING TO INEQUALITY I I MOREOVER , SUGGESTING THAT THE DISADVANTAGED ARE RESPONSIBLE FOR THEIR FATE , BUT OUGHT TO TRY AGAIN T I I O SUCCEED , JUSTIFIES THE GROWING DIVIDE BETWEEN THE RICH AND THE POOR AND STABILIZES OUR I I SOCIAL ORDER I 
221	DIVERSITY , EQUITY , AND INCLUSION TECHNOLOGY , INNOVATION MANAGEMENT AND ENTREPRENEURSHIP PUBLIC SECTOR OR 
221	THIS REVOLUTION IS INCREASING AND EMBEDDING INEQUALITY 
222	DESIGNING AND PILOTING A SIRL EVALUATION APPROACH FOR PARTICIPATORY SYSTEMS MAPPING IN POLICY
222	PARTICIPATORY SYSTEMS MAPPING , PSM , MAKES CAUSAL RELATIONS BETWEEN SYSTEM ELEMENTS TO BETTER UNDERSTAND THEIR BEHAVIOURS
222	THEY ARE CLAIMED TO BE USEFUL IN DEALING WITH THE COMPLEXITY OF POLICY , SUPPORTING CROSS DOMAIN KNOWLEDGE SYNTHESIS OF STAKEHOLDERS RESULTING IN MEANINGFUL ENGAGEMENT , ME , WITH COMMUNITIES UNFAMILIAR WITH PSM
222	THE STUDY FOCUSES ON THE LACK OF A METHODOLOGY TO EVALUATE WHETHER PSMS IN POLICY PROJECTS LEAD TO ME
222	A FRAMEWORK OF CRITERIA IS USED TO EVALUATE ME IMPACT , SELECTIVITY INCLUSIVITY REFLEXIVITY LONGEVITY , SIRL , 
222	THE WORK TO DATE IN DEVELOPING SIRL SUGGESTS THAT TO BETTER EVALUATE CLAIMS THAT PSM INTEGRATES CONFLICTING STAKEHOLDER PERSPECTIVES BOUNDARIES THAT THEY CONTRIBUTE TO THE RESOLUTION OF OTHER SYSTEMIC ISSUES IN THE INTERVENTION , THE METHODOLOGY WILL BENEFIT FROM CLOSER INTEGRATION OF FEMINIST INCLUSIVE APPROACHES TO PSM
222	DIVERSITY , EQUITY , AND INCLUSION 
223	DIVERSITY , EQUITY , AND INCLUSION IN ORGANIZATION BEHAVIOR , DOMAIN , BIBLIOMETRIC ANALYSIS , AND FUTURE RESEARCH AGENDA
223	AS A POTENTIAL RESEARCH DOMAIN , DIVERSITY , EQUITY , AND INCLUSION , DEI , IN ORGANIZATIONAL BEHAVIOR CAPTURES NUMEROUS ATTENTION FROM BOTH ACADEMICS AND PRACTICE
223	DEI IS A COMPLEMENTARY TERM AND CONCEPT THAT REFER TO STRATEGIES AND PROCESSES THAT ENABLE ORGANIZATIONS TO BECOME MORE REFLECTIVE OF AND RESPONSIVE TO THE IDENTITIES , VALUES , AND EXPERIENCES OF IMPORTANT STAKEHOLDER GROUPS , JOHNSON AND CHICHIRAU , , GIVEN THE PRIOR STUDIES ON DEI , FOR INSTANCE , LI AND NAGAR , , , SHOWED THAT FIRMS HOLDING SAME SEX DOMESTIC PARTNERSHIP BENEFIT POLICIES IN THE UNITED STATES EARN A FOUR FACTOR ANNUALIZED EXCESS RETURN , ALPHA , OF APPROXIMATELY , BEATING OF ALL PROFESSIONAL MUTUAL FUND
223	DESPITE THESE VALUABLE CONTRIBUTIONS , THERE NEEDS A COMPREHENSIVE STATE OF KNOWLEDGE OF DEI IN ORGANIZATIONAL BEHAVIOR
223	THIS STUDY PROVIDES NUMEROUS CONTRIBUTIONS
223	DIVERSITY , EQUITY , AND INCLUSION 
224	BRAND EXPLORATION IN METAVERSE , EFFECTS OF USER AVATAR RESEMBLANCE ON ENGAGEMENT AND BRAND ATTITUDE
224	BRAND METAVERSE , WHICH REFERS TO THE BRAND IN A VIRTUAL WORLD , HAS BECOME AN IMPORTANT MEDIUM FOR BRANDS TO COMMUNICATE WITH CUSTOMERS
224	IN THIS STUDY , WE INVESTIGATE THE INFLUENCE OF USER AVATAR RESEMBLANCE ON BRAND METAVERSE ENGAGEMENT AND BRAND ATTITUDE
224	SPECIFICALLY , WE PROPOSE THAT USER AVATAR RESEMBLANCE AFFECTS BRAND ATTITUDE BY VIRTUE OF THE ENGAGEMENT WITH THE BRAND METAVERSE
224	FURTHERMORE , WE POSIT THAT COPRESENCE , THE SIMULTANEOUS PRESENCE OF MULTIPLE AVATARS IN THE BRAND METAVERSE , ACTS AS A MODERATOR THAT STRENGTHENS THE MEDIATION
224	WE CONDUCTED AN EXPERIMENT USING A FASHION BRAND S VIRTUAL WORLD IN A POPULAR METAVERSE PLATFORM
224	OUR HYPOTHESES WERE SUPPORTED FOR THE MAIN AND INTERACTION EFFECTS
224	THE FINDINGS PROVIDE MEANINGFUL IMPLICATIONS FOR MARKETING PRACTITIONERS WHO HAVE INTENTIONS TO IMPLEMENT METAVERSE MARKETING EBUSINESS BEHAVIORAL OPERATIONS MANAGEMENT EMERGING TECHNOLOGIES AND APPLICATIONS 
225	INVESTIGATING THE CONSUMERS PRE CONSUMPTION AND POST CONSUMPTION PERCEPTION IN ONLINE PRODUCT REVIEWS
225	ONLINE CONSUMER REVIEWS HAVE SUBSTANTIAL VALUE FOR BUSINESSES
225	HOWEVER , THE CONTENT AND LINGUISTIC CHARACTERISTICS OF ONLINE CONSUMER REVIEWS CAN BE AFFECTED BY THEIR PRE CONSUMPTION AND POST CONSUMPTION PERCEPTION AND THEIR MATCH OR MISMATCH BETWEEN THESE TWO PERCEPTIONS
225	THIS STUDY FOCUSES ON THIS ISSUE AND PROVIDES IMPLICATIONS FOR BUSINESSES TO UNDERSTAND THE IMPORTANCE OF CONSUMER PERCEPTION CHANGE REFLECTED IN ONLINE REVIEWS EBUSINESS DATA MINING SOCIAL MEDIA ANALYTICS
225	USING TEXT MINING TO SUPPORT BUSINESS DECISIONS FROM ONLINE REVIEWS 
226	UNMASKING THE DECEPTION , THE INTERPLAY BETWEEN FAKE REVIEWS , RATING DISPERSION , AND CONSUMER DEMAND
226	THIS STUDY EXPLORES THE INTERPLAY BETWEEN FAKE REVIEWS , RATING DISPERSION , AND CONSUMER DEMAND
226	USING RATING DISTRIBUTION ROUNDING INDUCED DISPERSION CHANGES AS AN IDENTIFICATION STRATEGY , WE FIND THAT RATING DISPERSION NEGATIVELY AFFECTS SALES
226	THEN , WE EXAMINE THE CONNECTION BETWEEN FAKE REVIEWS AND RATING DISPERSION USING AN OBSERVATIONAL STUDY
226	TO INVESTIGATE THE UNDERLYING MECHANISM , WE CONDUCT AN EXPERIMENT AND SHOW THAT INCREASED RATING DISPERSION RAISES CONCERNS ABOUT FAKE REVIEWS , IMPACTING CONSUMER DEMAND
226	WE INTRODUCE AN INFORMATION TREATMENT WARNING CONSUMERS ABOUT FAKE REVIEWS , AN INSTRUMENTAL VARIABLE , IV , , TO DETERMINE THE IMPACT OF CONSUMER SUSPICION OF FAKE REVIEWS ON THEIR DEMAND
226	CRUCIALLY , THE TREATMENT HAS A GREATER IMPACT ON SOCIALLY DISADVANTAGED GROUPS , INDICATING ITS POTENTIAL TO PROMOTE EQUITY IN THE ONLINE MARKETPLACE EBUSINESS DIVERSITY , EQUITY , AND INCLUSION 
226	THIS STUDY UTILIZES DATA ANALYSIS TECHNIQUES TO EXAMINE CONSUMER BEHAVIOR IN THE DIGITAL MARKETPLACE 
227	EFFORTS TO REGULATE ONLINE REVIEW MANIPULATION MAY BACKFIRE 
227	THE PREVALENCE OF REVIEW MANIPULATION DEMANDS THAT ONLINE PLATFORMS REGULATE REVIEWS BY DETECTING FAKE REVIEWS AND PUNISHING MANIPULATORS
227	USING A SIGNALING MODEL , THIS PAPER HIGHLIGHTS THAT REGULATIONS AIMED AT PREVENTING REVIEW MANIPULATION IN ONLINE PLATFORMS CAN HAVE UNINTENDED CONSEQUENCES OF DECREASING THE CREDIBILITY OF ONLINE REVIEWS AND HURTING CONSUMER WELFARE
227	THE UNDERLYING MECHANISM IS THAT COMPARED WITH LOW QUALITY SELLERS , HIGH QUALITY SELLERS LOSE MORE WHEN FOUND ENGAGING IN REVIEW MANIPULATION
227	THEREFORE , HIGH QUALITY SELLERS PAY MORE ATTENTION TO THE REGULATIONS AND CORRESPONDINGLY REDUCE MORE OF THEIR MANIPULATION
227	THIS WILL MAKE CONSUMERS MORE LIKELY TO SEE ONLINE REVIEWS PRAISING LOW QUALITY SELLERS , FURTHER REDUCING THE CREDIBILITY OF ONLINE REVIEWS AND HURTING CONSUMER WELFARE EBUSINESS EMERGING TECHNOLOGIES AND APPLICATIONS ARTIFICIAL INTELLIGENCE
227	MY PAPER ARGUES THAT IT IS NOT ALWAYS ADVISABLE TO HARNESS DATA TO IMPROVE PREDICTION PRECISION
228	MARKET GENOMICS , GENOMICS BIG DATA ON THE BLOCKCHAIN
228	THE GENOMIC DATA REVOLUTION REPRESENTS A MONUMENTAL PARADIGM SHIFT IN RESEARCH ON MARKETS AND CONSUMER BEHAVIOR
228	APPROXIMATELY OF HUMAN BEHAVIORAL TRAITS ARE DRIVEN BY GENOMICS , AND CAN POTENTIALLY BE PREDICTED AT BIRTH
228	HOWEVER , APPROXIMATELY YEARS OF MARKET RESEARCH HAS MOSTLY FOCUSED ON THE OTHER ADDITIONALLY , THE EFFECTS OF GENOMICS INCREASE , NOT DECREASE , OVER A PERSON S LIFETIME
228	IN THIS PAPER , THE AUTHORS INTRODUCE A NEW FIELD THAT THEY TERM , MARKET GENOMICS , THAT DELINEATES HOW GENOMIC BIG DATA CAN BE USED TO PREDICT MARKET BEHAVIOR AT BIRTH
228	GENOMIC BIG DATA CANNOT , HOWEVER , BE ETHICALLY OR PRACTICALLY USED WITHOUT THE BLOCKCHAIN
228	THE AUTHORS THUS PRESENT A THEORETICAL FRAMEWORK AND MODEL FOR GENOMIC BIG DATA ON THE BLOCKCHAIN
228	THE FRAMEWORK MAY SERVE AS A SEMINAL FOUNDATION FOR FUTURE RESEARCH , AND MAY STIMULATE A NEW FIELD OF RESEARCH ON MARKETS EBUSINESS EMERGING TECHNOLOGIES AND APPLICATIONS HEALTH APPLICATIONS SOCIETY
228	MY RESEARCH IS ON THE GENOMICS DATA REVOLUTION , SPECIFICALLY GENOMICS BIG DATA ON THE BLOCKCHAIN 
229	SUPPLY CHAIN STRATEGIES IN THE PRESENCE OF LIVESTREAM E COMMERCE , CHANNEL LEADERSHIP AND LOW CARBON PROMOTION
229	LIVESTREAM E COMMERCE IS AN EMERGING PHENOMENON , AND ITS IMPACTS ON SUPPLY CHAINS ARE LARGELY UNKNOWN
229	MOTIVATED BY THIS IMPORTANT GROWING MARKET , WE PROPOSE AN ANALYTICAL MODEL TO STUDY A DECENTRALIZED SUPPLY CHAIN WITH AN UPSTREAM MANUFACTURER , HE , SELLING HIS PRODUCT TO A DOWNSTREAM RETAILER , SHE , VIA A WHOLESALE PRICE CONTRACT
229	WE SOLVE THE EQUILIBRIUM SOLUTIONS UNDER BOTH THE TRADITIONAL E COMMERCE MODE AND THE LIVESTREAM MODE
229	OUR RESULTS SHOW THAT THE TRADITIONAL E COMMERCE MODE IS ALWAYS DOMINATED BY THE LIVESTREAM MODE SUCH THAT BOTH PARTIES ARE MORE PROFITABLE WHEN PARTICIPATING IN THE LIVESTREAM E COMMERCE
229	HOWEVER , WHEN THE WHOLESALE PRICE IS SUFFICIENTLY HIGH , THE LIVESTREAM E COMMERCE IS NO LONGER FEASIBLE FOR BOTH PARTIES SUCH THAT THE MARKET BECOMES MANUFACTURER MONOPOLISTIC EBUSINESS EMERGING TECHNOLOGIES AND APPLICATIONS MSOM , SUPPLY CHAIN
230	DIGITAL CONSUMPTION AND CONSUMER SELF CONTROL
230	THE HARMFUL EFFECTS OF DIGITAL OVER CONSUMPTION BECOME INCREASINGLY SEVERE
230	THE GOAL OF OUR RESEARCH IS TO ANALYTICALLY EXAMINE HOW CONSUMERS EXERCISE SELF CONTROL AND HOW FOR PROFIT FIRMS PRICING SCHEMES , SUBSCRIPTION VERSUS PAY PER USE , AND PRODUCT DESIGN STRATEGIES AFFECT THEIR PROFIT , CONSUMER SURPLUS , AND CONSUMERS LONG TERM HEALTH
230	OUR FINDINGS INDICATE THAT FIRMS PRICING SCHEMES AND THEIR IMPACT ON CONSUMERS LONG TERM WELL BEING ARE DEPENDENT ON CONSUMER CHARACTERISTICS AND THE NATURE OF PRODUCT CATEGORY BEING CONSUMED EBUSINESS INFORMATION SYSTEMS NEW PRODUCT DEVELOPMENT
231	THE WEB S GREAT CONVERSATION , UNVEILING THE SECRETS OF CHAT BASED SEARCH ENGINES
231	THIS STUDY EXAMINES THE SELECTION CRITERIA DIFFERENCES BETWEEN CHAT BASED SEARCH ENGINES AND THEIR TRADITIONAL COUNTERPARTS , USING A UNIQUE DATASET COMPILED FROM QUERIES ON NEW BING
231	THE ANALYSIS FOCUSES ON THE RESPONSES GENERATED BY BING CHAT AND REVEALS A TENDENCY TO SELECT MAINSTREAM WEBSITES FOR NUCLEUS SENTENCES AND NICHE WEBSITES FOR ELABORATION PARTS , SUGGESTING AN INCLINATION TOWARDS DIVERSE CONTENT
231	HOWEVER , FURTHER ANALYSES SHOW THAT BING CHAT FAVORS SPECIFIC LINGUISTIC STYLES , SUCH AS GREATER OBJECTIVITY , AND THAT THE SELECTED NICHE WEBSITES EXHIBIT CONSIDERABLE SIMILARITY , LIMITING THE DIVERSITY OF INFORMATION AVAILABLE TO USERS
231	THE FINDINGS HAVE IMPLICATIONS FOR BOTH USERS AND WEBSITE OWNERS AND HIGHLIGHT THE NEED FOR FURTHER RESEARCH ON CHAT BASED SEARCH ENGINES TO ENSURE THE PROVISION OF ACCURATE AND VARIED CONTENT EBUSINESS INFORMATION SYSTEMS SOCIAL MEDIA ANALYTICS
232	ANTI COUNTERFEIT STRATEGIES OVER E COMMERCE PLATFORMS
232	ONLINE SELLERS OFTEN SELL COUNTERFEIT PRODUCTS OVER E COMMERCE PLATFORMS
232	WE COMPARE SCENARIOS WHERE DIFFERENT PARTIES TAKE ACTIONS TO DETECT COUNTERFEITS AND PENALIZE THE SELLER
232	OUR RESEARCH REVEALS SOME INTERESTING MANAGERIAL INSIGHTS FOR THE PLATFORMS AND THE REGULATORS EBUSINESS MSOM , SERVICE OPERATIONS 
233	ONLINE RETAIL COMPETITION WITH REFERRAL SERVICES
233	WE INVESTIGATE WHETHER TWO COMPETING ONLINE RETAILERS CAN BE BETTER OFF BY ADOPTING REFERRAL SERVICES WE SHOW THAT THE PROPORTION OF STRONGLY LOYAL CONSUMERS OF THE REFERRAL OFFERING RETAILER AMONG ALL ITS , POTENTIAL , CONSUMERS MAINLY DETERMINES THE CHANCES THAT THE REFERRAL SERVICE WILL BE ADOPTED
233	OUR MAIN RESULT IS THAT WHEN THE MARKET SHARES OF BOTH RETAILERS DO NOT DIFFER SIGNIFICANTLY , A REFERRAL SERVICE IS LIKELY TO BE ADOPTED
233	FURTHERMORE , AS THE DEGREE OF LOYALTY AND THE NUMBER OF COMPARISON CONSUMERS INCREASE , THE REFERRAL SERVICE IS MORE LIKELY TO BE ADOPTED EBUSINESS MSOM , SERVICE OPERATIONS 
234	PLATFORM S PRIVATE LABEL AND INFORMATION SHARING STRATEGY WITH PLATFORM S DIVERSION
234	E COMMERCE GIANTS LIKE AMAZON BUILD PRIVATE LABEL PRODUCTS WHILE PROMOTING THEM THROUGH THEIR RECOMMEND SYSTEMS
234	WE BUILD A SUPPLY CHAIN WITH ONE BRAND NAME SUPPLIER AND AN E COMMERCE PLATFORM WITH UNCERTAIN DEMAND POTENTIAL
234	WE STUDY THE PLATFORM S ENCROACHMENT STRATEGY WITH DIFFERENT SEARCH NEUTRALITIES AND THE OPTIMAL INFORMATION SHARING AGREEMENT STRATEGY
234	WE SHOW THAT THE PLATFORM S ENCROACHMENT WILL WEAKEN THE DOUBLE MARGINALIZATION EFFECT IN SELLING BRAND NAME PRODUCTS
234	MOREOVER , WHEN MORE FLOW IS ALLOCATED TO THE BRAND NAME PRODUCTS , THE SUPPLIER AND PLATFORM WILL BENEFIT FROM THE PLATFORM S ENCROACHMENT
234	WE ALSO EXPLORE THE INTERACTION BETWEEN THE INFORMATION SHARING AGREEMENT AND THE PLATFORM S ENCROACHMENT AND FIND THAT THE FORMER ACTION WILL INDUCE THE LATTER , AND INCREASE THE PROBABILITY THAT THE SUPPLIER SUFFERS FROM ENCROACHMENT EBUSINESS MSOM , SUPPLY CHAIN INFORMATION SYSTEMS
234	THE PLATFORM CAN ADJUST THE SEARCH NEUTRALITY TO RECOMMEND THE PRIVATE LABEL PRODUCTS 
235	ANTICIPATORY PACKING
235	IN THIS PAPER , WE STUDY A NOVEL PRACTICE TERMED ANTICIPATORY PACKING , WHICH IS TO PREPARE SOME PACKAGES IN NON PEAK PERIODS TO BE USED FOR FULFILLING ORDERS IN THE SUBSEQUENT PEAK PERIODS
235	SPECIFICALLY , THE PREPARATION INVOLVES THE OPERATION OF PICKING SOME ITEMS AND PUTTING THEM IN THE SAME CUSTOMER BIN BUT MAY NOT INVOLVE ACTUAL PACKAGING
235	FOR EFFECTIVE ANTICIPATORY PACKING , WE DEVELOP A SAMPLE AVERAGE APPROXIMATION , SAA , MODEL BY USING THE ORDER DATA OF RECENT DAYS AND THEN DESIGN AN EFFECTIVE APPROXIMATION ALGORITHM TO SOLVE IT
235	WE INVESTIGATE THE EFFECTIVENESS OF ANTICIPATORY PACKING AND THE SAA MODEL WITH EXTENSIVE EXPERIMENTS
235	ON A REAL DATA SET , WE SHOW THAT ANTICIPATORY PACKING CAN YIELD AN SIGNIFICANT OPERATIONAL COST REDUCTION EBUSINESS OPT , INTEGER AND DISCRETE OPTIMIZATION TRANSPORTATION SCIENCE AND LOGISTICS , TSL , 
235	OUR APPROACH TO THE PROBLEM TAKES THE DATA AS INPUT AND DIRECTLY COMPUTES THE SOLUTION
236	IN STORE PRODUCT PLANNING OF MULTICHANNEL RETAILER WITH PRODUCT FIT UNCERTAINTY AND COMPETITION
236	WE ADDRESS THE PROBLEM OF IN STORE ASSORTMENT PLANNING , SERVICE LEVEL DETERMINATION AND PRICING WHEN THE PRODUCT FIT IS UNCERTAIN , AND THE MULTICHANNEL RETAILER FACES COMPETITION
236	THE CONSUMERS DECIDE WHETHER TO PURCHASE BASED ON ONLINE INFORMATION OR VISIT THE STORE FOR VERIFICATION , WITH UNCERTAIN PRODUCT AVAILABILITY IN STORE EBUSINESS REVENUE MANAGEMENT AND PRICING 
237	EXAMINING CROWDSOURCED DELIVERYMEN S EXPLORATION BEHAVIOR IN THE ONLINE TO OFFLINE CONTEXT
237	ONLINE TO OFFLINE , O O , PLATFORMS HAVE EMERGED AND HAVE HAD FAST GROWTH RECENTLY
237	THE FULFILLMENT PERFORMANCE OF THE O O MODE LARGELY DEPENDS ON THE DELIVERYMEN , MOST OF WHICH ARE CROWDSOURCED
237	THIS STUDY EXAMINES THE DELIVERYMEN S PERFORMANCE FROM THEIR EXPLORATION BEHAVIOR PERSPECTIVE AND FINDS THE CONSEQUENCE OF THEIR EXPLORATION BEHAVIOR
237	WE PROVIDE IMPLICATIONS FOR DELIVERYMEN AND O O PLATFORMS TO ENHANCE THEIR OPERATIONAL EFFICIENCY EBUSINESS SERVICE SCIENCE DECISION ANALYSIS SOCIETY
237	THIS STUDY USES MANAGEMENT SCIENCE TECHNICS TO ANALYZE THE DATA IN O O CONTEXT 
238	THIRD PARTY PROVIDERS IN FOOD AND GROCERY DELIVERY SERVICE
238	E COMMERCE HAS GROWN RAPIDLY
238	DURING THE PANDEMIC , CONSUMERS INCREASINGLY TURNED TO E COMMERCE FOR ALL THEIR NEEDS , INCLUDING FOOD AND GROCERY
238	LEADING RETAILERS HAS CHANGED THE TRADITIONAL RETAILING MODELS , ALONG WITH THE REMARKABLE GROWTH , TO ACHIEVE FAST FULFILLMENT AND DELIVERY
238	OMNI CHANNEL RETAILERS PROVIDE DIFFERENT WAYS TO PROCESS AND FULFILL CONSUMER ORDERS , BUT ONE OF THE BIGGEST CHALLENGES AND EXPENSES IS LAST MILE , OR FINAL MILE DELIVERY
238	A STRATEGIC DECISION MODEL BETWEEN SELF OWN DELIVERY OR THIRD PARTY PROVIDERS IS ESTABLISHED BY FORECASTING DEMAND AND THE EXPENSE OF DELIVERY AND QUICK RESPONSE TO CUSTOMER ORDERS TO OPTIMIZE COST CUT OF RETAILERS AND ORDER FULFILLMENT PERFORMANCE EBUSINESS SHARING ECONOMY , INNOVATIVE MARKETPLACES , AND DATA SUPPLY CHAIN AND LOGISTICS IN PRACTICE
239	RIDE THE WAVE OR NOT
239	THE SPILLOVER EFFECT OF ONLINE SHOPPING FESTIVALS AND BEST TIMING FOR ADVERTISING
239	THIS WORK EXPLORES THE SPILLOVER EFFECT OF ONLINE SHOPPING FESTIVALS ON SHORT VIDEO ADVERTISING THROUGH A NATURAL EXPERIMENT
239	ONLINE SHOPPING FESTIVAL HAS A SPILLOVER EFFECT ON SHORT VIDEO ADVERTISING AND THE EFFECT CHANGES OVER TIME
239	IT IS POSITIVE IN THE WARM UP AND GENERAL PROMOTION PERIODS , AND BECOMES NEGATIVE IN THE PEAK PROMOTION AND POST PROMOTION PERIODS OF THE FESTIVAL
239	WE PROPOSE THREE MECHANISMS TO EXPLAIN THE POSITIVE EFFECT , I E , FESTIVAL S ENVIRONMENTAL CUES , AND THE NEGATIVE EFFECTS , I E , DIMINISHING MARGINAL UTILITY AND FINANCIAL CONSTRAINTS OF CONSUMERS , 
239	WE CONDUCT A FIELD EXPERIMENT , SEVERAL SURVEYS , AND USE SOME MODEL FREE EVIDENCE TO VERIFY THE EXISTENCE OF THESE MECHANISMS
239	THE RESULTS SUGGEST FIRMS MAY RIDE THE WAVE OF EXOGENOUS FESTIVALS , BUT SHALL CAREFULLY CHOOSE THE BEST TIMING FOR THEIR ADVERTISING EBUSINESS SOCIAL MEDIA ANALYTICS 
240	THE ROLE OF LIVE STREAMING COMMERCE IN DUAL CHANNEL SUPPLY CHAIN
240	LIVE STREAMING SHOPPING HAS BECOME A SIGNIFICANT SALES FORCE AND IT ALLOWS VIEWERS TO WATCH AND SHOP THROUGH REAL TIME INTERACTIONS OVER THE PHONE
240	WE INVESTIGATE HOW A SUPPLIER RESPONDS TO THE FAST GROWING LIVE STREAMING COMMERCE
240	WE EXAMINE MULTIPLE CENTRALIZED SETTINGS WHEN A SUPPLIER BUILDS HIS OWN LIVE STREAMING TEAMS AND HOSTS LIVE SESSIONS
240	WE ALSO DESIGN A TWO STAGE GAME TO FORMULATE ONE DECENTRALIZED CASE THAT THE SUPPLIER OFFERS A REVENUE SHARING CONTRACT AND SELLS PRODUCTS THROUGH A KEY OPINION LEADER S STREAM
240	OUR RESULTS SHOW THAT THE SUPPLIER AND THE KEY OPINION LEADERS MAY BE DISCOURAGED COMPARED WITH THE CENTRALIZED MODELS , WHICH MIGHT DECREASE THE SUPPLIER S EXPECTED PROFIT EVENTUALLY EBUSINESS SOCIAL MEDIA ANALYTICS 
241	A HIERARCHICAL EFFECTS MODEL ON CONSUMERS USE OF ONLINE REVIEW INFORMATION
241	THIS RESEARCH INVESTIGATES CONSUMERS USE OF ONLINE REVIEW INFORMATION AND THE HIERARCHICAL EFFECTS OF DIFFERENT DIMENSIONS OF REVIEW INFORMATION ON CONSUMERS DECISION MAKING PROCESS
241	SPECIFICALLY , A MODEL IS PROPOSED SUGGESTING THAT CONSUMERS USE A THRESHOLD TO DECIDE WHICH DIMENSION OF REVIEW INFORMATION TO EXPLORE NEXT , AND IF THE AVERAGE RATING FALLS BELOW THE THRESHOLD , THEY MAY EITHER RESEARCH A DIFFERENT PRODUCT OR LOOK AT THE NUMBER OF REVIEWERS AND EXAMINE THE ACTUAL REVIEWS AT A MORE SPECIFIC LEVEL EBUSINESS 
242	HOW DOES OFFLINE SUPERSTORE OPENING AFFECT NEARBY CONSUMERS ONLINE MARKET BASKETS
242	WE EMPIRICALLY EXAMINE HOW AN OFFLINE STORE ENTRY AFFECTS ONLINE CONSUMER S PURCHASE BEHAVIOR
242	OUR ANALYSES SHOW THAT ONLINE CONSUMERS MARKET BASKETS SUBSTANTIALLY CHANGE WHEN AN OFFLINE STORE OPENS
242	WE FIND THAT DIFFERENT CONSUMER SEGMENTS , OCCASIONAL VERSUS HEAVY CONSUMERS AND RISK AVERSE VERSUS RISK LOVING CONSUMERS , RESPOND DIFFERENTLY TO A STORE ENTRY , AND THAT THE DOMINANT STORE ENTRY EFFECTS ARE DETERMINED BY PRODUCT TYPES , TANGIBLE VERSUS INTANGIBLE AND LOW VERSUS HIGH PRICED PRODUCTS , 
242	OUR RESULTS ALSO SHOW THAT , , THE FINAL DIRECTION OF SUPERSTORE ENTRY EFFECTS DEPENDS ON CONSUMER SEGMENTS RATHER THAN PRODUCT TYPES , , , WHEN A PRE EXISTING SUPERSTORE EXISTS , THE NUMBER OF ITEMS PURCHASED ONLINE IS NOT AFFECTED BY A NEW SUPERSTORE ENTRY , , , THE DECREASED NUMBER OF ITEMS PURCHASED ONLINE DECREASES EVEN AFTER MONTHS EBUSINESS 
243	THE EFFECT OF IDENTITY MULTIPLICITY SIGNALING ON INTERPERSONAL TRUST
243	THIS RESEARCH INVESTIGATES HOW AND WHY SIGNALING MULTIPLE IDENTITIES , VS A SINGLE IDENTITY , INFLUENCES INTERPERSONAL TRUST
243	SIX STUDIES INCLUDING A ﬁELD EXPERIMENT , ANALYSIS OF SOCIAL MEDIA DATA , AND LAB AND ONLINE EXPERIMENTS DEMONSTRATE THAT IDENTITY MULTIPLICITY SIGNALING FOSTERS INTERPERSONAL TRUST BY PROMOTING PERCEIVED AUTHENTICITY
243	WE REPLICATE THIS FINDING ACROSS STUDIES WITH VARIOUS MEASURES AND DESIGNS
243	WE ALSO SHOW THAT THE EFFECT OF IDENTITY MULTIPLICITY IS ATTENUATED WHEN THE IDENTITY SIGNALING MESSAGE IS PRESENTED TOGETHER WITH MONETARY EXCHANGE MENTIONS AS A CUE THAT SUGGESTS LACK OF AUTHENTICITY
243	TAKEN TOGETHER , THE RESULTS ADVANCE THE UNDERSTANDING OF THE MULTIFACETED NATURE OF IDENTITY AND ITS SOCIAL COGNITIVE CONSEQUENCES IN CONTEXTS SUCH AS , ONLINE , COMMUNICATION , COLLABORATION , AND PERSUASION EBUSINESS 
244	ENHANCING VISIT INTENTION THROUGH SERVICE ROBOTS IN THE HOSPITALITY INDUSTRY , ROLE OF ANTHROPOMORPHISM , PERCEIVED WARMTH AND WOM
244	THIS STUDY ENHANCES RESEARCH INTO THE SERVICE ROBOT APPLICATION IN THE HOSPITALITY SECTOR BY PRESENTING RESEARCH PROPOSALS WITH AN INTEGRATED FRAMEWORK FOR UNDERSTANDING HOW THE HOSPITALITY INDUSTRY MIGHT USE AND PROFIT FROM SERVICE ROBOTS
244	THIS ARTICLE EXAMINES THE ROLES OF ANTHROPOMORPHISM , PERCEIVED WARMTH , TECHNOLOGICAL READINESS , AND WOM TO BETTER UNDERSTAND THE IMPACT ON VISIT INTENTION
244	EMERGING TECHNOLOGIES AND APPLICATIONS ARTIFICIAL INTELLIGENCE SERVICE SCIENCE 
245	BLOCKCHAIN BASED TOKENIZED DIGITAL VERIFICATION OF GRADE CARD CERTIFICATES , A MULTI STAKEHOLDER APPROACH
245	FOR VERIFICATION OF GRADE CARD CERTIFICATES ISSUED BY INDIAN GOVERNMENT BODIES OR UNIVERSITIES , A HIRING ORGANIZATION NEEDS TO CONTACT THE SOURCE ORGANIZATION
245	THIS INTRODUCES DELAYS IN THE VERIFICATION PROCESS AND MAY ALSO INTRODUCE HUMAN ERROR WHILE INSERTING MARKS INTO A DATABASE
245	TO ADDRESS THIS PROBLEM , THIS PAPER DISCUSSES A MULTI STAKEHOLDER PLATFORM FOR DIGITAL VERIFICATION OF GRADE CARDS AND CERTIFICATES BY THE ORIGINATING BODY OR UNIVERSITY WHICH ACTS AS THE VALIDATOR
245	OCR CAPTURES VITAL INFORMATION FROM THE DOCUMENT UPLOADED BY A CANDIDATE
245	AFTER BLOCKCHAIN BASED TOKENIZED VALIDATION FROM THE SOURCE ORGANIZATION , THE UPLOADED DOCUMENT WITH ITS VITAL DETAILS ARE SAVED ON THE WEB BASED PLATFORM
245	THIS VERIFIED DOCUMENT IS NOW ACCESSIBLE TO ALL CONCURRENT AND FUTURE STAKEHOLDERS THE POSSIBILITY OF FRAUD IS ALSO ADDRESSED DUE TO DIRECT VALIDATION BY SOURCE
245	EMERGING TECHNOLOGIES AND APPLICATIONS DATA DRIVEN INNOVATIONS IN OR EDUCATION NEW PRODUCT DEVELOPMENT
245	THIS WORK DISCUSSES MANAGING THE DATA INTENSIVE CERTIFICATE VERIFICATION PROCESS FOR INDIA 
246	TRADE OFFS BETWEEN BUILDING IN HOUSE LIVESTREAMING TEAMS AND OUTSOURCING TO INFLUENCERS
246	LIVESTREAMING E COMMERCE HAS BECOME INCREASINGLY POPULAR AMONG BRAND MANUFACTURERS , WHO CAN EITHER BUILD IN HOUSE TEAMS OR OUTSOURCE TO INFLUENCERS TO CONDUCT LIVESTREAMING SALES
246	IN THIS PAPER , WE USE A GAME THEORETIC MODEL TO ANALYZE THE TRADE OFFS BETWEEN THESE TWO APPROACHES
246	IN THE MODEL WE CONSIDER TWO PLAYERS , THE BRAND MANUFACTURER AND THE INFLUENCER
246	BUILDING AN IN HOUSE TEAM PROVIDES BETTER CONTROL OVER BRAND IMAGE AND INFORMATION FLOW , BUT COMES AT THE COST OF HIGH FIXED COSTS
246	OUTSOURCING TO INFLUENCERS MAY LEAD TO FASTER MARKET ENTRY DUE TO THEIR HIGHER TRAFFIC , BUT AT THE RISK OF LOSING CONTROL OVER BRAND IMAGE
246	OUR ANALYSIS PROVIDES INSIGHTS INTO THE FACTORS THAT BRAND MANUFACTURERS SHOULD CONSIDER WHEN DECIDING BETWEEN BUILDING IN HOUSE LIVESTREAMING TEAMS AND OUTSOURCING TO INFLUENCERS
246	EMERGING TECHNOLOGIES AND APPLICATIONS EBUSINESS 
247	LIVE STREAM PLATFORM STRATEGIES , DRIVE TRAFFIC OR NOT
247	LIVE STREAM , WITH ITS DIVERSE CONTENT AND REAL TIME INTERACTION WITH THE AUDIENCE , HAS BECOME A POWERFUL MEANS OF BOOSTING ONLINE TRAFFIC
247	IN ORDER TO BENEFIT FROM THE MASSIVE TRAFFIC , LIVE STREAM PLATFORMS HAVE BEGUN TO ENCOURAGE LIVE PROMOTIONS DRIVING POTENTIAL CONSUMERS TO TRADITIONAL E COMMERCE PLATFORMS , WHILE ATTEMPTING TO INCORPORATE E COMMERCE FEATURES INTO THEMSELVES
247	WE DEVELOP A STYLIZED MODEL CONSISTING OF A THIRD PARTY SELLER , A LIVE STREAM PLATFORM AND A TRADITIONAL E COMMERCE PLATFORM TO INVESTIGATE THEIR STRATEGIC INTERACTIONS , AND CONSUMER S SWITCHING BEHAVIOR BETWEEN TRADITIONAL AND LIVE STREAM CHANNELS
247	WE SHARE MANAGERIAL INSIGHTS IN LIVE STREAM PLATFORM DESIGN , AND CHANNEL STRATEGIES FOR THIRD PARTY SELLERS
247	EMERGING TECHNOLOGIES AND APPLICATIONS EBUSINESS 
248	COGNITIVE DIGITAL TWINS FOR SUPPLY CHAIN RESILIENCE ENHANCEMENT
248	GIVEN THE ADVERSE IMPACT OF LOCAL AND GLOBAL CRISES ON GLOBAL SUPPLY CHAINS , BUILDING RESILIENCY IS VITAL TO MITIGATE SUCH ADVERSE IMPACTS
248	THEREFORE , A COGNITIVE DIGITAL SUPPLY CHAIN TWIN IS DEVELOPED TO ENHANCE SUPPLY CHAIN RESILIENCE THROUGH IMPROVED DECISION MAKING SUPPORT , DRIVEN BY THE GROWING DIGITAL TRANSFORMATION EFFORTS
248	THE COGNITIVE DIGITAL TWIN ADOPTS A SET OF MACHINE LEARNING BASED MODULES , ENABLING DISRUPTION DETECTION , DISRUPTED COMPONENT IDENTIFICATION , DISRUPTION DURATION PREDICTION , AND TIME TO RECOVERY PREDICTION
248	ADDITIONALLY , A DISRUPTION EXTRAPOLATION MODULE IS DEVELOPED TO PREDICT THE FUTURE SUPPLY CHAIN PERFORMANCE TRAJECTORY UNDER A DISRUPTIVE EVENT AND TEST RECOVERY ACTIONS
248	OBTAINED INFORMATION FROM THE COGNITIVE DIGITAL TWIN HELPS DECISION MAKERS MAKE APPROPRIATE DECISIONS BASED ON REAL TIME DISRUPTION DETECTION DATA
248	EMERGING TECHNOLOGIES AND APPLICATIONS MACHINE LEARNING IN OPERATIONS SIMULATION SOCIETY
248	THE DEVELOPED COGNITIVE DIGITAL SUPPLY CHAIN TWIN IS UTILIZES DATA DRIVEN MODELS FOR DISRUPTION DETE 
249	FREEMIUM DESIGN , WHAT IS THE OPTIMAL DIFFERENTIATION MODEL OF THE CONTENT PLATFORM
249	WE DEVELOP AN ANALYTICAL MODEL TO EXPLORE THE OPTIMAL FREEMIUM STRATEGY FOR A MONOPOLISTIC CONTENT PLATFORM
249	WE IDENTIFY THREE COMMON STRATEGIES FOR RELEASING FREEMIUM , DIFFERENTIATION ONLY BY CONTENT , OC MODEL , , DIFFERENTIATION ONLY BY ADVERTISING , OA MODEL , , AND DIFFERENTIATION BY BOTH CONTENT AND ADVERTISING , CA MODEL , 
249	EMERGING TECHNOLOGIES AND APPLICATIONS SHARING ECONOMY , INNOVATIVE MARKETPLACES , AND DATA TECHNOLOGY , INNOVATION MANAGEMENT AND ENTREPRENEURSHIP
250	VAR IS WATCHING YOU , THE INTRODUCTION OF VIDEO ASSISTANT REFEREE AND PLAYER MISCONDUCTS
250	THIS STUDY INVESTIGATES THE INFLUENCE OF VIDEO ASSISTANT REFEREE , VAR , USAGE ON PLAYER MISCONDUCT DURING FOOTBALL MATCHES , SPECIFICALLY EXPLORING ITS EFFECTS ON RED AND YELLOW CARDS , FOULS COMMITTED , AND PLAYER INJURIES
250	USING STAGGERED DID , THE FINDINGS INDICATE A SIGNIFICANT DECREASE IN YELLOW CARDS , FOULS , AND INJURIES SUBSEQUENT TO THE INTRODUCTION OF VAR
250	INTERESTINGLY , THE RESEARCH UNCOVERS A COMPLEX INTERPLAY BETWEEN THE EFFECTIVENESS OF VAR AND THE INTENSITY OF MATCHES , WITH ITS IMPACT DIMINISHING IN HIGHLY COMPETITIVE ENCOUNTERS
250	IT REVEALS THE BEHAVIORAL ALTERATIONS ADOPTED BY PLAYERS UNDER VAR SCRUTINY , RESULTING IN A REDUCTION OF INAPPROPRIATE BEHAVIORS
250	MOREOVER , THE STUDY HIGHLIGHTS THE LIMITED IMPACT OF VAR WHEN PLAYERS ARE FULLY ENGROSSED IN THE GAME , UNRAVELING THE INTRICACIES OF ITS ROLE IN FOOTBALL
250	EMERGING TECHNOLOGIES AND APPLICATIONS SPORTS TECHNOLOGY , INNOVATION MANAGEMENT AND ENTREPRENEURSHIP
251	THE ECONOMICS AND OPTIMAL DESIGN OF INDOOR FARMING SUPPLY CHAINS
251	INDOOR FARMING IS ONE OF THE FASTEST GROWING INDUSTRIES IN THE U S ITS PROJECTED COMPOUND ANNUAL GROWTH RATE AVERAGES MORE THAN BETWEEN AND ALTHOUGH INDOOR FARMING HAS WELL KNOWN ADVANTAGES OVER TRADITIONAL FARMING , THE HIGH INITIAL TECHNOLOGY AND SETUP INVESTMENTS PLUS OPERATING COSTS RELATED TO PRODUCTION , PACKAGING , DISTRIBUTION CAN OUTWEIGH THE BENEFITS
251	IN THIS PRESENTATION , I WILL TALK ABOUT THE NEED FOR ECONOMICS STUDY AND SUSTAINABILITY OF INDOOR FARMING STARTUPS
251	AN OPTIMIZATION MODEL WILL BE PRESENTED TO DEMONSTRATE HOW THE USE OF DATA AND MATHEMATICAL PROGRAMMING CAN PROVIDE VALUABLE DATA DRIVEN DECISION SUPPORT FOR THE OPTIMAL DESIGN AND OPERATION OF AN END TO END INDOOR FARMING SUPPLY CHAIN
251	EMERGING TECHNOLOGIES AND APPLICATIONS SUPPLY CHAIN AND LOGISTICS IN PRACTICE 
252	FACTORS AFFECTING THE RESISTANCE TO ADOPT METAVERSE PLATFORM
252	METAVERSE REFERS TO AN IMMERSIVE AND INTERACTIVE DIGITAL WORLD , WHERE USERS ENGAGE IN VARIOUS ACTIVITIES
252	AS THE COMPANIES SUCH AS META HAVE PROMOTED THE METAVERSE PLATFORMS , THE METAVERSE TECHNOLOGY BECAME MATURED ENOUGH
252	HOWEVER , MANY RESEARCHES ON METAVERSE ADOPTION POINTED THAT PUBLICS ACCEPTANCE IS FAR BEHIND THE BUSINESS EXPECTATION WE IDENTIFIED THE FACTORS OF THE PUBLICS RESISTANCE OF METAVERSE USING AN INTEGRATED MODEL BASED ON THE INNOVATION RESISTANCE THEORY AND TECHNOLOGY ACCEPTANCE MODEL
252	THE DATA WERE COLLECTED THROUGH A SURVEY FROM NON ADOPTERS OF METAVERSE IN SOUTH KOREA
252	SMARTPLS WAS USED TO REVEAL THE BARRIER FACTORS THAT LEAD TO RESIST AGAINST THE PLATFORM
252	THE FINDINGS WILL BE FURTHER DISCUSSED IN THE CONFERENCE
252	EMERGING TECHNOLOGIES AND APPLICATIONS TECHNOLOGY , INNOVATION MANAGEMENT AND ENTREPRENEURSHIP 
253	THE QUANTUM TORTOISE AND THE CLASSICAL HARE , WHICH PROBLEMS WILL QUANTUM COMPUTING ACCELERATE
253	QUANTUM COMPUTING PROMISES TRANSFORMATIONAL GAINS FOR SOLVING SOME PROBLEMS , BUT LITTLE TO NONE FOR OTHERS
253	FOR FIRMS HOPING TO USE QUANTUM COMPUTERS NOW OR IN THE FUTURE , IT IS IMPORTANT TO KNOW WHICH PROBLEMS WILL BENEFIT
253	IN THIS PAPER , WE ANSWER THIS QUESTION BY ANALYZING THE RELATIVE STRENGTHS OF CLASSICAL AND QUANTUM COMPUTERS
253	THIS ANALYSIS THEN PROVIDES INSIGHTS FOR WHICH TYPES OF PROBLEMS FACED BY BUSINESSES WILL BENEFIT FROM QUANTUM AND WHICH WILL NOT
253	EMERGING TECHNOLOGIES AND APPLICATIONS TECHNOLOGY , INNOVATION MANAGEMENT AND ENTREPRENEURSHIP 
253	QUANTUM IS ONE OF THE NEXT GEN TOOLS PROMISING TO ANSWER BIG DATA QUESTIONS
254	DISTRIBUTED COOPERATIVE TRAJECTORY AND LANE CHANGING OPTIMIZATION OF CONNECTED AUTOMATED VEHICLES , MERGE AND DIVERGE SEGMENTS
254	MERGE AND DIVERGE SEGMENTS CAN CREATE BOTTLENECKS DUE TO THE CONSIDERABLE NUMBER OF MANDATORY AND DISCRETIONARY LANE CHANGES
254	THIS STUDY INTRODUCES A VEHICLE LEVEL MIXED INTEGER MODEL TO CONTROL LONGITUDINAL AND LATERAL MOVEMENTS OF CONNECTED AUTOMATED VEHICLES , CAVS , , PROVIDE A SMOOTH FLOW OF TRAFFIC , INCREASE CAPACITY , AND AVOID CONGESTION
254	TO ENSURE THE FEASIBILITY OF VEHICLE LEVEL DECISIONS AND PROMOTE SYSTEM LEVEL OPTIMALITY , A COOPERATIVE DISTRIBUTED ALGORITHM IS ESTABLISHED
254	AS A RESULT , CAVS COORDINATE THEIR DECISIONS TO FIND THE OPTIMAL LONGITUDINAL AND LATERAL MANEUVERS THAT AVOID COLLISIONS AMONG ALL VEHICLES
254	THE PROPOSED COORDINATION SCHEME LETS CAVS FIND THEIR OPTIMAL TRAJECTORIES BASED ON PREDICTIVE INFORMATION , I E , FUTURE LOCATIONS AND SPEEDS , FROM SURROUNDING VEHICLES AND COORDINATE THEIR LANE CHANGING DECISIONS
254	EMERGING TECHNOLOGIES AND APPLICATIONS TRANSPORTATION SCIENCE AND LOGISTICS , TSL , TSL , INTELLIGENT TRANSPORTATION SYSTEMS
255	BIUXX
255	A CLOUD BASED ENTERPRISE RESOURCE PLANNING , ERP , SYSTEM OFFERS ORGANIZATIONS WITH INTEGRATED SOFTWARE TO MANAGE THE ORGANIZATION OPERATIONS AND FINANCIAL INFORMATION
255	IT ALSO PROVIDES ACCESS TO BUSINESS INFORMATION FROM ANY CONNECTED DEVICE IN REAL TIME
255	HOWEVER , THE LACK OF STRATEGY IN IMPLEMENTING CLOUD BASED ERP IN GOVERNMENT ORGANIZATIONS CAN CAUSE A FAILURE IN THE EFFICIENCY AND PERFORMANCE OF THE ORGANIZATION
255	THE SUDAN CIVIL AVIATION AUTHORITY , SCAA , , A UNIQUE LARGE GOVERNMENT ORGANIZATION THAT REGULATES THE AVIATION SECTOR IN SUDAN , HAS FAILED TO FULLY IMPLEMENT CLOUD ERP
255	THIS LEADS TO THE CESSATION OF AUTOMATION OPERATIONS RESULTING IN A LACK OF INTEGRATED INFORMATION SYSTEMS , WEAKNESSES IN RISK ASSESSMENT , AND INEFFICIENCY IN INTEGRATING CROSS FUNCTIONAL INTERACTIONS
255	THEREFORE , THIS STUDY AIMS TO INVESTIGATE THE IMPLEMENTATION OF AN ERP SYSTEM IN THE AVIATION INDUSTRY AND DEVELOP A MODEL FOR SUCCESSFULLY IMPLEMENTING CLOUD ERP IN THE CIVIL AVIATION AUTHORITY OF SUDAN
255	THIS STUDY USES DE LONE MCLEAN S UPDATED MODEL OF SUCCESSFUL IS IMPLEMENTATION
255	TWO DIMENSIONS FROM THE MODEL , WHICH ARE SYSTEM QUALITY AND SERVICE QUALITY , ARE USED IN THIS STUDY
255	IN ADDITION , TWO OTHER DIMENSIONS , PROCESS QUALITY AND SUPPORT QUALITY , ARE TAKEN FROM THE PREVIOUS LITERATURE
255	THESE ARE IMPORTANT TO FORM A COMPREHENSIVE HYPOTHESIS FOR INVESTIGATION AT THE ORGANIZATIONAL LEVEL
255	THIS RESEARCH USES A QUANTITATIVE APPROACH BY CONDUCTING A SURVEY USING A QUESTIONNAIRE AS AN INSTRUMENT TO COLLECT DATA FROM THE TARGET POPULATION IN SCAA , WHICH HAS MANY SUBORDINATES
255	THE RESULTS OF THIS RESEARCH ARE EXPECTED TO SHOW A THEORETICAL AND PRACTICAL APPROACH TOWARD THE SUCCESSFUL IMPLEMENTATION OF CLOUD ERP IN SCAA AND OTHER AVIATION INDUSTRIES
255	EMERGING TECHNOLOGIES AND APPLICATIONS 
256	THE IMPACT OF BLOCKCHAIN ON PROFIT AND WASTE IN FOOD SUPPLY CHAINS
256	FOOD SUPPLY CHAINS CAN INCUR SIGNIFICANT WASTE DUE TO DIFFERENT QUALITY STANDARDS ADOPTED BY SUPPLY CHAIN MEMBERS
256	IN THIS PAPER , WE INVESTIGATE THE IMPACT OF BLOCKCHAIN TECHNOLOGY ON FOOD WASTE AND PROFITABILITY IN A SUPPLY CHAIN WITH ONE SUPPLIER AND ONE RETAILER
256	WE FIND THAT ADOPTING BLOCKCHAIN TECHNOLOGY ALWAYS IMPROVES THE SUPPLIER S PROFIT BUT CAN HURT THE RETAILER S AND THE SUPPLY CHAIN S PROFITABILITY
256	WE ALSO FIND THAT WHEN THE SUPPLIER S QUALITY STANDARD IS VERY HIGH , THE IMPLEMENTATION OF BLOCKCHAIN IS MORE LIKELY TO REDUCE THE WASTE IN THE SUPPLY CHAIN
256	EMERGING TECHNOLOGIES AND APPLICATIONS 
257	CHATBOT PERSUASION , AN ELABORATION LIKELIHOOD MODEL PERSPECTIVE 
257	CONVERSATIONAL AGENTS , CAS , ARE AI ENABLED PROGRAMS ENGAGING IN CONVERSATIONS AND INTERACTIONS WITH HUMANS
257	WHILE SIMPLE RULE BASED CAS PRIMARILY ASSIST USERS WITH PREDEFINED QUERIES AND INFORMATION RETRIEVAL , MORE ADVANCED CAS CAN UNDERSTAND USER INTENTIONS , AND EXHIBIT EMOTIONS , PERSONALITY TRAITS , AND EMPATHY
257	RECENTLY , THERE HAS BEEN A GROWING INTEREST IN UTILIZING CAS TO INFLUENCE USERS ATTITUDES , BELIEFS , AND BEHAVIOURS , SUCH AS AI COUNSELORS AND AI COACHES
257	RECOGNIZING THIS TREND , WE PROPOSE A LABORATORY EXPERIMENT DESIGN UNDER THE ELABORATION LIKELIHOOD MODEL AND THE SOCIAL RESPONSE THEORY , TO COMPARE THE PERSUASION EFFECTIVENESS OF A CHATBOT AND A WEBSITE WITHOUT THE INTERACTIVE CONVERSATIONAL CAPABILITY
257	EMERGING TECHNOLOGIES AND APPLICATIONS 
258	AN ECONOMIC ANALYSIS OF BILLBOARD DIGITIZATION IN TIMELY MARKETING
258	WITH THE DEVELOPMENT OF IT , MANY BILLBOARD OWNERS ARE DIGITIZING THEIR BILLBOARDS
258	TRADITIONAL BILLBOARD OWNERS HAVE TO PAINT ADVERTISEMENTS ON THEIR BILLBOARDS , WHICH IS COSTLY
258	THUS , BILLBOARD ADVERTISING IS NOT A SUITABLE CHOICE FOR TIMELY MARKETING , WHOSE ADVERTISING CAMPAIGNS USUALLY LAST FOR A SHORT TERM
258	AFTER DIGITIZING THE BILLBOARD USING THE LED SCREEN AND AUTOMATIC CONTROL SYSTEMS , BILLBOARD OWNERS CAN CHANGE THE ADVERTISEMENT CONTENT EASILY
258	THIS INCREASES THE POPULARITY OF USING BILLBOARDS FOR TIMELY MARKETING
258	IN THIS STUDY , WE ANALYZE HOW THE DIGITIZATION OF BILLBOARDS AFFECTS THE TIMELY MARKETING INDUSTRY , SUCH AS HOW IT AFFECTS THE PAYOFFS OF ADVERTISERS WITH TIMELY MARKETING CAMPAIGNS
258	EMERGING TECHNOLOGIES AND APPLICATIONS 
259	THE PARADOXICAL EFFECTS OF ALGORITHMIC HUMAN RESOURCE MANAGEMENT
259	THE QUESTIONS ABOUT WHAT INFLUENCE ALGORITHMIC HRM WOULD PRODUCE ARE PROMPTED WITH THE WIDESPREAD ADOPTION OF ALGORITHMIC TECHNOLOGIES IN HRM PRACTICES
259	THE FINDINGS ON THE ACTUAL CONSEQUENCES OF SUCH USE ARE MIXED
259	DRAWING ON THE TECHNOLOGY AFFORDANCE THEORY , WE SYSTEMATICALLY ANALYZED THE EFFECTS OF ALGORITHMIC HRM BASED ON ITS TECHNOLOGY AFFORDANCES , I E , COMPREHENSIVE , INSTANTANEOUS , INTERACTIVE AND OPAQUE , FROM A PARADOXICAL PERSPECTIVE
259	WE FIND THAT ALGORITHMIC HRM EXERT CONTROL IN THE WORKPLACE THROUGH TWO MECHANISM , WHICH WE RE CONSTRUCTED AS ENABLING CONTROL BY AUGMENTING EMPLOYEES TO IMPROVE THEIR WORK ABILITY AND ENCLOSING CONTROL BY PROVIDING RESTRAINS AND SOCIAL STRUCTURES TO LIMIT PEOPLE S WORK IN THE ORGANIZATIONS
259	WE ALSO CONCLUDE THIS PAPER WITH THE PROVIDING AVENUES FOR FUTURE RESEARCH
259	EMERGING TECHNOLOGIES AND APPLICATIONS THE DIGITAL TRANSFORMATION IN HRM AND THE BIG DATA FROM HRM ARE IMPORTANT PARTS IN MS 
260	CONDITION BASED MAINTENANCE FOR WIND FARMS USING A DISTRIBUTIONALLY ROBUST CHANCE CONSTRAINED PROGRAM
260	EXISTING CONDITION BASED MAINTENANCE , CBM , STRATEGIES FOR WIND FARMS RELY ON THE ASSUMPTION THAT PROGNOSTIC ALGORITHMS CAN ACCURATELY PREDICT WIND TURBINES REMAINING LIFETIME DISTRIBUTION , RLD , , ALLOWING FOR THE IMPLEMENTATION OF STOCHASTIC PROGRAMMING OR SIMULATION BASED OPTIMIZATION METHODS
260	HOWEVER , THIS ASSUMPTION MIGHT NOT HOLD IN PRACTICE
260	THIS TALK ADDRESSES THIS ISSUE BY PRESENTING A NEW CBM STRATEGY FOR WIND FARMS THAT USES A DISTRIBUTIONALLY ROBUST CHANCE CONSTRAINED , DRCC , OPTIMIZATION MODEL
260	THIS FORMULATION ACKNOWLEDGES THAT ESTIMATED DISTRIBUTIONS MAY BE INCORRECT AND SEEKS ROBUST SOLUTIONS AGAINST DISTRIBUTION FLUCTUATIONS
260	WE SHOW THAT THE DRCC OPTIMIZATION PROBLEM CAN BE REFORMULATED AS AN INTEGER LINEAR PROGRAM
260	THE STRATEGY IS VALIDATED THROUGH COMPUTATIONAL STUDIES USING SYNTHETIC AND REAL WORLD DEGRADATION DATA
260	ENERGY , NATURAL RESOURCES AND THE ENVIRONMENT , ENRE , ENRE , ENERGY OPT , OPTIMIZATION UNDER UNCERTAINTY
261	A BEHAVIORAL SCIENCE CENTRIC UNDERSTANDING OF ENERGY LIMITING BEHAVIOR
261	ENERGY LIMITING BEHAVIOR ARISES FROM A HOUSEHOLD S INABILITY OR UNWILLINGNESS TO CONSUME A SAFE AND HEALTHY LEVEL OF ENERGY
261	THE LOW INCOME HOME ENERGY ASSISTANCE PROGRAM , LIHEAP , IS DESIGNED TO FINANCIALLY ASSIST ENERGY POOR HOUSEHOLDS , BUT THERE EXIST GAPS IN UNDERSTANDING THE EFFECTIVENESS OF LIHEAP AS AN INTERVENTION MECHANISM
261	WE PROPOSE A BEHAVIORAL SCIENCE CENTRIC STUDY TO UNDERSTAND PEOPLE S ENERGY USE PREFERENCES IN ENERGY LIMITING CONDITIONS AND EXAMINE WHETHER LIHEAP IS EFFECTIVE
261	USING A REGRESSION MODEL AND HOUSEHOLD ENERGY USE DATA , INDIVIDUAL PRIORITIES FOR ENERGY USE IN ENERGY LIMITING CONDITIONS ARE REVEALED
261	IN CONTRAST , STATED PREFERENCES OF LIHEAP PARTICIPANTS SHOWS HOW MUCH EXTRA HOUSEHOLD ENERGY COULD BE USED IF THEY HAD EXPANDED BUDGETS
261	THESE TWO JOINT METHODS PROVIDE A HOLISTIC VIEW OF ENERGY LIMITING BEHAVIOR AND LIHEAP EFFECTIVENESS
261	ENERGY , NATURAL RESOURCES AND THE ENVIRONMENT , ENRE , ENRE , ENERGY 
261	WE USE ENERGY USE DATA FROM UTILITIES TO UNDERSTAND ENERGY LIMITING BEHAVIOR 
262	DESIGN OF LOGISTICS INFRASTRUCTURE IN SUPPORT OF NAVAL OPERATIONS WITH USE OF AMMONIA BASED FUEL
262	ONE OF THE U S NAVY S ENERGY GOALS IS TO DEMONSTRATE AND THEN DEPLOY A GREAT GREEN FLEET , WHICH WILL INCLUDE SHIPS AND AIRCRAFT USING ALTERNATIVE SOURCES OF ENERGY
262	ONE SUCH ENERGY SOURCE IS AMMONIA
262	A CHALLENGE WITH SWITCHING TO USING AMMONIA FOR FUEL IS REDUCED RANGE
262	THIS STUDY AIMS TO ASSESS THE VIABILITY OF UTILIZING AMMONIA AS FUEL TO SUPPORT NAVAL OPERATIONS
262	TO THIS END , A MIXED INTEGER NON LINEAR PROGRAMMING MODEL IS DEVELOPED TO DETERMINE SHIP ROUTES TAKING INTO ACCOUNT FACTORS SUCH AS SHIP SPEEDS , REFUELING TIME , AND THE NON LINEAR RELATIONSHIP BETWEEN FUEL CONSUMPTION AND THE SHIP S SPEED
262	THE OBJECTIVE OF THE MODEL IS TO MINIMIZE COST
262	TO SOLVE THIS MODEL , A PARTICLE SWARM OPTIMIZATION BASED ALGORITHM IS DEVELOPED
262	PRELIMINARY RESULTS FROM SEVERAL HYPOTHETICAL FUEL LOGISTICS SCENARIOS ARE PRESENTED
262	ENERGY , NATURAL RESOURCES AND THE ENVIRONMENT , ENRE , ENRE , ENVIRONMENT AND SUSTAINABILITY DATA , OR , AND SOCIAL JUSTICE
263	DOES SMART CITIES IMPROVE CARBON EMISSION EFFICIENCY
263	EVIDENCE FROM CHINA
263	CITIES ARE FACED WITH THE CHALLENGE OF BALANCING ECONOMIC DEVELOPMENT WITH CARBON REDUCTION , AND SMART CITY CONSTRUCTION PROVIDES A PROMISING SOLUTION
263	THIS PAPER TAKES THE CHINA SMART CITY PILOT POLICY AS A QUASI NATURAL EXPERIMENT , AND EMPIRICALLY TESTS THE EFFECTS OF SMART CITIES ON CARBON EMISSION EFFICIENCY , CEE , USING A DIFFERENCE IN DIFFERENCES METHOD
263	WE FIND THAT SMART CITIES HAVE SIGNIFICANTLY IMPROVED CEE , AND THE MECHANISM ANALYSIS INDICATES THAT SMART CITIES CONTRIBUTE TO IMPROVEMENT OF CEE BY ADVANCING TECHNOLOGICAL INNOVATION , OPTIMIZING INDUSTRIAL STRUCTURE , AND ENHANCING RESOURCE ALLOCATION
263	THE SPATIAL EFFECT DEMONSTRATES THAT THE CONSTRUCTION OF SMART CITIES HAS A SIGNIFICANT SPILLOVER EFFECT ON CEE , WHICH CAN PROMOTE CEE IN THE SURROUNDING CITIES
263	ENERGY , NATURAL RESOURCES AND THE ENVIRONMENT , ENRE , ENRE , ENVIRONMENT AND SUSTAINABILITY ENRE , ENERGY CLIMATE
264	IMPACTS OF BUILDING SECTOR GHG LIMITING ORDINANCES ON LONG TERM INVESTMENT DECISIONS CONSIDERING POLICY UNCERTAINTY
264	SEVERAL CITIES IN THE U S HAVE ENACTED GHG LIMITING ORDINANCES TO REDUCE ON SITE BUILDING SECTOR EMISSIONS
264	HOWEVER , ANALYSES OF THE ORDINANCES LONG TERM IMPACTS ON NATURAL GAS AND POWER SYSTEM INFRASTRUCTURE INVESTMENT ARE MISSING FROM THE LITERATURE
264	IN THIS STUDY , WE EXTEND THE U S EPA S CITY BASED OPTIMIZATION MODEL FOR ENERGY TECHNOLOGY TO MODEL LONG TERM MINIMUM COST ENERGY AND BUILDING SECTOR INVESTMENT DECISIONS OF NYC S GHG LIMITING ORDINANCE
264	OUR RESULTS SHOW THAT THE COST OPTIMAL INVESTMENT DECISIONS DEPEND SIGNIFICANTLY ON THE INCLUSION OF NECESSARY SYSTEM UPGRADES SUCH AS NATURAL GAS MAIN REPLACEMENTS AND FUTURE COSTS OF CLEAN NATURAL GAS SUBSTITUTES
264	ENERGY , NATURAL RESOURCES AND THE ENVIRONMENT , ENRE , ENRE , ENVIRONMENT AND SUSTAINABILITY ENRE , ENERGY CLIMATE
265	RESTORATION OF FOREST LINEAR DISTURBANCES FROM OIL AND GAS EXPLORATION , HOW CAN NETWORK MODELS HELP
265	WE PROPOSE A TWO TIER NETWORK OPTIMIZATION MODEL FOR RESTORATION OF LINEAR FOREST DISTURBANCES IN AREAS OF OIL AND GAS EXTRACTION
265	THE MODEL DELINEATES A CONTIGUOUS SET OF COARSE SCALE REGIONS FOR RESTORATION AND THEN USES THIS SOLUTION TO WARM START A FINE SCALE FOREST PATCH LEVEL NETWORK OPTIMIZATION MODEL THAT ALLOCATES RESTORATION ACTIVITIES TO MAXIMIZING THE ACCESS OF WILDLIFE SPECIES TO UNDISTURBED HABITAT , MAINTAIN HUMAN ACCESS TO UNRESTORED SITES AND KEEP RESTORATION IN MEANINGFUL CLUSTERS
265	WE APPLIED THE APPROACH TO DEVELOP FOREST RESTORATION SCENARIOS IN THE RED ROCK CARIBOU RANGE IN THE NORTHWESTERN ALBERTA , CANADA
265	ENERGY , NATURAL RESOURCES AND THE ENVIRONMENT , ENRE , ENRE , ENVIRONMENT AND SUSTAINABILITY ENRE , NATURAL RESOURCES
266	IMPACT ANALYSIS OF ENVIRONMENTAL POLICIES ON LINER SHIP FLEET PLANNING UNDER DEMAND UNCERTAINTY
266	CONSIDERATIONS TO DECARBONIZE MARITIME SHIPPING BY IMPLEMENTING THE EMISSIONS TRADING SYSTEM , ETS , ARE UNDERWAY AT THE INTERNATIONAL MARITIME ORGANIZATION , IMO , 
266	WE PROPOSE A FLEET PLANNING MODEL ACCOUNTING FOR CARBON EMISSIONS TO EVALUATE THE DECISION MAKING NUANCES OF A LINER COMPANY TO INVESTIGATE THE SHORT TERM IMPACT OF THE ETS
266	NUMERICAL EXPERIMENTS ARE CONDUCTED ON VARIOUS PROPOSED POLICY DESIGN PARAMETERS
266	OUR FINDINGS INDICATE THAT , FOR LINER SHIPPING WHICH IS CROSS REGIONAL BY NATURE , REGIONAL ETS IMPLEMENTATIONS ARE INADEQUATE DUE TO CARBON LEAKAGE , OPEN ETS POLICIES HAVE LIMITED EFFICACY , PARTICULARLY WHEN CARBON PRICES ARE LOW , STRICT CARBON PURCHASE CAPS INTEGRATED WITH ROBUST CARBON PRICE SETTING MECHANISMS ARE CRITICAL TO DESIGNING AN EFFECTIVE ETS
266	ENERGY , NATURAL RESOURCES AND THE ENVIRONMENT , ENRE , ENRE , ENVIRONMENT AND SUSTAINABILITY TSL , FREIGHT TRANSPORTATION
267	OPTIMIZING LIGNIN VALORIZATION IN BIOREFINERY SYSTEMS WITH BIOLOGICAL UPGRADING , ASSESSING ECONOMIC VIABILITY AND UNCERTAINTY ANALYSIS
267	WE STUDY THE ECONOMIC OPTIMIZATION OF LIGNIN VALORIZATION WITH BIOLOGICAL UPGRADING IN BIOREFINERY SYSTEM
267	USING A SUPERSTRUCTURE BASED PROCESS OPTIMIZATION METHOD , WE IDENTIFY THE OPTIMAL PATHWAY AND ASSESS THE IMPACT OF PARAMETERS SUCH AS FEEDSTOCK AND PRODUCTION COSTS , BIOPRODUCT PRICE , AND PROCESS YIELD THROUGH UNCERTAINTY ANALYSIS
267	THE DETERMINISTIC CASE REVEALS THE OPTIMAL PROCESS INVOLVES USING HERBACEOUS PLANTS AS FEEDSTOCK , UNDERGOING BASE CATALYZED DEPOLYMERIZATION , RESULTING A MAXIMUM NET PRESENT VALUE OF MILLION AND INTERNAL RATE OF RETURN UNCERTAINTY ANALYSIS VIA STOCHASTIC PROGRAMMING DEMONSTRATES THAT THE OPTIMAL STRATEGY DEPENDS SIGNIFICANTLY ON ECONOMIC SCENARIOS
267	OUR FINDINGS LAY THE GROUNDWORK FOR DEVELOPING LIGNIN VALORIZATION BIOREFINERIES , FURTHERING CLIMATE CHANGE MITIGATION AND CIRCULAR ECONOMY EFFORTS
267	ENERGY , NATURAL RESOURCES AND THE ENVIRONMENT , ENRE , ENRE , NATURAL RESOURCES EMERGING TECHNOLOGIES AND APPLICATIONS 
268	ASSESSING THE RESILIENCE OF SUPPLY CHAINS TO CLIMATE CHANGE , BUILDING A CLIMATE RESILIENT SUPPLY CHAIN AND ENHANCING COMPETITIVENESS
268	THIS STUDY INVESTIGATES THE RELATIONSHIP BETWEEN CLIMATE HAZARDS , BUSINESS RISK EXPOSURE , SUPPLY CHAIN SUSCEPTIBILITY , DISRUPTION IMPACT , RESILIENCE , AND RESPONSE CAPACITY
268	THE STUDY AIMS TO PROVIDE A BETTER UNDERSTANDING OF HOW FIRMS CAN IMPROVE THEIR SUPPLY CHAIN RESILIENCE IN THE FACE OF INCREASING CLIMATE HAZARDS AND BUSINESS RISK EXPOSURE
268	DATA FROM A SUPPLY CHAIN VISIBILITY FIRM , RESILINC , FROM VARIOUS INDUSTRIES WILL BE USED TO TEST THE HYPOTHESES
268	THE STUDY S FINDINGS WILL BE RELEVANT FOR MANAGERS AND POLICYMAKERS SEEKING TO STRENGTHEN SUPPLY CHAIN RESILIENCE IN THE FACE OF DISRUPTIVE EVENTS
268	ENERGY , NATURAL RESOURCES AND THE ENVIRONMENT , ENRE , 
269	BOOSTING EFFICIENCY IN POWER SYSTEM STATE ESTIMATION LEVERAGING ATTENTION MECHANISM
269	ENSURING STABILITY IN POWER SYSTEMS REQUIRES ACCURATE STATE ESTIMATION , WHICH IS CHALLENGING DUE TO THE PRESENCE OF NOISE IN MEASUREMENTS , NONLINEARITY OF POWER FLOW EQUATIONS AND POTENTIAL FALSE DATA INJECTIONS
269	WE INTRODUCE THE GRAPH ATTENTION ESTIMATION NETWORK , GAEN , MODEL FOR POWER SYSTEM STATE ESTIMATION , WHICH LEVERAGES THE GRAPH STRUCTURE OF POWER GRIDS FOR EFFICIENT INFORMATION EXCHANGE , DISTRIBUTED ARCHITECTURE , AND RESILIENCE TO CYBER ATTACKS
269	USING GRAPH CONVOLUTIONAL NEURAL NETWORKS , GCNNS , AND ATTENTION MECHANISMS , WE ADDRESS THE LIMITATIONS OF PREVIOUS ARCHITECTURES
269	EMPIRICAL RESULTS SHOW SUPERIOR PERFORMANCE , SCALABILITY , AND HEIGHTENED EFFICACY COMPARED TO TRADITIONAL TECHNIQUES
269	THIS WORK ADVANCES THE INTEGRATION OF LEARNING ARCHITECTURES IN POWER SYSTEM STATE ESTIMATION , FOSTERING RELIABLE AND SECURE POWER NETWORKS I 
269	ENRE , ELECTRICITY ARTIFICIAL INTELLIGENCE OPT , MACHINE LEARNING
269	OUR METHODS USES DATA COLLECTED FROM THE POWER GRID TO COME UP WITH THE BEST ESTIMATE OF THE STATE 
270	PRICE PASS THROUGH AND COST BURDEN INDUCED BY DECARBONIZATION POLICIES CONSIDERING LONG TERM CAPACITY EXPANSION AND SHORT TERM GRID OPERATION
270	THE IMPACT OF CARBON COST ON ELECTRICITY SUPPLY AND CARBON PASS THROUGH REQUIRES A SIMULATION THAT INTEGRATE CO SUB SUB EMISSION TRADING AND ELECTRICITY SUPPLY AND DISPATCH INTO A CONTINUOUS PROCEDURE
270	THIS STUDY LINKS AGENT BASED MODEL WITH SWITCH MODEL THAT INVOLVES ELECTRICITY SUPPLY , TRANSMISSION AND LOAD CENTERS , AND ESTIMATES THE CARBON PASS THROUGH RATES OF DIFFERENT REGIONS
270	THE RESULTS SHOW THAT A HIGH CARBON PASS THROUGH RATES IS CLOSELY RELATED TO LOCAL ELECTRICITY SUPPLY AND INTERREGIONAL POWER DISPATCH
270	THE MIX SCENARIO THAT SIMULTANEOUSLY CONSIDERS CO SUB SUB EMISSION TRADING , CET , AND RENEWABLE ELECTRICITY TARGET , RET , SHOWS THE SYNERGISTIC EFFECT OF TWO POLICIES ON LOW CARBON ELECTRICITY TRANSITION
270	MEANWHILE , AT LOW CARBON COST , CARBON MARKET SHOULD BE IMPLEMENTED COMBINING WITH RENEWABLE ELECTRICITY TARGET TO ACHIEVE THE EXPECTED POLICY TARGET
270	ENRE , ELECTRICITY ENERGY , NATURAL RESOURCES AND THE ENVIRONMENT , ENRE , ENRE , ENERGY CLIMATE
271	RENEWABLE BATTERY HYBRID POWER PLANTS IN CONGESTED ELECTRICITY MARKETS , IMPLICATIONS FOR PLANT CONFIGURATION
271	THE RISING INTEREST IN RENEWABLE BATTERY HYBRID POWER PLANTS DEMANDS UNDERSTANDING THEIR VALUE , ESPECIALLY IN CONGESTED AREAS OF THE ELECTRICITY MARKET
271	PREVIOUS RESEARCH DOESN T FACTOR IN GEOGRAPHIC CONSTRAINTS LIKE TRANSMISSION CONGESTION
271	OUR STUDY ASSESSES HOW CONGESTION PATTERNS AND HYBRID PLANT CONFIGURATIONS NEAR CONGESTED LINES IMPACT SYSTEM VALUE
271	WE USED POWER MARKET PRICES , , ACROSS SEVEN US ISOS , RUNNING A LINEAR OPTIMIZATION PROGRAM
271	WE FOUND PLACING A HOUR BATTERY , SIZED TO THE PLANT S NAMEPLATE CAPACITY , IN THE LOAD CENTER RELATIVE TO THE VRE RICH AREA YIELDS ADDITIONAL VALUE , MWH FOR SOLAR AND MWH FOR WIND
271	LONG DURATION STORAGE DECREASES BATTERY DEGRADATION AND RAISES CAPACITY FACTOR DURING STRESSED HOURS , THEREBY BOOSTING VALUE
271	THIS SUGGESTS HYBRIDS INCREASING RELEVANCE IN SYSTEMS WITH LIMITED TRANSMISSION CAPACITY
271	ENRE , ELECTRICITY ENERGY , NATURAL RESOURCES AND THE ENVIRONMENT , ENRE , ENRE , ENVIRONMENT AND SUSTAINABILITY
272	AN OVERVIEW OF ELECTRICITY CONSUMPTION IN EUROPE USING CLASSIFICATION , SEGREGATION , AND PREDICTION MODELS
272	ALTHOUGH AGGREGATE ELECTRICITY CONSUMPTION PROVIDES VALUABLE INFORMATION FOR MARKET ANALYSIS , DEMAND COMPOSITION OF INDUSTRIAL , RESIDENTIAL , ILLUMINATION , AND OTHER USES , AND SPECIAL DAYS , SUCH AS HOLIDAYS AND INDUSTRIAL SHUTDOWNS , DIFFER FOR EACH COUNTRY
272	WE ANALYZE THE HOURLY ELECTRICITY CONSUMPTION OF COUNTRIES IN THE EUROPEAN TRANSMISSION SYSTEM OPERATION FOR ELECTRICITY , ENTSO E , GRID FROM TO WE PROPOSE AN OUTLIER DETECTION METHOD TO IDENTIFY SPECIAL DAYS USING THE HOURLY TIME SERIES AND A MODULATED FOURIER SERIES EXPANSION MODEL TO DETERMINE THE BREAKDOWN OF INDUSTRIAL HOUSEHOLD AND HEATING COOLING CONSUMPTION
272	THE PROPOSED DEMAND PREDICTION MODEL HAS A AVERAGE ERROR WHEN HEATING USE IS NOT DOMINANT
272	IT ALSO ALLOWS COUNTRY CLASSIFICATION BY CONSUMPTION PATTERNS TO EFFICIENTLY MANAGE REGIONAL OR COUNTRY BASED ELECTRICITY MARKETS
272	ENRE , ELECTRICITY ENERGY , NATURAL RESOURCES AND THE ENVIRONMENT , ENRE , 
273	OPTIMAL ENERGY MANAGEMENT OF NETWORKED ENERGY HUBS IN COASTAL CITIES TO IMPROVE POWER SYSTEM RESILIENCY DURING NATURAL DISASTERS
273	SMART POWER SYSTEM IS A CRUCIAL BUILDING BLOCK OF A SMART CITY
273	THE KEY CHALLENGES FACED BY SMART POWER SYSTEMS ARE TO ACHIEVE COST EFFECTIVENESS , ZERO CARBON EMISSION , AND RESILIENCY
273	THE CHALLENGES BECOME FURTHER INTENSIFIED FOR THE COASTAL CITIES DUE TO THE REQUIREMENT OF ACHIEVING ADDITIONAL CAPABILITIES TO COMBAT EXTREME NATURAL EVENTS WHILE MEETING THE HIGHER ENERGY DEMAND FOR THE INDUSTRIAL BELT AROUND THE CITIES AND MANAGING DIFFERENT ENERGY INTENSIVE PROCESSES UNLIKE FROM THE ISLANDS
273	OPTIMALLY DESIGNING AND CONTROLLING THE ENERGY HUB NETWORK CAN BE A PROMISING SOLUTION TO ADDRESS THE CHALLENGES AND ENHANCE THE ROBUSTNESS OF THE POWER SYSTEM DURING NATURAL DISASTERS
273	A MATHEMATICAL MODEL IS DEVELOPED FOR OPTIMAL ENERGY MANAGEMENT STRATEGIES OF THE NETWORK TO IMPROVE THE PREPAREDNESS AND RESILIENCY OF THE SYSTEM BEFORE APPROACHING DISASTERS
273	ENRE , ELECTRICITY ENRE , ENERGY ENRE , ENERGY CLIMATE
274	NAVIGATING THE BITCOIN BOOM , ASSESSING THE IMPACT OF MINING ON POWER GENERATION EXPANSION
274	TEXAS HAS WELCOMED AN INFLUX OF BITCOIN MINERS SEEKING AFFORDABLE ENERGY RESOURCES
274	HOWEVER , THE PRESENCE OF MINERS HAS RAISED DEBATES ABOUT THEIR IMPACT ON THE CARBON FOOTPRINT OF THE POWER GRID AND NEW GENERATION INVESTMENTS
274	IN THIS WORK , WE STUDY THE IMPACT OF BITCOIN MINING ON GENERATION EXPANSION IN ERCOT AS A TWO STAGE STOCHASTIC COST MINIMIZATION PROBLEM WHICH WE FURTHER ANALYZE USING A PROGRESSIVE HEDGING APPROACH TO TACKLE THE LARGE PROBLEM SIZE
274	ENRE , ELECTRICITY ENRE , ENERGY ENRE , ENVIRONMENT AND SUSTAINABILITY
275	ASSESSING THE IMPACTS OF HIGH RENEWABLE POTENTIAL WHEN CONSIDERING CROSS BORDER TRADE IN THE ENERGY TRANSITION IN LATIN AMERICA
275	THERE ARE IN LATIN AMERICA AN ABSENCE OF STUDIES THAT EVALUATES THE CONSEQUENCE IN DEPTH OF THE OUTCOME OF CROSS BORDER TRADE AND THE USE OF FLEXIBLE TECHNOLOGIES IN THE ENERGY TRANSITION TO HIGHLY RENEWABLE SYSTEMS , CONSIDERING THE NATIONALLY DETERMINED CONTRIBUTION IN EACH REGION
275	IN THIS PAPER , WE STUDY THE IMPLICATIONS OF ACHIEVING THE NATIONALLY DETERMINED CONTRIBUTION OF THE COUNTRIES INVOLVED IN CROSS BORDER TRADE
275	TO DO THIS , WE USE A SOFT LINKING APPROACH THAT PROVIDES DEMAND AND CAPACITY INVESTMENT LEVELS FROM AN INTEGRATED ASSESSMENT MODEL WITH AN ENERGY SYSTEM MODEL
275	THE RESULTS SHOW THAT CROSS BORDER ELECTRICITY TRADE WOULD INCREASE SINCE SEVERAL NEIGHBORING COUNTRIES CAN POSITIVELY IMPACT THE ENERGY SECTOR
275	ENRE , ELECTRICITY ENRE , ENERGY ENRE , NATURAL RESOURCES
276	FREQUENCY REGULATION AND STORAGE , ON LOSSES AND PROFITS
276	WE DERIVE AN ANALYTICAL SOLUTION TO THE DECISION MAKING PROBLEM OF STORAGE OPERATORS WHO SELL FREQUENCY REGULATION POWER TO GRID OPERATORS AND TRADE ELECTRICITY ON DAY AHEAD MARKETS
276	THANKS TO A CONSTRAINT ON THE EXPECTED TERMINAL STATE OF CHARGE , THE AMOUNT OF ELECTRICITY TRADED ON DAY AHEAD MARKETS BECOMES AN IMPLICIT FUNCTION OF THE REGULATION POWER SOLD TO GRID OPERATORS
276	THE IMPLICIT FUNCTION QUANTIFIES THE AMOUNT OF POWER THAT NEEDS TO BE PURCHASED TO COVER THE EXPECTED ENERGY LOSS THAT RESULTS FROM PROVIDING FREQUENCY REGULATION
276	WE SHOW HOW THE ASSOCIATED MARGINAL COST OF FREQUENCY REGULATION DECREASES WITH ROUNDTRIP EFFICIENCY AND INCREASES WITH FREQUENCY DEVIATION DISPERSION
276	WE FIND THAT THE PROFITS OVER THE LIFETIME OF ENERGY CONSTRAINED STORAGE DEVICES ARE INVERSELY PROPORTIONAL TO THE LENGTH OF TIME FOR WHICH REGULATION POWER MUST BE COMMITTED
276	ENRE , ELECTRICITY ENRE , ENERGY OPT , OPTIMIZATION UNDER UNCERTAINTY
277	OPTIMAL SUBSIDY POLICY TO MANAGE SOLAR ADOPTION IN A REGION
277	A CENTRAL PLANNER OF A REGION AIMS TO ACHIEVE A CERTAIN LEVEL OF SOLAR ADOPTION AT THE END OF THE PLANNING HORIZON
277	THE TWO PRODUCTS AVAILABLE IN THE REGION ARE ROOF TOP AND SUBSCRIPTION SOLAR
277	THE REGION IS HETEROGENOUS IN THE HOUSEHOLD INCOME AND THE DEMAND FOR ELECTRICITY
277	WE MODEL THE DEMAND EVOLUTION AS A STOCHASTIC DIFFERENTIAL EQUATION AND DERIVE A CLOSED FORM EXPRESSION FOR THE DISTRIBUTION OF OPTIMAL ADOPTION TIME OF EACH INCOME LEVEL FOR A GIVEN SUBSIDY USING A OPTIMAL STOPPING FORMULATION
277	USING THE DERIVED DISTRIBUTION FUNCTION OF RANDOM ADOPTION TIMES AND GIVEN INCOME DISTRIBUTION , WE DEVELOP A CONTRAINTED NON LINEAR OPTIMIZATION MODEL TO DERIVE OPTIMAL SUBSIDY POLICY TO ENSURE FAIR AND EFFICIENT SOLAR ADOPTION IN PRESENCE OF HETEROGENITY IN THE REGION
277	ENRE , ELECTRICITY ENRE , ENERGY OPT , OPTIMIZATION UNDER UNCERTAINTY
277	ITS A OPTIMIZATION UNDER UNCERTAINTY PROBLEM 
278	ENERGY STORAGE AS LEARNING AGENTS IN ELECTRICITY MARKETS
278	THE STRATEGIC BEHAVIOR OF ENERGY STORAGE IN ENERGY MARKETS IS CRUCIAL FOR MARKET POWER MITIGATION AND NEW MARKET MODEL DEVELOPMENT
278	WHILE PRIOR RESEARCH HAS ATTEMPTED TO MODEL STRATEGIC ENERGY STORAGE BEHAVIORS , THESE EFFORTS HAVE OFTEN BEEN CONSTRAINED BY HIGH COMPUTATIONAL COSTS AND ASSUMPTIONS OF PERFECT MARKET CLEARING KNOWLEDGE AMONG ENERGY STORAGE PARTICIPANTS
278	THIS STUDY SEEKS TO OVERCOME THESE CHALLENGES BY INTEGRATING A WHOLESALE ENERGY MARKET SIMULATION WITH A MODEL BASED MACHINE LEARNING ENERGY STORAGE BIDDING ALGORITHM
278	THIS NOVEL APPROACH OFFERS A MORE REALISTIC REPRESENTATION OF ENERGY STORAGE STRATEGIC BEHAVIORS IN REAL WORLD SCENARIOS
278	ENRE , ELECTRICITY ENRE , ENERGY 
279	STUDY THE EFFECT OF WEATHER UNCERTAINTY AND FUTURE SCENARIOS ON THE US POWER GRID
279	THIS TALK WILL EXAMINE HOW MULTIPLE SOURCES OF UNCERTAINTY INFLUENCE SHORT TERM OPERATIONS OF BULK POWER SYSTEMS
279	THE FIRST PART OF THE TALK FOCUSES ON HOW STATIONARY WEATHER UNCERTAINTY AFFECTS THE DISTRIBUTION OF POWER PLANT AIR POLLUTION DAMAGES AMONG DIFFERENT DEMOGRAPHIC GROUPS
279	THE SECOND PART INVESTIGATES HOW GRID DECARBONIZATION WILL INFLUENCE THE RESPONSE OF POWER SYSTEM AND AIR QUALITY IMPACTS DURING EXTREME EVENTS , DROUGHTS AND HEAT WAVES , 
279	BOTH AIM TO IDENTIFY EFFECTIVE SOLUTIONS TO MITIGATE THE NEGATIVE EFFECTS OF AIR POLLUTION ON PUBLIC HEALTH WHILE ALSO ADDRESSING ISSUES OF SOCIAL JUSTICE
279	ENRE , ELECTRICITY ENRE , ENERGY CLIMATE ENRE , ENERGY
280	ELUCIDATING THE CAPABILITIES AND LIMITATIONS OF LONG DURATION ENERGY STORAGE MODELING APPROACHES
280	ENERGY STORAGE DEPLOYMENT ENABLES INTEGRATION OF VARIABLE RENEWABLE ENERGY , E G , WIND , SOLAR , IN POWER SYSTEMS
280	HOWEVER , EXISTING MODELS FOR LONG DURATION STORAGE LACK ACCURATE REPRESENTATION
280	THIS STUDY DISCUSSES CHALLENGES , LIMITATIONS , AND PROPOSES IMPROVEMENTS
280	ENHANCED LONG DURATION STORAGE DISPATCH MODELING CAN INCREASE OPERATIONAL VALUE BY AND CAPACITY CREDIT BY THIS REPRESENTS SIGNIFICANT COST SAVING OPPORTUNITIES FOR US INDEPENDENT SYSTEM OPERATORS
280	THREE DISPATCH METHODS WERE ASSESSED , FAVORING END VOLUME TARGETS
280	FURTHER RESEARCH IS NEEDED FOR IMPROVED METHODS AND INCLUSION OF EXTREME CLIMATE EVENTS IN POWER SYSTEM PLANNING AND OPERATION
280	ENRE , ELECTRICITY ENRE , ENERGY CLIMATE OPT , COMPUTATIONAL OPTIMIZATION AND SOFTWARE
281	THE ROLE OF LONG DURATION ENERGY STORAGE IN MITIGATING THE RELIABILITY IMPACTS OF CLIMATE DRIVEN EXTREME WEATHER EVENTS 
281	IT IS BECOMING CLEAR THAT CLIMATE CHANGE WILL LEAD TO CHANGES IN FUTURE WEATHER PATTERNS , INCLUDING INCREASINGLY FREQUENT AND IMPACTFUL PERIODS OF EXTREME OPERATING CONDITIONS
281	WE DEMONSTRATE THE IMPORTANCE OF CONSIDERING FUTURE WEATHER CONDITIONS IN GENERATION EXPANSION PLANNING THROUGH A CASE STUDY ANALYSIS OF THE ERCOT POWER SYSTEM , WITH A SPECIFIC FOCUS ON ESTABLISHING THE ROLE OF LONG DURATION ENERGY STORAGE IN MITIGATING THE ASSOCIATED RELIABILITY IMPACTS
281	WE UTILIZE DATA FROM THREE GLOBAL CLIMATE MODELS TO GENERATE A RANGE OF FUTURE SCENARIOS FOR WIND AND SOLAR AVAILABILITY AND ELECTRICITY DEMAND , WHILE ALSO CONSIDERING TEMPERATURE DEPENDENT GENERATOR AND TRANSMISSION INFRASTRUCTURE OUTAGE PROBABILITIES
281	WE THEN ILLUSTRATE HOW REPRESENTING PROJECTED FUTURE WEATHER CONDITIONS IN A STOCHASTIC GEP FRAMEWORK IMPACTS THE OPTIMAL GENERATION PORTFOLIO
281	ENRE , ELECTRICITY ENRE , ENERGY CLIMATE 
282	EFFECT OF OPTIMALLY POOLING DIVERSE WIND GENERATION SOURCES ON RESULTING OPERATIONAL COSTS
282	IT IS WIDELY ACCEPTED THAT COMBINING TOGETHER GEOGRAPHICALLY OR TECHNOLOGICALLY DIVERSE ENERGY SOURCES CAN SIGNIFICANTLY REDUCE GENERATION VARIABILITY
282	SINCE VARIABILITY DIRECTLY TRANSLATES INTO INCREASED COST OF WIND AND SOLAR ENERGY , BEING ABLE TO BETTER UNDERSTAND WAYS TO CONTROL IT CAN BE IMPORTANT
282	IN PREVIOUS EFFORTS WE HAVE DEMONSTRATED THAT BY A PRIORI EMPLOYING ADVANCED OPTIMIZATION TECHNIQUES , SPECIFICALLY , RISK AVERSE PORTFOLIO MODELING , , IT IS POSSIBLE TO DESIGN ENERGY GENERATION PORTFOLIO THAT EXHIBITS SIGNIFICANTLY LOWER INTERMITTENCY AND HIGHER GENERATION FORECASTING ACCURACY
282	IN THIS TALK WE WILL DISCUSS OUR EFFORTS TO MODEL THE EXTENT TO WHICH THIS REDUCTION IN VARIABILITY CAN DIRECTLY TRANSLATE TO REDUCTION IN OPERATIONAL COSTS AND GRID EFFICIENCY
282	ENRE , ELECTRICITY ENRE , ENVIRONMENT AND SUSTAINABILITY ENERGY , NATURAL RESOURCES AND THE ENVIRONMENT , ENRE , 
283	ENHANCING POWER GRID RESILIENCE , CO OPTIMIZING REPAIR CREW ROUTING AND NETWORK RECONFIGURATION FOR EFFECTIVE MANAGEMENT OF POWER OUTAGES 
283	THE INCREASING OCCURRENCE OF NATURAL DISASTERS NECESSITATES THE EFFECTIVE MANAGEMENT OF POWER OUTAGES IN DISTRIBUTION NETWORKS
283	THIS STUDY FOCUSES ON TWO KEY TASKS , OFFLINE REPAIR CREW ROUTING AND ONLINE DISTRIBUTION RECONFIGURATION
283	THE OBJECTIVE IS TO CO OPTIMIZE THE VISIT SEQUENCE OF REPAIR CREWS AND RECONFIGURATION TASKS , AIMING TO MAXIMIZE THE SUPPLY LOADS DURING POWER GRID RECOVERY
283	A MIXED INTEGER PROGRAMMING MODEL IS PROPOSED FOR REPAIR CREW ROUTING AND NETWORK RECONFIGURATION IN A DISCRETE EVENT SYSTEM
283	FURTHERMORE , DEEP REINFORCEMENT LEARNING IS USED TO ADDRESS POTENTIAL CHANGES IN REPAIR PLANS BASED ON ACTUAL REPAIR TIME
283	THE PROPOSED METHODOLOGY IS EXPERIMENTALLY EVALUATED USING MODIFIED IEEE BUS DISTRIBUTION SYSTEMS
283	ENRE , ELECTRICITY OPT , INTEGER AND DISCRETE OPTIMIZATION MACHINE LEARNING FOR OPTIMIZATION
284	PRICING AND ECONOMIC IMPACT OF CONVEX RELAXATIONS FOR POWER FLOW ON ELECTRICITY SPOT MARKETS
284	WELFARE MAXIMIZATION PROBLEMS ON ELECTRICITY SPOT MARKETS SHOULD IDEALLY CONSIDER CONSTRAINTS THAT REFLECT THE PHYSICS OF THE POWER GRID
284	AS THIS LEADS TO AN INTRACTABLE NON CONVEX AND NON LINEAR OPTIMIZATION PROBLEM , LINEARIZED POWER FLOW MODELS ARE CURRENTLY USED IN PRACTICE
284	TIGHTER NON LINEAR CONVEX RELAXATIONS HAVE BEEN DEVELOPED , BUT MOST RESEARCH FOCUSES ON THEIR OPTIMALITY AND SCALABILITY
284	WE STUDY THE IMPACT OF DIFFERENT RELAXATIONS ON PRICES , REQUIRED SIDE PAYMENTS BY THE MARKET OPERATOR , AND REDISPATCH COSTS , WHILE ALSO CONSIDERING NON CONVEXITIES IN THE PREFERENCES OF BUYERS AND SELLERS
284	LARGE SCALE NUMERICAL EXPERIMENTS INDICATE THAT CURRENTLY USED LINEARIZED MODELS CAN LEAD TO UNJUSTIFIABLY HIGH PRICES AND BIASED INVESTMENT SIGNALS , WHILE TIGHTER CONVEX RELAXATIONS SET BETTER INCENTIVES AND REFLECT THE PHYSICS OF THE GRID MORE ACCURATELY
284	ENRE , ELECTRICITY OPT , NONLINEAR OPTIMIZATION AUCTIONS AND MARKET DESIGN
285	A BINARY EXPANSION APPROACH FOR THE OPTIMAL DEMAND RESPONSE IN LARGE AND HIGH ALTITUDE WATER DISTRIBUTION NETWORKS
285	DEMAND RESPONSE FOR WATER NETWORKS IS AN OPTIMISATION MODEL THAT DETERMINES WHICH WATER PUMPS WILL BE TURNED ON OR OFF EVERY TIME ACCORDING TO A DYNAMIC ELECTRICAL TARIFF
285	THE PROBLEM IS RELEVANT IN MINING DUE TO THE HIGH POWER USAGE OF WATER PUMPS AND THE POWER PRICES UNCERTAINTY
285	THE PROBLEM FACES DIFFICULTIES , I , NONLINEARITIES OF THE FRICTIONAL LOSSES ALONG THE PIPES AND PUMPS , II , MANY POSSIBLE COMBINATIONS OF PRESSURE HEAD AND FLOW RATE , WHICH LEADS TO HIGH COMPUTATIONAL COSTS
285	THESE LIMITATIONS PREVENT THE PROBLEM FROM BEING SOLVED IN A REASONABLE COMPUTATIONAL TIME IN WATER NETWORKS WITH MORE THAN TWO PUMPS AND RESERVOIRS
285	THEREFORE , WE DEVELOP NEW MODELS FOR THIS PROBLEM THAT USE A BINARY EXPANSION APPROACH TO ACCOUNT FOR THE NONLINEARITIES AND MINIMISE THE SYSTEMIC COST , AND IT REDUCES THE COMPUTATIONAL TIME COMPARED TO THE CURRENT NONLINEAR GUROBI SOLVER
285	ENRE , ELECTRICITY OPT , NONLINEAR OPTIMIZATION OPT , NETWORK OPTIMIZATION
286	DATA VALUATION FROM DATA DRIVEN OPTIMIZATION
286	IN THIS TALK WE SHOW HOW DISTRIBUTIONALLY ROBUST OPTIMIZATION , DRO , OFFERS A NATURAL FRAMEWORK TO BOTH , I , ACCOUNT FOR DATA QUALITY IN DATA DRIVEN STOCHASTIC OPTIMIZATION AND , II , DIRECTLY VALUE DATA SETS ACCORDING TO THEIR CONTRIBUTION TO THE DECISION COST
286	FOR THIS PURPOSE , WE FIRST DISCUSS THE USEFULNESS OF THE WASSERSTEIN METRIC TO QUANTIFY DATA QUALITY AND THEN CONSTRUCT A NOVEL WASSERSTEIN DRO FORMULATION THAT ACCOMMODATES DATA FROM MULTIPLE SOURCES WITH INDIVIDUAL TRANSPORT BUDGETS
286	WE ILLUSTRATE THE PROPOSED FRAMEWORK USING AN APPLICATION FROM POWER SYSTEM OPERATIONS , WHERE WE SHOW HOW THE RESULTING OPTIMIZATION PROBLEM IMPLICITLY COMPUTES THE VALUE OF DATA GIVEN ITS QUALITY AND THE CONTEXT OF THE PHYSICS CONSTRAINED DECISION MAKING PROBLEM AT HAND
286	ENRE , ELECTRICITY OPT , OPTIMIZATION UNDER UNCERTAINTY 
286	WE PRESENT A NOVEL APPROACH TO VALUATE DATA SETS TO FACILITATE DATA ECONOMIC FRAMEWORKS
287	TESLA AUTOBIDDER , ALGORITHMIC BIDDING IN WHOLESALE ELECTRICAL MARKETS INTERNATIONALLY
287	AUTOBIDDER IS TESLA S PLATFORM FOR ALGORITHMIC TRADING IN WHOLESALE ELECTRICAL MARKETS
287	BIDDING ON BEHALF OF VARIOUS ENERGY STORAGE ASSET TYPES AND SITES ACROSS MULTIPLE MARKET DESIGNS INTERNATIONALLY PRESENTS UNIQUE HORIZONTAL SCALING CHALLENGES
287	IN THIS TALK WE EVALUATE THE KEY DIMENSIONS BY WHICH PARTICIPATION IN WHOLESALE ELECTRICAL MARKETS VARY AND COMPARE THIS TO THE BREADTH OF OPTIMIZATION TOOLS THAT CAN BE USED TO SOLVE THEM
287	WE AIM TO ILLUSTRATE THE SUBTLE YET IMPORTANT DIFFICULTIES CREATED BY DIFFERENCES IN MARKET DESIGN
287	ENRE , ELECTRICITY OPTIMIZATION , OPT , AUCTIONS AND MARKET DESIGN
288	OPTIMIZATION MODELS FOR RESIDENTIAL ELECTRICITY USAGE UNDER NET METERING PROGRAMS IN A SMART GRID
288	THIS RESEARCH AIMS TO STUDY RESIDENTS ELECTRICITY CONSUMPTION BEHAVIOR AND THE RESULTING SYSTEM LEVEL CONSUMPTION PROFILE IN A SMART GRID
288	WE ASSUME THAT EACH HOUSEHOLD IS EQUIPPED WITH A SYSTEM CONSISTING OF SOLAR PANELS AND BATTERY STORAGE AND , UNDER THE NET METERING PROGRAM , IS ALLOWED TO SELL EXCESS ELECTRICITY BACK TO THE GRID
288	WE STUDY ELECTRICITY CONSUMPTION FROM TWO DIFFERENT PERSPECTIVES
288	THE SYSTEM OPTIMAL , SO , MODEL MINIMIZES THE TOTAL SYSTEM COST , WHILE THE USER EQUILIBRIUM , UE , MODEL DESCRIBES THE INDIVIDUAL HOUSEHOLDS BEHAVIOR IN A NASH EQUILIBRIUM
288	UNDER CERTAIN CONVEXITY ASSUMPTIONS , WE PROVE THE EXISTENCE AND UNIQUENESS OF THE SOLUTION
288	NUMERICAL EXPERIMENTS USING A SIMULATED NETWORK AND EXTENSIVE SENSITIVITY ANALYSIS WILL BE REPORTED
288	ENRE , ELECTRICITY OPTIMIZATION , OPT , 
289	A STOCHASTIC DECISION DEPENDENT MODEL FOR DEPLOYMENT OF MOBILE POWER SOURCES IN POWER DISTRIBUTION SYSTEMS
289	MOBILE POWER SOURCES , MPSS , HAVE PROMISING POTENTIAL FOR FLEXIBILITY IN POWER DISTRIBUTION SYSTEMS , PDSS , FOR RESILIENT EMERGENCY RESPONSES TO NATURAL DISASTERS
289	THE RESTORATION PROCESS CAN BE MADE MORE EFFICIENT BY DEPLOYING MPSS TO STRATEGIC DEPOTS IN ADVANCE OF HIGH IMPACT LOW PROBABILITY EVENTS
289	THIS PAPER PROPOSES A NEW SERVICE RESTORATION PROBLEM , WHICH INCORPORATES ENDOGENOUS UNCERTAINTY IN THE DECISION MAKING PROCESS FOR MPSS PRE DISASTER DEPLOYMENT
289	WE PROPOSE A STOCHASTIC JOINT CHANCE CONSTRAINED PROGRAMMING MODEL AND REFORMULATE THE MODEL AS AN EQUIVALENT MIXED INTEGER LINEAR PROGRAMMING , MILP , MODEL
289	CASE STUDIES DEMONSTRATE THE EFFECTIVENESS OF THE PROPOSED RESTORATION SCHEME IN BOOSTING PDS RESILIENCE AND THE SIGNIFICANCE OF INCORPORATING ENDOGENOUS UNCERTAINTIES IN THE DECISION MAKING PROCESS
289	ENRE , ELECTRICITY PUBLIC SECTOR OR LOCATION ANALYSIS
290	DESIGNING EFFICIENT AND EQUITABLE RETAIL RATE FOR DISTRIBUTED ENERGY RESOURCES
290	ROOFTOP SOLAR AND STORAGE ADOPTION WITH VARIABLE ELECTRICITY RETAILS THAT REFLECT MARGINAL , ENERGY , AND FIXED , NETWORK , COSTS OF UTILITY CAN PLAY AN IMPORTANT ROLE IN EFFICIENT AND EQUITABLE DECARBONIZATION
290	UNDER NET ENERGY METERING , ESPECIALLY IN STATES WITH HIGH TARIFFS , ADOPTERS OF SOLAR AND OR STORAGE HAVE BEEN OVERCOMPENSATED FOR THE SURPLUS ENERGY SOLD BACK
290	IN THIS WORK , WE TEST DIFFERENT RETAIL RATE FORMULATIONS TWO PART , TIERED , AND HIGH PEAK OFF PEAK TIME VARYING VOLUMETRIC TARIFFS UNDER A NET BILL MINIMIZATION DECISION MAKING FRAMEWORK WITH FLEXIBLE ELECTRIFIED LOAD TO UNDERSTAND ADOPTER BILL SAVINGS , UTILITY NET COSTS , AND SOCIETY S ENVIRONMENTAL SURPLUS FOCUSED ON DISTRIBUTIONAL EQUITY
290	INITIAL RESULTS INDICATE STORAGE WITH SOLAR PROVIDES BENEFITS TO BOTH ADOPTERS AND UTILITY WITH TIME VARYING RATES , FOR BOTH VOLUMETRIC AND TWO PART TARIFFS , 
290	ENRE , ELECTRICITY REVENUE MANAGEMENT AND PRICING DECISION ANALYSIS SOCIETY
291	A DATA DRIVEN MODEL OF THE EUROPEAN DAY AHEAD ELECTRICITY MARKET
291	IN EUROPE S DAY AHEAD ELECTRICITY MARKET , FLOW BASED MARKET COUPLING FACILITATES ELECTRICITY TRADE BETWEEN MARKET ZONES
291	TRANSMISSION SYSTEM OPERATORS RESTRICT COMMERCIAL FLOWS BASED ON EXPECTED CONGESTION ON INTER AND INTRA ZONAL NETWORK ELEMENTS
291	A LACK OF TRANSPARENCY ON THE STRATEGIES FOLLOWED BY TRANSMISSION SYSTEM OPERATORS AND THE BIDS OFFERS CHALLENGES STUDYING THE MARKET S PERFORMANCE
291	WE LEVERAGE PUBLICLY AVAILABLE DATA SETS TO RECONSTRUCT SUPPLY CURVES AND THE FLOW BASED DOMAINS THROUGH INVERSE OPTIMIZATION
291	THE RESULTING INTERPRETABLE MODEL REPRODUCES DAY AHEAD ELECTRICITY PRICES , CROSS BORDER FLOWS , AND FLOW BASED DOMAINS WITH SIMILAR ACCURACY AS STATE OF THE ART BLACK BOX TOOLS
291	IN ADDITION , IT ALLOWS STUDYING THE EXPECTED IMPACT OF STRUCTURAL CHANGES , SUCH AS NEW TRANSMISSION OR GENERATION ASSETS
291	ENRE , ELECTRICITY WE USE DATA TO RECOVER A MODEL THAT DESCRIBES EUROPE S DAY AHEAD ELECTRICITY MARKET
292	ASSESSING THE EFFECTS OF VARIOUS ASSUMPTIONS ON EQUILIBRIUM MODELS IN POWER SYSTEM EXPANSION PLANNING
292	THE MODELING OF STRATEGIC INTERACTIONS BETWEEN COMPETING PROFIT SEEKING ENTITIES IN THE CONTEXT OF POWER SYSTEM EXPANSION PLANNING HAS BEEN INVESTIGATED IN THE LITERATURE
292	GAME THEORY BASED EQUILIBRIUM MODELING APPROACHES HAVE BEEN COMMONLY EMPLOYED FOR THIS PURPOSE
292	HOWEVER , DUE TO COMPUTATIONAL COMPLEXITIES ASSOCIATED WITH THESE EQUILIBRIUM MODELS , MANY SIMULATION MODELS TEND TO MAKE SIMPLIFICATIONS AND ASSUMPTIONS
292	THIS PRESENTATION AIMS TO EXPLORE THE IMPACT OF DIFFERENT ASSUMPTIONS ON THE SOLUTIONS DERIVED FROM EQUILIBRIUM MODELS
292	ENRE , ELECTRICITY 
293	OPTIMAL COMPUTATION OF FIXED CHARGES FOR EFFICIENT ELECTRICITY TARIFFS IN FUTURE DISTRIBUTION NETWORKS
293	WITH THE INCREASINGLY IMPORTANT ROLE OF DISTRIBUTION NETWORKS IN THE ENERGY TRANSITION , ELECTRICITY TARIFFS SHOULD EVOLVE TO BECOME MORE COST REFLECTIVE
293	THIS IMPLIES RESORTING MORE AND MORE TO FIXED CHARGES TO RECOVER RESIDUAL NETWORK COSTS
293	AT THE SAME TIME , HIGHER FIXED CHARGES INCREASE THE INCENTIVE OF PROSUMERS TO GO OFF GRID WHILE DECREASING COSTS OF DER WILL ONLY INCREASE THE RISK OF GRID DEFECTION IN THE FUTURE
293	IN THIS WORK , WE PROPOSE A MODEL THAT ENDOGENIZE THE COMPUTATION OF FIXED CHARGES IN DISTRIBUTION TARIFFS THAT ACCOUNTS FOR THE POSSIBILITY OF GRID DEFECTION BY PROSUMERS IN THE NETWORK
293	BASED ON THIS FRAMEWORK , WE PROPOSE ILLUSTRATIVE RESULTS ON SMALL INSTANCES AS WELL SIMULATIONS ON REALISTIC CASES , AND COMMENT ON THE IMPLICATION OF THE INCREASING RISK OF GRID DEFECTION FOR THE DESIGN OF DISTRIBUTION TARIFFS
293	ENRE , ELECTRICITY 
294	CREATION OF SYNTHETIC TRANSMISSION NETWORKS WITH FLEXIBLE AGGREGATION AND REALISTIC INTERZONAL POWER FLOW PROPERTIES FOR ELECTRIC POWER SYSTEM PLANNIN 
294	PLANNING STUDIES FOR LARGE ELECTRIC POWER SYSTEMS REQUIRE DATA WHICH IS SUFFICIENTLY DETAILED TO CAPTURE LOCATIONAL CONSTRAINTS RESULTING FROM TRANSMISSION CONGESTION , WHILE COMPUTATIONAL BURDENS DEMAND A DEGREE OF AGGREGATION
294	THIS WORK DEVELOPS A FRAMEWORK FOR AGGREGATING TRANSMISSION NETWORKS TO A LEVEL OF DETAIL WHICH IS FLEXIBLE TO COMPUTATIONAL OR OTHER MODELING NEEDS , USING PREDEFINED ZONAL BOUNDARIES OR CLUSTERING BASED ON NETWORK PROPERTIES
294	THE PARAMETERS OF THE AGGREGATED TRANSMISSION LINKS ARE CALCULATED USING BOTH NETWORK REDUCTION AND OPTIMAL POWER FLOW TECHNIQUES
294	PLANNING OUTCOMES AND COMPUTATIONAL PERFORMANCE ARE COMPARED ACROSS DIFFERENT LEVELS OF AGGREGATION , DEMONSTRATING THE TRADEOFFS BETWEEN FIDELITY AND TRACTABILITY
294	ENRE , ELECTRICITY THE TALK PRESENTS MEANS TO BALANCE DATA FIDELITY AND TRACTABILITY THROUGH REDUCTIONS METHODS 
295	THE ENERGY CARBON NEXUS OF SUSTAINABLE ENERGY SYSTEMS
295	TO ACHIEVE CARBON NEUTRALITY BY , SWITZERLAND NEEDS A COMPREHENSIVE UNDERSTANDING OF ITS ENERGY SYSTEM AND THE POTENTIAL FOR USING CARBON AS A RECYCLABLE COMMODITY IN ENERGY X PATHS
295	OUR STUDY USES A MILP METHOD TO INVESTIGATE THE ENERGY CARBON NEXUS AND DEMONSTRATES THE CRITICAL ROLE OF ENERGY X IN SUPPLYING SUSTAINABLE FUELS AND ACHIEVING NET ZERO CO EMISSIONS
295	LEVERAGING OR MS TECHNIQUES AND DATA DRIVEN APPROACHES , OUR WORK OPTIMIZES ENERGY SYSTEM DESIGN AND PROVIDES A SCIENTIFIC BASIS FOR DECISION MAKERS
295	INTEGRATION OF ENERGY X RESULTS IN COST EFFECTIVE STORAGE SOLUTIONS DURING TIMES OF LIMITED IMPORT CAPACITIES OR HIGH PRICES
295	OUR INSIGHTS ARE APPLICABLE TO OTHER NATIONAL ENERGY SYSTEMS
295	ENRE , ENERGY EMERGING TECHNOLOGIES AND APPLICATIONS OPTIMIZATION , OPT , 
295	DATA DRIVEN SYSTEM DESIGN
295	DECISION MAKING TOWARDS APPLICATION BASED ON SCIENTIFIC RESULTS
296	HOW RELIABILITY FACTORS AFFECT STOCHASTIC ENERGY SYSTEM PLANNING
296	THE EVER INCREASING DEMAND FOR ELECTRICITY NECESSITATES EXPANDING POWER INFRASTRUCTURE TO KEEP UP WITH DEMAND
296	ENERGY SYSTEM PLANNING IS DRIVEN BY THE DEMAND FORECAST , BEING PRONE TO DEMAND ESTIMATION ERROR
296	TAKING THE EFFECT OF UNCERTAINTY IN DEMAND PREDICTION INTO ACCOUNT , THIS RESEARCH WILL MODEL ENERGY SYSTEM PLANNING AS A STOCHASTIC PROBLEM
296	SUPPLYING RELIABLE POWER TO CUSTOMERS IS ANOTHER CRUCIAL ASPECT OF POWER SYSTEM PLANNING THAT WILL BE CONSIDERED VIA MEETING PREDETERMINED POWER SYSTEM RELIABILITY INDICES
296	ENRE , ENERGY ENRE , ELECTRICITY ENRE , ENVIRONMENT AND SUSTAINABILITY
297	MODELING RAMPING CONSTRAINTS FOR THE STATISTICAL UNIT COMMITMENT PROBLEM
297	OVER THE PAST DECADE , STOCHASTIC MODELS HAVE GAINED RELEVANCE IN THE POWER SYSTEMS OPERATION FIELD
297	DUE TO A GROWING INTEGRATION OF RENEWABLE ENERGY SOURCES , IT IS ESSENTIAL TO INCORPORATE THE INHERENT VARIABILITY OF THESE SOURCES INTO OPTIMIZATION MODELS
297	IN THIS WORK , WE PROPOSE A VARIATION OF THE STOCHASTIC UNIT COMMITMENT PROBLEM THAT DOES NOT RELY ON SCENARIO BASED METHODS
297	INSTEAD , AN ANALYTICAL FORMULATION OF THE EXPECTED DISPATCH COST IS DERIVED FROM THE NET LOAD PROBABILITY DISTRIBUTION FUNCTION , CONSIDERING TECHNICAL CONSTRAINTS SUCH AS STARTUP COST TRAJECTORIES AND RAMPING CONSTRAINTSL
297	THE MODEL IS TESTED IN THE CALIFORNIA INDEPENDENT SYSTEM OPERATOR , CAISO , POWER SYSTEM
297	RESULTS , ALGORITHMS , AND CONCLUSIONS WILL BE PRESENTED
297	ENRE , ENERGY ENRE , ELECTRICITY OPT , OPTIMIZATION UNDER UNCERTAINTY
298	ASSESSING AND ENABLING THE FEASIBILITY OF THE EUROPEAN ENERGY TRANSITION UNDER MYOPIC AND CONSTRAINED TECHNOLOGY DEPLOYMENT
298	CURRENT EVIDENCE CASTS DOUBT ON THE FEASIBILITY OF PERFORMING AN ENERGY TRANSITION THAT COMPLIES WITH THE C CLIMATE GOAL
298	YET , AN ABUNDANT BODY OF ENERGY SYSTEM OPTIMIZATION MODELS , ESOMS , PROPOSES GUIDELINES TO ACHIEVE THE TRANSITION
298	HOWEVER , ESOMS OFTEN SIMPLIFY THE CAPACITY EXPANSION PROCESS BY ASSUMING PERFECT FORESIGHT AND INSTANTANEOUS TECHNOLOGY DEPLOYMENT , RESULTING IN POTENTIALLY UNREALISTIC AND INEFFECTIVE TRANSITION RECOMMENDATIONS
298	FOCUSING ON EUROPE , WE INVESTIGATE TWO BARRIERS TO THE OPTIMAL DECISION MAKING , I , MYOPIC FORESIGHT , AND II , REAL WORLD CONSTRAINTS ON TECHNOLOGY DEPLOYMENT
298	WE FIND THAT THE COMBINATION OF THE TWO BARRIERS MIGHT DELAY THE ENERGY TRANSITION AND MAKE EUROPE MISS ITS CLIMATE TARGETS
298	BASED ON THESE INSIGHTS , WE EXPLORE AND PROPOSE MEASURES TO ENABLE A SUCCESSFUL TRANSITION
298	ENRE , ENERGY ENRE , ENERGY CLIMATE ENRE , ELECTRICITY
298	OPTIMIZATION MODELS ARE UNIQUELY SUITED TO FIND OPTIMAL SOLUTIONS FOR A MYRIAD OF PARAMETER VALUES 
299	THE IMPACT OF MACROECONOMIC INDICATORS ON OIL PRICES , EVIDENCE FROM EMERGING ECONOMIES
299	THE RESEARCH ENDEAVOURS TO UNDERSTAND THE CONCEPT OF MACROECONOMIC INDICATORS AND ASSESSMENT OF VARIATIONS IN OIL PRICES IN ANY COUNTRY , THE IMPACT OF MACROECONOMIC INDICATORS ON OIL PRICES AND TO PROVIDE RECOMMENDATIONS IN THIS REGARD
299	THE DATA FROM THE YEARS WAS ADOPTED WHERE THE VARIABLES USED FOR ASSESSMENT WERE INFLATION , INTEREST , EXCHANGE RATE , GDP AND OIL PRICES OF THE GLOBAL MARKET
299	IT WAS CONCLUDED THAT THE VARIABLES ARE INTERRELATED WITH EACH OTHER AS IT EXPLAINS THE ASSOCIATION BETWEEN THE VARIABLES AS HAVING AN IMPACT ON THE OIL PRICES IN THE COUNTRY
299	BASED ON RESULTS FROM THE CURRENT RESEARCH IT IS RECOMMENDED TO PROVIDE THE BALANCE REGARDING FOUR MACROECONOMIC FACTORS , TAKEN IN THIS RESEARCH SUCH AS INTEREST RATE , INFLATION RATE , EXCHANGE RATE AND REAL GDP OF A COUNTRY THAT COULD INFLUENCE THE DEVELOPMENT OF THE ECONOMY
299	ENRE , ENERGY ENRE , ENVIRONMENT AND SUSTAINABILITY ENRE , NATURAL RESOURCES
299	OR MS CAN HARNESS IT LIKE BIG DATA ANALYTICS , OPTIMIZATION AND DECISION SUPPORT , PREDICTIVE MODELING 
300	OPTIMIZATION MODEL FOR GRID CONNECTED PHOTOVOLTAIC AND BATTERY ENERGY STORAGE SYSTEM 
300	THIS PAPER PROPOSES AN OPTIMIZATION MODEL FOR PHOTOVOLTAIC , PV , AND BATTERY ENERGY STORAGE SYSTEMS , BESS , IN A GRID CONNECTED ELECTRIC NETWORK
300	THE MODEL CONSIDERS THE VARIABILITY AND UNCERTAINTY OF SOLAR ENERGY GENERATION RESOURCES AND THE AVAILABLE CAPACITIES FOR THE BATTERY STORAGE SYSTEMS TO DETERMINE THE BEST ENERGY MIX TO MEET THE GROWING ENERGY DEMANDS
300	A MIXED INTEGER LINEAR PROGRAMMING , MILP , TECHNIQUE WAS USED ON EXPERIMENTAL IEEE BUS SYSTEMS TO DETERMINE THE OPTIMAL SOLUTION FOR COMBINING PV AND BESS TO REDUCE DEPENDENCY ON THE ELECTRIC GRID SYSTEM
300	ACADEMIC RESEARCHERS AND UTILITY ASSET MANAGERS WOULD BENEFIT FROM THE EXPERIMENTAL RESULTS OBTAINED FROM THIS RESEARCH PAPER TO GAIN BETTER INSIGHTS INTO ACHIEVING THEIR SUSTAINABLE ENERGY GROWTH REQUIREMENTS , GIVEN A LIMITED BUDGET OVER A PLANNING HORIZON
300	ENRE , ENERGY ENRE , ENVIRONMENT AND SUSTAINABILITY OPT , OPTIMIZATION UNDER UNCERTAINTY
301	AN EFFICIENT LEARNING BASED SOLVER FOR TWO STAGE DC OPTIMAL POWER FLOW WITH FEASIBILITY GUARANTEES
301	TWO STAGE STOCHASTIC DC OPTIMAL POWER FLOW , OPF , PROBLEMS ARE COMPUTATIONALLY CHALLENGING TO SOLVE DUE TO THE LARGE NUMBER OF SCENARIOS NEEDED TO ACCURATELY REPRESENT THE UNCERTAINTIES
301	WE PROPOSE A LEARNING METHOD TO SOLVE TWO STAGE PROBLEMS EFFICIENTLY AND OPTIMALLY
301	A TECHNIQUE CALLED THE GAUGE MAP IS INCORPORATED INTO THE LEARNING ARCHITECTURE DESIGN TO GUARANTEE THE LEARNED SOLUTIONS FEASIBILITY TO THE NETWORK CONSTRAINTS
301	THAT IS SAID , THE SECOND STAGE DECISIONS ARE APPROXIMATED BY FEED FORWARD FUNCTIONS THAT ONLY OUTPUT FEASIBLE SOLUTIONS
301	SIMULATION RESULTS ON STANDARD IEEE SYSTEMS SHOW THAT , COMPARED TO ITERATIVE SOLVERS AND THE WIDELY USED AFFINE POLICY , OUR PROPOSED METHOD NOT ONLY LEARNS GOOD QUALITY SOLUTIONS BUT ALSO ACCELERATES THE COMPUTATION BY ORDERS OF MAGNITUDE
301	ENRE , ENERGY MACHINE LEARNING FOR OPTIMIZATION OPT , OPTIMIZATION UNDER UNCERTAINTY
301	OUR WORK USES DATA TO TRAIN THE LEARNING MODEL THAT SOLVES THE OPTIMIZATION PROBLEM 
302	BIO INSPIRED SELF HEALING FOR ENHANCING RESILIENCE IN POWER SYSTEMS
302	INSPIRED BY SELF HEALING IN BIOLOGICAL SYSTEMS , THIS STUDY PROPOSES A NOVEL FRAMEWORK TO ENHANCE THE RESILIENCE OF INTEGRATED ENERGY SYSTEMS
302	THE SELF HEALING OPERATION BORROWS FROM MORPHOGENESIS , I E , CELL RECOMBINATION AND TISSUE FORMATION , IMPLEMENTED THROUGH SECTIONING OF FAULTED ZONES IN THE EVENT OF A DISRUPTION
302	THE OBJECTIVE IS TO DETERMINE RESTORATION PATHWAYS WITH THE LEAST COST OF OPTIMALLY CONFIGURED CAPACITIES
302	SPECIFICALLY , HOW MUCH SHOULD BE INVESTED IN BUILDING SUCH REDUNDANT CAPACITIES
302	WHAT ELECTRICITY GENERATING TECHNOLOGIES SHOULD MAKE UP THE PORTFOLIO
302	AN IEEE REFERENCE NETWORK MODEL IS USED TO VALIDATE THE RESTORATIVE INTERVENTION
302	ENRE , ENERGY OPT , OPTIMIZATION UNDER UNCERTAINTY 
303	PRIORITIZING AND OPTIMIZING COUNTY LEVEL RESPONSES FOR A JUST ENERGY TRANSITION
303	ENERGY SYSTEM DECARBONIZATION WILL , ABSENT LARGE SCALE CARBON CAPTURE DEPLOYMENT , INVOLVE REDUCING FOSSIL ENERGY PRODUCTION AND USE
303	THIS SHIFT WILL NEGATIVELY IMPACT COMMUNITIES THAT RELY ON FOSSIL FUELS FOR ECONOMIC ACTIVITY , WITH SUBSTANTIAL COUNTY LEVEL VARIATION IN IMPACT AND SENSITIVITY
303	IN THIS WORK , WE LEVERAGE COUNTY LEVEL SOCIOECONOMIC DATA , WIND INSTALLATION AND OPERATION COST DATA , AND MAXIMUM WIND GENERATION CAPACITY , TO BUILD AN OPTIMIZATION FRAMEWORK DESIGNED TO MAXIMIZE JOB CREATION ACROSS OHIO
303	BY WEIGHTING COUNTIES ON THE BASIS OF EXPOSURE AND VULNERABILITY DURING ENERGY SYSTEM TRANSITIONS , OUR MODEL ALLOWS POLICY MAKERS TO PRIORITIZE INVESTMENTS IN AREAS THAT ARE LIKELY TO BE LEFT BEHIND DURING DECARBONIZATION
303	ENRE , ENERGY PUBLIC SECTOR OR DATA , OR , AND SOCIAL JUSTICE
303	WE USE LARGE SCALE SOCIOECONOMIC DATA TO PREDICT AND MITIGATE NEGATIVE IMPACTS OF ENERGY TRANSITIONS 
304	OPTIMIZING NUCLEAR POWER PLANT S ENVIRONMENTAL FACTORS THROUGH FUNCTIONAL DESIGN OF EXPERIMENTS
304	NUCLEAR POWER PLANTS RELY ON COOLING SYSTEMS TO ENSURE THE SAFE AND RELIABLE OPERATION OF THE NUCLEAR REACTOR
304	DURING OPERATION , THE REACTOR COOLANT PUMP , RCP , FUNCTIONS TO CIRCULATE DEMINERALIZED LIGHT WATER UNDER PRESSURE THROUGH THE REACTOR VESSEL AND LOOPS
304	THE RCP PROVIDES FORCED PRIMARY COOLANT FLOW TO REMOVE AND TRANSFER THE AMOUNT OF HEAT GENERATED IN THE REACTOR CORE
304	IN THIS STUDY , A SAMPLE OF CONTINUOUS VIBRATION SIGNAL DATA FROM AN RCP OF A NUCLEAR POWER PLANT WAS ANALYZED
304	THE CONTINUOUS SIGNAL WAS ACQUIRED APPROXIMATELY EVERY FIVE SECONDS AND VISUALIZED IN REAL TIME FOR TRENDING AND MONITORING
304	USING WAVELET FUNCTIONAL ANALYSIS , WE EXTRACT FUNCTIONAL PRINCIPAL COMPONENTS , FPCS , 
304	ESTABLISHING A RELATIONSHIP BETWEEN FPCS AND ENVIRONMENTAL FACTORS , THE VIBRATION SIGNALS WILL BE CONTROLLED IN AN OPTIMAL SHAPE
304	ENRE , ENERGY QUALITY , STATISTICS AND RELIABILITY 
304	ENSURE THE SAFE OPERATION OF A NUCLEAR POWER PLANT BY ANALYZING EQUIPMENT MONITORING DATA 
305	RENEWABLE ENERGY PATHWAYS TO CARBON NEUTRALITY IN CHINA
305	CHINA HAS ANNOUNCED AMBITIOUS CLIMATE POLICY GOALS OF REACHING PEAK CARBON EMISSIONS BY AND CARBON NEUTRALITY BY THIS PROCESS REQUIRES A LARGE INCREASE IN LOW CARBON RENEWABLE ENERGY AND COMPLEMENTARY INFRASTRUCTURE
305	WHILE THESE LONG TERM OBJECTIVES ARE CLEAR , THE DEPLOYMENT STRUCTURE , PACE , AND DISTRIBUTIONAL IMPACTS ARE UNCERTAIN
305	TO ADDRESS THIS GAP , WE DEVELOPED A POWER SYSTEM PLANNING AND OPERATION MODEL WITH A HIGH SPATIAL AND TEMPORAL RESOLUTION FOR DEPLOYING RENEWABLES , STORAGE SYSTEMS , AND TRANSMISSION LINES
305	WE ADAPTED THIS MODEL TO EVOLVING POWER SYSTEM CONDITIONS AND INPUT ASSUMPTIONS BY SEQUENTIALLY LINKING THE OUTPUTS OF EACH DECADE TO SIMULATE TECHNOLOGY VINTAGING MECHANISMS
305	THE COMBINED MODEL OUTPUTS ACROSS PERIODS IDENTIFY FEASIBLE AND EFFICIENT PATHWAYS FOR RENEWABLE DEPLOYMENT FROM TO ENRE , ENERGY CLIMATE ENRE , ELECTRICITY ENRE , ENERGY
305	THE OPTIMIZATION MODEL INCORPORATES HIGH SPATIAL LAND USE DATA TO IDENTIFY DEPLOYMENT IMPACTS
306	TRANSCONTINENTAL POWER POOLS FOR LOW CARBON ELECTRICITY
306	TRANSITION TO LOW CARBON ELECTRICITY IS CRUCIAL FOR MEETING GLOBAL CLIMATE GOALS
306	HOWEVER , GIVEN THE UNEVEN SPATIAL DISTRIBUTION AND TEMPORAL VARIABILITY OF RENEWABLE RESOURCES , IT IS CHALLENGING TO BALANCE THE SUPPLY AND DEMAND OF ELECTRICITY WHEN RELYING HEAVILY ON RENEWABLES
306	HERE , WE USE AN ELECTRICITY PLANNING MODEL TO EXAMINE WHETHER TRANSCONTINENTAL POWER POOLS HELP MEET GLOBAL ELECTRICITY DEMAND BY RENEWABLES
306	BY UTILIZING ONLY AVAILABLE SITES , RENEWABLES ARE ECONOMICALLY INFEASIBLE TO MEET OF GLOBAL DEMAND IN WITHOUT INTERNATIONAL ELECTRICITY TRADE
306	INTRODUCING TRANSCONTINENTAL POWER POOLS , HOWEVER , RENEWABLES ARE FEASIBLE TO MEET OF ELECTRICITY DEMAND , WHILE REDUCING THE COSTS BY ACROSS POWER POOLS
306	OUR RESULTS HIGHLIGHT THE POTENTIAL OF EXPANDING REGIONAL TRANSMISSION NETWORKS IN ACHIEVING DECARBONIZATION OF ELECTRICITY
306	ENRE , ENERGY CLIMATE ENRE , ELECTRICITY ENRE , ENVIRONMENT AND SUSTAINABILITY
307	RESILIENT PLANNING OF POWER SYSTEMS FUNDAMENTAL VALUE ANALYSIS
307	THIS PAPER ADDRESSES THE INCREASING VULNERABILITY OF POWER SYSTEMS TO EXTREME WEATHER AND CLIMATE EVENTS RESULTING FROM CLIMATE CHANGE
307	RESILIENCE OF THE POWER SYSTEM IS CRITICAL , AND OPTIMAL PLANNING REQUIRES A GRANULAR REPRESENTATION OF RISK RELATING TO EXTREMES
307	WE EXAMINE THE TRADE OFFS BETWEEN THE VARIABILITY OF NEW SOURCES OF SUPPLY AND DEMAND AND THE CODEPENDENCE OF EXISTING FOSSIL GENERATION INFRASTRUCTURE AND SUPPLY CHAINS
307	TO UNDERSTAND FUNDAMENTAL EXPOSURES OF THE SYSTEM TO EXTREMES AND THE RESILIENT SYSTEM MIX FOR FUTURE POWER SYSTEMS , WE DEVELOP A RISK AVERSE STOCHASTIC ELECTRICITY PLANNING MODEL ADAPTED FROM THE STATE OF THE ART GENX POWER SYSTEM PLANNING MODEL
307	OUR RESULTS PROVIDE INSIGHTS FOR POLICYMAKERS AND POWER SYSTEM PLANNERS TO DESIGN MORE RESILIENT POWER SYSTEMS
307	ENRE , ENERGY CLIMATE ENRE , ELECTRICITY ENRE , NATURAL RESOURCES
308	DRIVING THE RESIDENTIAL HEATING TRANSITION POLICY ASSESSMENT CONSIDERING PARAMETRIC UNCERTAINTY AND NEAR OPTIMAL SOLUTIONS
308	RESIDENTIAL HEATING ELECTRIFICATION VIA HEAT PUMPS WILL BE KEY TO ACHIEVING CLIMATE TARGETS AND MOVING AWAY FROM FOSSIL BASED HEATING SUPPLY
308	OUR STUDY ASSESSES THE IMPACT OF POLICIES , NAMELY A CARBON TAX AND A HEAT PUMP REBATE , ON RESIDENTIAL HEATING ELECTRIFICATION
308	TO DO SO , WE DETERMINE THE COST OPTIMAL DESIGN AND OPERATION OF RESIDENTIAL MULTI ENERGY SYSTEMS FOR DIFFERENT POLICY LEVELS AND EMISSIONS TARGETS
308	THE ANALYSIS ACCOUNTS FOR I , PARAMETRIC UNCERTAINTY AND II , UNCERTAINTY RELATED TO HUMAN DECISION MAKING BY I , PERFORMING SENSITIVITY ANALYSIS AND II , ASSESSING THE NEAR OPTIMAL FEASIBLE SOLUTION SPACE
308	RESULTS SUGGEST THAT INTRODUCING POLICIES INCREASES THE ROBUSTNESS OF THE TRANSITION TO HIGHLY ELECTRIFIED LOW CARBON HEATING
308	ENRE , ENERGY CLIMATE ENRE , ENERGY ENRE , ENVIRONMENT AND SUSTAINABILITY
309	COMPUTING EQUILIBRIUM AUTOMOTIVE TECHNOLOGY DECISIONS UNDER REGULATION
309	COMPUTATIONAL EQUILIBRIUM MODELS OF THE AUTOMOTIVE INDUSTRY ARE USED TO INFORM VEHICLE TECHNOLOGY STRATEGIES AND POLICIES BY UNDERSTANDING THE IMPACT OF PARTICULAR REGULATIONS ON AUTOMAKER COSTS AND TECHNOLOGY USE
309	HOWEVER , THE USE OF THESE MODELS IN PRACTICE HAS BEEN HINDERED BY , , HIGH COMPUTATIONAL TIME AND , , UNKNOWN PROPERTIES GOVERNING WHEN THE MODEL WILL SUCCESSFULLY SOLVE FOR VALID EQUILIBRIA
309	BY EXPLOITING PROPERTIES OF AUTOMAKERS PROFIT MAXIMIZATION PROBLEM AND DEPLOYING A MULTI STAGE SOLUTION APPROACH , THIS WORK IDENTIFIES IMPROVEMENTS THAT ACCELERATE SOLUTIONS AND GUARANTEE VALID EQUILIBRIUM SOLUTIONS GIVEN SUFFICIENT TIME
309	ENRE , ENERGY CLIMATE ENRE , ENVIRONMENT AND SUSTAINABILITY OPT , GLOBAL OPTIMIZATION 
310	PATHWAYS TO CARBON NEUTRALITY IN CALIFORNIA S HEAVY DUTY TRANSPORTATION SECTOR
310	CALIFORNIA HAS A GOAL OF REACHING NET ZERO GREENHOUSE GAS , GHG , EMISSIONS BY NEARLY OF THE STATE S GHG EMISSIONS COME FROM THE HEAVY DUTY TRANSPORTATION SECTOR
310	WE ASSESS DECARBONIZATION STRATEGIES USING TWO POLICY OPTIONS , ZERO EMISSION VEHICLE , ZEV , SALES MANDATES AND ACCELERATED RETIREMENT PROGRAMS
310	WE BUILD A DETAILED , BOTTOM UP FLEET TURNOVER MODEL PAIRED WITH AN EMISSIONS AND AIR QUALITY MODEL TO TRACK THE EVOLUTION OF THE VEHICLE FLEET AND ASSOCIATED CUMULATIVE HEALTH AND CLIMATE IMPACTS OF EACH POLICY
310	WE TRACK HEALTH IMPACTS BY RACE AND INCOME
310	WE USE SECOND HAND VEHICLE PRICES TO ESTIMATE THE COST OF RETIREMENTS AND IDENTIFY THE MOST COST EFFECTIVE POLICIES
310	WE FIND ZEV SALES MANDATES ARE INSUFFICIENT TO REACH CALIFORNIA S CLIMATE TARGETS , AND ACCELERATED RETIREMENT POLICIES TARGETING HEAVY HEAVY DUTY VEHICLES ARE MOST COST EFFECTIVE
310	ENRE , ENERGY CLIMATE ENRE , ENVIRONMENT AND SUSTAINABILITY TSL , FREIGHT TRANSPORTATION
310	THE MODEL AND RESULTS I WILL BE DISCUSSING RELY ON MANY DATA INPUTS , THOUGH NOT BIG DATA 
311	SYNERGIZING EMISSIONS REDUCTION AND ENERGY POVERTY MITIGATION , ASSESSING THE ROLE OF CARBON TAX REFUND POLICIES UNDER THE PARIS AGREEMENT AND SDGS
311	THIS STUDY EVALUATES WHETHER CARBON TAX REFUND POLICIES CAN SYNERGIZE ENERGY POVERTY REDUCTION WITH EMISSIONS REDUCTION
311	USING THE RICE EP MODEL , INCORPORATING ENERGY POVERTY AS A FACTOR , THE STUDY ASSESSES CHANGES IN GLOBAL TEMPERATURE , WELFARE , AND ENERGY POVERTY UNDER VARIOUS SCENARIOS
311	RESULTS SHOW THAT WHILE CARBON TAX REFUND POLICIES HELP TO REDUCE EMISSIONS AND ENERGY POVERTY , THE LOWEST INCOME GROUPS WILL STILL FACE INCREASED ENERGY POVERTY UNDER THE SCENARIO
311	A MODERATE EMISSION REDUCTION RATE CAN MITIGATE ENERGY POVERTY , BUT HIGH RATES EXACERBATE IT
311	MAJOR COUNTRIES SHOULD TAKE ON GREATER EMISSION REDUCTION RESPONSIBILITIES IN THE EARLY STAGES , WHILE LOW INCOME COUNTRIES CAN ADOPT RELAXED MEASURES INITIALLY AND STRICTER ONES LATER AS THEIR ECONOMIC AND TECHNOLOGICAL LEVELS IMPROVE
311	ENRE , ENERGY CLIMATE ENRE , ENVIRONMENT AND SUSTAINABILITY 
312	THE FUELS AND INDUSTRY INTEGRATED OPTIMIZATION MODEL , FINITO , 
312	THE EVOLUTION OF THE INDUSTRIAL SECTORS PLAYS A CRUCIAL ROLE ON MITIGATING CLIMATE CHANGE AND REACHING NET ZERO EMISSIONS TARGETS BY IN THE UNITED STATES YET DETAILED MODELING EFFORTS REMAIN SPARSE
312	THEREFORE , DISCUSSION ON INDUSTRIAL DECARBONIZATION STRATEGIES SHOULD CONSIDER ECONOMIC AND ENVIRONMENTAL OBJECTIVES AS WELL AS RELATIONS WITH FUEL AND POWER SECTORS
312	IN THIS PRESENTATION , WE DISCUSS THE FUELS AND INDUSTRY INTEGRATED OPTIMIZATION MODEL , FINITO , WHICH IS A SPATIALLY EXPLICIT , LONG TERM CAPACITY EXPANSION MODEL FOR THE INDUSTRIAL AND FUEL SUPPLY SECTORS
312	WE DEMONSTRATE BOTH THE METHODS OF AND IMPLICATIONS ON INDUSTRIAL , FUEL SUPPLY , AND POWER SECTOR EVOLUTION BY LINKING WITH THE REGIONAL ENERGY DEPLOYMENT SYSTEM , REEDS , , THE NATIONAL RENEWABLE ENERGY LABORATORY S FLAGSHIP ELECTRICITY CAPACITY EXPANSION MODEL
312	ENRE , ENERGY CLIMATE OPT , LINEAR AND CONIC OPTIMIZATION MSOM , SUPPLY CHAIN
313	CARBON AWARE DATA CENTER MANAGEMENT , TOWARDS SUSTAINABLE AND EFFICIENT OPERATIONS
313	WITH THE PROLIFERATION OF DATA CENTERS WORLDWIDE , THEIR ENVIRONMENTAL IMPACT HAS BECOME A PRESSING CONCERN
313	AS A RESULT , CARBON AWARE OPERATION FOR A GROUP OF DATA CENTERS HAS EMERGED AS A STRATEGIC APPROACH TO MINIMIZE EMISSIONS AND IMPROVE EFFICIENCY ACROSS MULTIPLE FACILITIES
313	THIS ABSTRACT PRESENTS A CARBON AWARE OPERATION FOR A GROUP OF DATA CENTERS TO REDUCE THEIR CARBON EMISSION BY WITHOUT ANY SIGNIFICANT INCREASE IN OPERATIONAL COSTS BY EXPLORING STRATEGIES SUCH AS GEO SHIFTING OF LOADS , RENEWABLE ENERGY INTEGRATION , ETC
313	BY ADOPTING CARBON AWARE PRACTICES AT THE GROUP LEVEL , DATA CENTERS CAN ACHIEVE SIGNIFICANT REDUCTIONS IN CARBON EMISSIONS , ENHANCE ENERGY EFFICIENCY , AND CONTRIBUTE TO A MORE SUSTAINABLE DIGITAL INFRASTRUCTURE
313	ENRE , ENVIRONMENT AND SUSTAINABILITY ARTIFICIAL INTELLIGENCE MACHINE LEARNING IN OPERATIONS
313	THIS ABSTRACT PRESENTS A CARBON AWARE OPERATION FOR A GROUP OF DATA CENTERS TO REDUCE THEIR CARBON E 
314	ESTIMATE SUPPLY CHAIN EMISSION USING LARGE LANGUAGE MODEL
314	ESTIMATING THE CARBON EMISSION EMBODIED IN THE SUPPLY CHAIN PRODUCT IS IMPERATIVE FOR UNDERSTANDING THE CLIMATE IMPACT AND ITS ACTIONS
314	THE US ENVIRONMENTALLY EXTENDED INPUT OUTPUT , USEEIO , MODEL PROVIDES A CARBON EMISSION FACTOR PER DOLLAR SPEND FOR A SET OF INDUSTRY SECTORS
314	THIS PROVIDES AN OPPORTUNITY TO CLASSIFY THE PRODUCT TRANSACTION DATA INTO ONE OF THE PREDEFINED USEEIO INDUSTRY CLASSES
314	BUT THE PRESENCE OF ACRONYM AND THE LIMITED WORDS IN THE TRANSACTION DATA POSES A CHALLENGE IN MAPPING AN EXPENSE DATA TO AN INDUSTRY SECTOR
314	TO ADDRESS THIS CHALLENGE , WE PROPOSE TO INCORPORATE THE ENTERPRISE SPECIFIC NOVEL EMBEDDINGS INTO THE NLP FOUNDATION MODEL LEVERAGING ENTERPRISE CONTEXTUAL DATA
314	THIS HELPS TO IMPROVE THE DISAMBIGUATION WITH INDUSTRY ABBREVIATIONS AND THE RESULTS SHOW AN IMPROVED ACCURACY IN COMPARABLE TO ANNOTATION BY DOMAIN EXPERTISE
314	ENRE , ENVIRONMENT AND SUSTAINABILITY ARTIFICIAL INTELLIGENCE SUPPLY CHAIN AND LOGISTICS IN PRACTICE
315	IDENTIFYING RELIABLE POLLUTION MANAGEMENT POLICIES USING EQUILIBRIUM PROGRAMS WITH CHANCE CONSTRAINTS
315	THIS PRESENTATION DEMONSTRATES HOW GAME THEORETIC PROGRAMS WITH CHANCE CONSTRAINTS CAN BE USED TO INFORM POLICIES FOR ENVIRONMENTAL REGULATIONS
315	THE IMPACTS OF ANTHROPOGENIC PHENOMENA , E G , ACID RAIN , VARY ACCORDING TO WEATHER PATTERNS OR CLIMATE CHANGE
315	THUS , RELIABILITY IS AN IMPORTANT ASPECT OF EFFECTIVE ENVIRONMENTAL REGULATIONS BECAUSE POLLUTION REDUCTION EFFECTIVENESS VARIES IN A SIMILAR MANNER
315	FORTUNATELY , THE DATA REVOLUTION HAS LED TO A PROLIFERATION OF REMOTE SENSING AND MONITORING INSTALLATIONS , WHICH HAS CREATED MORE DATA REGARDING THE NATURE OF THIS VARIABILITY
315	THIS ENABLES THE USE OF STOCHASTIC MATHEMATICAL MODELS TO ADDRESS POLICY QUESTIONS THAT WERE PREVIOUSLY ADDRESSED WITH DETERMINISTIC SIMPLIFICATIONS
315	THIS MODELING APPROACH IS APPLIED TO A HYPOTHETICAL , WATER QUALITY CREDIT MARKET FOR A RIVER BASIN IN METROPOLITAN WASHINGTON , D C
315	ENRE , ENVIRONMENT AND SUSTAINABILITY AUCTIONS AND MARKET DESIGN OPT , NONLINEAR OPTIMIZATION
315	BUILDING STOCHASTIC MODELS USING GREATER DATA AVAILABILITY 
316	HARNESSING INTERNET OF THINGS AND DATA ANALYTICS FOR A SUSTAINABLE AND INTELLIGENT SANITATION INDUSTRY
316	EXISTING INTELLIGENT SANITATION SYSTEMS ARE INEFFICIENT DUE TO A LACK OF A COMPREHENSIVE AND UNIFIED FRAMEWORK
316	THIS PAPER INTRODUCES THE FIRST GENERALISED IOT BASED SANITATION FRAMEWORK , SAN IOT , TO REVOLUTIONISE THE CURRENT STATE OF INTELLIGENT SANITATION , AS WELL AS THE FIRST GENERALISED DATA ANALYTICS FRAMEWORK , SAN IOT DA , TO FACILITATE DATA DRIVEN DECISIONS
316	THE GROUNDBREAKING FRAMEWORKS CAN BE SERVED AS A FOUNDATION FOR FUTURE RESEARCH INTO IOT BASED SANITATION SOLUTIONS
316	THIS PAPER DEVELOPS A WEB BASED APPLICATION TO PROCESS DATA FROM IOT LAYERS , DERIVE VALUE FROM SANITATION DATA , DELIVER VALUABLE INSIGHTS TO GLOBAL STAKEHOLDERS , AND OPTIMIZE RESOURCE MANAGEMENT
316	THIS PAPER PROVIDES RELEVANT STAKEHOLDERS WITH INSIGHTS INTO HOW TO USE IOT AND DATA ANALYTICS TO IMPROVE THE EFFICIENCY , SUSTAINABILITY , AND SAFETY OF THE SANITATION INDUSTRY
316	ENRE , ENVIRONMENT AND SUSTAINABILITY EMERGING TECHNOLOGIES AND APPLICATIONS INFORMATION SYSTEMS
317	FOREIGN OWNERSHIP AND ENVIRONMENTAL INNOVATION IN EMERGING ECONOMIES
317	DRAWING ON INSTITUTIONAL THEORY , WE DEVELOP A THEORETICAL FRAMEWORK TO INVESTIGATE HOW FOREIGN OWNERSHIP BENEFITS FIRMS ENVIRONMENTAL INNOVATION , A PHENOMENON THAT WAS LARGELY IGNORED BY MOST PREVIOUS STUDIES
317	OUR THEORETICAL FRAMEWORK WAS SUPPORTED BY LONGITUDINAL DATASETS THE PERIOD BETWEEN AND FROM CHINA
317	THE RESULTS SHOW THAT FOREIGN OWNERSHIP POSITIVELY AFFECTS ENVIRONMENTAL INNOVATION
317	MOREOVER , THE EMPIRICAL FINDINGS DEMONSTRATE THAT STATE INTERVENTION WEAKENS THE RELATIONSHIP BETWEEN FOREIGN OWNERSHIP AND ENVIRONMENTAL INNOVATION , WHEREAS INSTITUTIONAL DEVELOPMENT STRENGTHENS THE EFFECT OF FOREIGN OWNERSHIP ON ENVIRONMENTAL INNOVATION
317	BY HIGHLIGHTING THE SIGNIFICANT ROLE OF FOREIGN OWNERSHIP ON ENVIRONMENTAL INNOVATION IN EMERGING ECONOMIES THIS RESEARCH EXTEND MANAGEMENT LITERATURE
317	ENRE , ENVIRONMENT AND SUSTAINABILITY EMERGING TECHNOLOGIES AND APPLICATIONS TECHNOLOGY , INNOVATION MANAGEMENT AND ENTREPRENEURSHIP
318	VEHICLES ENVIRONMENTAL EFFICIENCY EVALUATION OF DIFFERENT REGIONAL , A COMBINATION OF LCA AND NETWORK DEA METHOD
318	THE EFFICIENCY OF THE SAME VEHICLE CAN VARY BY DIFFERENT REGION , POSING UNIQUE CHALLENGES AND IMPLICATIONS FOR ELECTRIC VEHICLES , EVS , AND PLUG IN ELECTRIC VEHICLES , PHEVS , WITHIN A COUNTRY
318	MOREOVER , MOST STUDIES REGARDED COUNTRIES AS A SINGLE UNITY , AND ASSESSING EFFICIENCY DIFFERENCES BETWEEN SIMILAR ENTITIES CANNOT BE WELL DONE BY SIMPLY USING LIFE CYCLE ANALYSIS , LCA , METHOD
318	TO PROVIDE SPECIFIC ENVIRONMENTAL EFFICIENCY OF VEHICLES OF EACH REGION , THIS STUDY USED DATA FROM CHINA AND SIMULATE THE DRIVING CONDITIONS OF CARS AT DIFFERENT TIMES AND IN DIFFERENT REGIONS FROM THREE ASPECTS , TEMPERATURE , DRIVING CONDITIONS AND DRIVING DISTANCE
318	A MORE EFFECTIVE METHOD , WHICH CONSISTED OF LCA AND NETWORK DATA ENVELOPMENT ANALYSIS , DEA , WAS INTEGRATED TO REFLECT THE PHASES OF VEHICLES PRODUCTION , OPERATION AND RECYCLE MORE CLEARLY
318	ENRE , ENVIRONMENT AND SUSTAINABILITY ENERGY , NATURAL RESOURCES AND THE ENVIRONMENT , ENRE , ENRE , ENERGY CLIMATE
319	HOW SUSTAINABLE ARE SHARED E SCOOTERS
319	INSIGHTS FROM A REAL WORLD APPLICATION AND MANAGERIAL IMPLICATIONS
319	E SCOOTERS ARE EMERGING TECHNOLOGIES AS A SHARED ECONOMY APPLICATION IN CITIES
319	IN THIS RESEARCH , WE INVESTIGATE ENVIRONMENTAL , ECONOMIC , AND SOCIAL IMPACTS OF SHARED E SCOOTERS AND PROVIDE KEY MANAGERIAL AND POLICY INSIGHTS FOR SUSTAINABLE APPLICATIONS OF E SCOOTER MOBILITY SOLUTIONS IN CITIES
319	WE DEVELOP A NOVEL A NOVEL LIFE CYCLE SUSTAINABILITY ASSESSMENT MODEL AND A SET OF UTILIZATION SCENARIOS DERIVED FROM A REAL WORLD APPLICATION IN CITY OF DOHA , QATAR
319	WE QUANTIFIED LIFE CYCLE SUSTAINABILITY IMPACTS ENCOMPASSING FROM REGIONAL AND GLOBAL VALUE CHAINS OF EACH LIFE CYCLE PHASE OF E SCOOTERS
319	THE RESULTS HIGHLIGHT THAT THE UTILIZATION OF E SCOOTERS HAS A PARAMOUNT IMPORTANCE FOR SUCCESSFUL APPLICATION OF SHARED E SCOOTERS
319	ENRE , ENVIRONMENT AND SUSTAINABILITY ENRE , ENERGY CLIMATE MSOM , SUSTAINABLE OPERATIONS
320	IMPACTS OF REGIONAL ALLOWANCE ALLOCATION DIFFERENCE ON CAPACITY PORTFOLIOS AND FACILITY LOCATION UNDER CAP AND TRADE
320	THIS STUDY PRESENTS A TWO STAGE MODELING APPROACH TO INVESTIGATE THE EFFECT OF ENVIRONMENTAL REGULATION IN THE FORM OF CARBON ALLOWANCE ALLOCATION UNDER CAP AND TRADE SYSTEM ON CAPACITY PORTFOLIO AND FACILITY LOCATION DECISIONS OF A FIRM
320	IN THIS CONTEXT , CARBON ALLOWANCE FOR A FACILITY HAS A REGIONAL DIFFERENCE AND IS ALLOCATED BASED SOME RULE , GRANDFATHERING , BENCHMARK , 
320	CARBON EMISSION OF A FACILITY INCLUDES ITS PRODUCTION EMISSION AND TRANSPORTATION EMISSION FROM PRODUCTION LOCATION TO MARKET
320	AS A RESPONSE , THE FIRM DECIDES FACILITY LOCATIONS AND CORRESPONDING CAPACITY PORTFOLIOS , WHICH INCLUDE CAPACITY SIZE AND THE TYPE OF TECHNOLOGY , DIRTY OR GREEN , 
320	UNCERTAINTIES LIKE CARBON PRICE AND CONSUMER DEMAND ARE CONSIDERED
320	L SHAPED METHOD IS IMPLEMENTED TO GET SIGHT INTO THE FIRM S OPTIMAL DECISIONS UNDER DIFFERENT ALLOCATION RULES
320	ENRE , ENVIRONMENT AND SUSTAINABILITY LOCATION ANALYSIS OPTIMIZATION , OPT , 
321	ENHANCING ENERGY FORECASTS IN PUBLIC TRANSIT USING ADVANCED MACHINE LEARNING TECHNIQUES AND HIGH LEVEL PLANNING METRICS
321	THIS RESEARCH REPRESENTS A GROUNDBREAKING APPROACH TO FORECASTING ENERGY USAGE IN PUBLIC TRANSIT SYSTEMS , SPECIFICALLY THE MASSACHUSETTS BAY TRANSPORTATION AUTHORITY , MBTA , URBAN RAIL NETWORK IN BOSTON
321	BUILDING ON PREVIOUS WORK THAT ACHIEVED A TEST ERROR IN ENERGY ESTIMATION , THIS STUDY UTILIZES HIGH LEVEL PLANNING METRICS TO MODEL LOW LEVEL VARIABLES , CONTRIBUTING SIGNIFICANTLY TO ENERGY EFFICIENCY
321	WE THEN ESTIMATED VECTOR AUTOREGRESSIVE MODELS AND LONG SHORT TERM MEMORY NETWORKS TO DEVELOP A ROBUST ENERGY FORECASTING MODEL
321	THIS STUDY OFFERS A GENERATIVE MODEL TRAINED TO MAP HIGH LEVEL METRICS TO MOVEMENT VARIABLES , PROVING ITS EFFECTIVENESS IN DRIVING ENERGY EFFICIENCY
321	ENRE , ENVIRONMENT AND SUSTAINABILITY MACHINE LEARNING IN OPERATIONS TSL , URBAN TRANSPORTATION PLANNING AND MODELING
322	DISAMBIGUATION OF PRODUCT EXPENSE DATA FOR CARBON EMISSION ESTIMATION
322	ESTIMATING THE CARBON EMISSION EMBODIED IN THE SUPPLY CHAIN PRODUCT IS IMPERATIVE FOR UNDERSTANDING THE CLIMATE IMPACT AND ITS ACTIONS
322	THE US ENVIRONMENTALLY EXTENDED INPUT OUTPUT , USEEIO , MODEL PROVIDES A CARBON EMISSION FACTOR PER DOLLAR SPEND FOR A SET OF INDUSTRY SECTORS
322	THIS PROVIDES AN OPPORTUNITY TO CLASSIFY THE PRODUCT TRANSACTION DATA INTO ONE OF THE PREDEFINED USEEIO INDUSTRY CLASSES
322	BUT THE PRESENCE OF ACRONYM AND THE LIMITED WORDS IN THE TRANSACTION DATA POSES A CHALLENGE IN MAPPING AN EXPENSE DATA TO AN INDUSTRY SECTOR
322	TO ADDRESS THIS CHALLENGE , WE PROPOSE TO INCORPORATE THE ENTERPRISE SPECIFIC NOVEL EMBEDDINGS INTO THE NLP FOUNDATION MODEL LEVERAGING ENTERPRISE CONTEXTUAL DATA
322	THIS HELPS TO IMPROVE THE DISAMBIGUATION WITH INDUSTRY ABBREVIATIONS AND THE RESULTS SHOW AN IMPROVED ACCURACY IN COMPARABLE TO ANNOTATION BY DOMAIN EXPERTISE
322	ENRE , ENVIRONMENT AND SUSTAINABILITY MSOM , SUSTAINABLE OPERATIONS ARTIFICIAL INTELLIGENCE
323	SCOPE BASED CORPORATE CARBON FOOTPRINT ACCOUNTING AND REPORTING , INSIGHTS FROM A REAL WORLD APPLICATION 
323	CARBON FOOTPRINT ACCOUNTING AND REPORTING HAVE GAINED TREMENDOUS INTEREST IN RECENT YEARS DUE TO THE PRESSING IMPACTS OF GLOBAL CLIMATE CHANGE
323	MANAGING AND REDUCING A COMPANY S CARBON FOOTPRINT REQUIRES COMPREHENSIVE SYSTEMS BASED APPROACHES WHERE COMPANIES REQUIRE TO MAP ALL THEIR VALUE CHAINS AND OPERATIONS , DEVELOP IMPORTANT PERFORMANCE METRICS , AND COMPOSITE INDICATORS , AND ADOPT INTEGRATED DATA MANAGEMENT AND VISUALIZATION APPROACHES
323	IN THIS RESEARCH , WE PRESENT A REAL WORLD APPLICATION OF CORPORATE CARBON FOOTPRINT ACCOUNTING AND REPORTING AND DEMONSTRATE THE BENEFITS OF USING ADVANCED CARBON FOOTPRINT ACCOUNTING METHODS FOR CALCULATING SCOPE EMISSIONS , THE DEVELOPMENT OF COMPOSITE SUSTAINABILITY INDICATORS , AND DATA VISUALIZATION
323	ENRE , ENVIRONMENT AND SUSTAINABILITY MSOM , SUSTAINABLE OPERATIONS DECISION ANALYSIS SOCIETY
324	MARKET OR GOVERNMENT REGULATION , IMPACT ON OPERATIONAL DECARBONIZATION
324	OPERATIONAL DECARBONIZATION IS THE OPTIMIZATION OF OPERATIONAL DECISIONS IN SUPPLY NETWORKS IN THE PRESENCE OF CARBON EMISSIONS PENALTIES
324	WE RE VISIT THE STYLIZED SINGLE LOCATION DETERMINISTIC DEMAND MODEL WITH EXOGENEOUS CARBON PRICES
324	IN PARTICULAR , WE STUDY THE IMPACT OF CARBON TAXES IMPOSED THROUGH GOVERNMENT REGULATIONS AND CARBON PRICING OF CONSUMERS IN THE MARKET ON OPERATIONAL DECISIONS WHEN DECISION MAKERS HAVE OBJECTIVES OTHER THAN THE TRADITIONAL PROFIT MAXIMIZATION MOTIVE
324	OUR FINDINGS FOCUS ON THE EFFICACY OF CARBON PRICING MECHANISMS IN REDUCING CARBON FOOTPRINTS AND HAVE SOCIETAL AS WELL AS POTENTIAL REGULATORY IMPLICATIONS
324	ENRE , ENVIRONMENT AND SUSTAINABILITY MSOM , SUSTAINABLE OPERATIONS SOCIALLY RESPONSIBLE AND SUSTAINABLE OPERATIONS
325	ESG , THE FEVER OF SUSTAINABLE BUSINESS
325	PREVIOUSLY , MORE PEOPLE WERE FAMILIAR WITH THE TERM CSR OR CORPORATE SOCIAL RESPONSIBILITY
325	HOWEVER , IN THE LAST FEW YEARS , THE ESG ISSUE HAS STARTED TO BE MORE WIDELY DISCUSSED
325	IN THIS SURVEY PROJECT , SEVERAL IMPORTANT POINTS WILL BE DISCUSSED REGARDING SUSTAINABLE BUSINESS , WHICH IS ONE OF THE DRIVERS IN THE DECISION TO ESG INVESTING
325	SEEING TECHNOLOGICAL DEVELOPMENTS AND PEOPLE S CONCERN FOR ENVIRONMENTAL SUSTAINABILITY , MANY LARGE COMPANIES HAVE LAUNCHED SUSTAINABLE BUSINESSES FOR THEIR PRODUCTS OR COMPANY ACTIVITIES
325	THE AIM IS TO ATTRACT INVESTORS TO TAKE PART AND INVEST IN THEIR BUSINESS , WHILE ALSO BEING ABLE TO BUILD A GOOD BRAND IMAGE AMONG THE PUBLIC AND BUILD PUBLIC AWARENESS
325	ENRE , ENVIRONMENT AND SUSTAINABILITY NEW PRODUCT DEVELOPMENT 
326	EVOLUTIONARY GAME THEORY MODEL FOR PREIGNITION WILDFIRE RISK MITIGATION
326	THE PREVENTION OF WILDFIRES IS ONLY POSSIBLE WITH THE COOPERATION OF AGENCIES IN TERMS OF GOVERNMENT , INSURANCE COMPANIES , AND LANDOWNERS
326	WE PROPOSE A WILDFIRE RISK ASSESSMENT MODEL USING GOVERNMENT SUBSIDIES AND LANDOWNERS EFFORTS TO PREVENT WILDFIRES IN LOW RISK AND HIGH RISK AREAS
326	THIS STUDY FOCUSES ON INTEGRATING THE FIRE BEHAVIOR MODEL INTO A GAME MODEL THAT MINIMIZES EXPECTED SOCIAL COSTS CONSISTENT WITH CONDITIONS FOR THE START AND SPREAD OF LARGE WILDFIRES
326	WE CALCULATE THE FAIR PREMIUM FOR WILDFIRE RISKS IN EACH REGION , WHICH IS ONE OF THE MOST IMPORTANT ISSUES FACING INSURANCE COMPANIES IN GENERAL
326	THE GAME MODEL DETERMINES THE OPTIMAL GOVERNMENT SUBSIDIES THAT COVER THE PROPORTIONAL COSTS OF FIRE INSURANCE TO REACH A SOCIAL OPTIMUM
326	A FUEL TREATMENT STRATEGY BY EXAMINING THE FACTORS OF WEATHER AND FUEL VARIABLES ON SURFACE FIRE INTENSITY IS ALSO DESIGNED
326	ENRE , ENVIRONMENT AND SUSTAINABILITY OPT , NONLINEAR OPTIMIZATION APPLIED PROBABILITY 
327	A HUMAN CENTERED APPROACH TO REGIONAL OFF GRID ELECTRIFICATION BUDGETING , THE COLOMBIAN CASE
327	THE UN S SEVENTH SUSTAINABLE DEVELOPMENT GOAL CALLS FOR CLEAN AND AFFORDABLE ENERGY TO BOOST SOCIAL MOBILITY IN DISADVANTAGED COMMUNITIES
327	THIS STUDY PROPOSES A HUMAN CENTERED APPROACH TO FACILITATE BUDGET ALLOCATION PLANNING IN RURAL ELECTRIFICATION
327	A BI OBJECTIVE OPTIMIZATION MODEL THAT EVALUATES DIFFERENT ALLOCATION STRATEGIES IN TERMS OF ENERGY COSTS AND HUMAN DEVELOPMENT IS PROPOSED
327	THE MODEL IS APPLIED TO THE COLOMBIAN PACIFIC COAST , AN IMPOVERISHED REGION WITH SEVERAL UNMET HUMAN NEEDS
327	OUR RESULTS INDICATE THAT WHEN BUDGET ALLOCATION IS MADE FOLLOWING THE MINIMUM ENERGY COST PARADIGM , ONLY A FEW COMMUNITIES BENEFIT AND DEVELOP
327	HOWEVER , WHEN BUDGET ALLOCATION IS BASED ON MAXIMIZING THE HUMAN DEVELOPMENT INDEX , ENERGY SERVICE IMPROVES IN MOST COMMUNITIES , INCREASING THEIR CHANCES FOR FUTURE DEVELOPMENT
327	ENRE , ENVIRONMENT AND SUSTAINABILITY PUBLIC SECTOR OR DIVERSITY , EQUITY , AND INCLUSION
328	FUTURE PROOFING SEPTIC SYSTEMS TO SEA LEVEL RISE , AN OPTIMIZATION APPROACH FOR ADAPTATION PLANNING
328	THIS STUDY EXAMINES THE ADAPTATION OF SEPTIC SYSTEMS TO SEA LEVEL RISE RISKS
328	A MIXED INTEGER LINEAR PROGRAMMING MODEL IS DEVELOPED WITH THE OBJECTIVES OF MINIMIZING TOTAL ADAPTATION COSTS AND MAXIMIZING THE RESILIENCE OF WASTEWATER DISPOSAL AND TREATMENT SYSTEMS
328	THE PROPOSED ADAPTATION STRATEGIES INCLUDE CONNECTING TO EXISTING SEWER NETWORK , CONSTRUCTING NEW CLUSTERS OF MICRO SEWER NETWORKS , AND BUILDING MOUND SYSTEMS
328	THE PROPOSED MODEL IS APPLIED TO ACTUAL DATA OBTAINED FROM MIAMI DADE COUNTY TO PROVIDE OPTIMAL DECISIONS REGARDING THE ADAPTATION OF SEPTIC SYSTEMS AND THE EXPANSION OF PUMP STATION CAPACITY IN A REAL LIFE SETTING
328	THE RESULTS DEMONSTRATE THE RELEVANCE OF THE MODEL IN COMPARISON TO THE COUNTY S ADAPTATION PLANS
328	ENRE , ENVIRONMENT AND SUSTAINABILITY PUBLIC SECTOR OR MSOM , SUSTAINABLE OPERATIONS
328	UTILIZING EXTENSIVE SENSOR AND LIDAR DATA TO DEVELOP DATA DRIVEN SOLUTIONS FOR CLIMATE ADAPTATION 
329	MANAGING PHYSICAL ASSETS , A SYSTEMATIC REVIEW AND A SUSTAINABLE PERSPECTIVE
329	PHYSICAL ASSET MANAGEMENT , PAM , HAS SHIFTED FROM THE NEGATIVE IMAGE OF ASSET FAILURE AND EXPENSIVE MAINTENANCE TO AN ENABLER OF SUSTAINABILITY THAT CREATES VALUE FROM EXTENDED LIFETIME AND RENEWED FUNCTIONS
329	WE FOLLOW A SYSTEMATIC REVIEWING PROCESS ENABLED BY TEXT ANALYTICS METHODS TO IDENTIFY THE APPROACHES TO BUILDING A SUSTAINABLE PERSPECTIVE FOR PAM
329	STATISTICS AND CRITICAL FEATURES EXTRACTED FROM OVER JOURNAL ARTICLES SUPPORT OUR KEY CONTRIBUTIONS AND INSIGHTS
329	WE PARTICULARLY EMPHASIZE THE RESEARCH FOOTPRINT AND TRENDS OF THE ASSET INTENSIVE CONSTRUCTION AND ENERGY SECTORS REPRESENTED AS BARRIERS AND ENABLERS OF SUSTAINABLE DEVELOPMENT
329	WE PROPOSE A CONCEPTUAL FRAMEWORK THAT ADOPTS AN ASSET WITHIN A SYSTEM PERSPECTIVE , RECOGNIZES THE LINKS BETWEEN THE STAKEHOLDERS , AND HOLISTICALLY INTEGRATES THE EXTRACTED RESEARCH TRENDS
329	ENRE , ENVIRONMENT AND SUSTAINABILITY SOCIALLY RESPONSIBLE AND SUSTAINABLE OPERATIONS ENRE , ENERGY
330	SUSTAINABILITY AWARE ASSET INVESTMENT OPTIMIZATION
330	SUSTAINABILITY AWARE ASSET REPLACEMENT HAS TAKEN A PROMINENT ROLE IN ENERGY UTILITIES , SUPPLY CHAIN , TRANSPORTATION , AND OTHER INDUSTRIES TO MEET THE CLEAN ENERGY AND ZERO EMISSIONS TARGETS SET BY THE PARIS AGREEMENT
330	THIS TALK INTRODUCES A NOVEL APPROACH FOR ASSET REPLACEMENT PLANNING USING SUSTAINABILITY SCORES TOGETHER WITH ASSET HEALTH METRICS
330	WE PRIORITIZE ASSETS TO BE REPLACED BASED ON FAILURE RISK AND CRITICALITY WHILE AIMING FOR THE HIGHEST OVERALL SUSTAINABILITY BENEFITS
330	OUR FOUR STEP APPROACH INCLUDES COMPUTING ASSET SUSTAINABILITY POSTURE , FORECASTING THIS POSTURE OVER A PLANNING HORIZON , ENHANCING THE ASSET RISK MATRIX WITH SUSTAINABILITY SCORES , AND OPTIMIZING ASSET INVESTMENT PLANNING BY INCORPORATING THESE SCORES
330	WE DEMONSTRATE THE APPLICATION OF OUR METHODOLOGY TO DISTRIBUTION TRANSFORMERS IN THE ENERGY UTILITIES INDUSTRY
330	ENRE , ENVIRONMENT AND SUSTAINABILITY SOCIALLY RESPONSIBLE AND SUSTAINABLE OPERATIONS OPTIMIZATION , OPT , 
330	LEVERAGING DATA DRIVEN DECISION MAKING AND FORECASTING , TO TRANSFORMER REPLACEMENTS 
331	THE IMPACT OF CORPORATE RESPONSES TO ENVIRONMENTAL SHAREHOLDER PROPOSALS ON FINANCIAL PERFORMANCE
331	SHAREHOLDER SPONSORED PROPOSALS THAT PETITION PUBLICLY HELD COMPANIES TO ADOPT ENVIRONMENTAL INITIATIVES HAVE BECOME COMMONPLACE IN RECENT YEARS
331	THE WAY IN WHICH FIRMS RESPOND TO SUCH PROPOSALS PLAYS A KEY ROLE IN EXPLAINING THE DIVERSITY OF OBSERVED RELATIONSHIPS BETWEEN CORPORATE ENVIRONMENTAL BEHAVIOR AND CORPORATE FINANCIAL PERFORMANCE
331	THIS STUDY , WHICH FOCUSES ON WITHDRAWN PROPOSALS , BUILDS UPON THE RESOURCE BASED VIEW , RBV , AND STAKEHOLDER MANAGEMENT THEORY
331	WE MERGE INFORMATION FROM MULTIPLE SOURCES TO ASSEMBLE A COMPREHENSIVE DATA SET , AND EMPIRICALLY INVESTIGATE THIS RELATIONSHIP , HIGHLIGHTING THE CONTINGENT ROLE OF THE FIRM S R D AND ADVERTISING ACTIVITIES
331	ENRE , ENVIRONMENT AND SUSTAINABILITY SOCIALLY RESPONSIBLE AND SUSTAINABLE OPERATIONS 
331	SOPHISTICATED TOOLS TO ASSESS HOW CORPORATE ENVIRONMENTAL BEHAVIOR AFFECTS FINANCIAL OUTCOMES 
332	THE EFFECTS OF ORGANIC WASTE BANS , AN ANALYSIS OF U S WASTE DISPOSAL FROM WE ESTIMATE THE EFFECTS OF ORGANIC WASTE BANS ON WASTE DIVERSION FROM LANDFILLS USING ANNUAL COUNTY AND STATE LEVEL WASTE DISPOSAL AND COMPOSTING DATA FROM U S STATES FROM TO THIS IS THE FIRST STUDY THAT EMPIRICALLY STUDIES THE EFFECT OF ORGANIC WASTE BANS
332	WE USE A SYNTHETIC CONTROLS DESIGN AND PLACEBO INFERENCE TO ESTIMATE THE STATISTICAL POWER OF THE DATASET
332	USING SYNTHETIC CONTROLS WE ESTIMATE THE TREATMENT EFFECTS AND COMPARE THEM AGAINST THE EXPECTED REGULATORY EFFECT
332	CONTRARY TO POLICYMAKERS EXPECTATIONS , WE FIND EVIDENCE OF A NULL EFFECT OF THE BANS ON TOTAL WASTE DIVERTED FROM LANDFILLS
332	OUR FINDINGS SUGGEST THAT CURRENT ORGANIC WASTE BANS MAY NOT EFFECTIVELY REDUCE WASTE DISPOSAL AS EXPECTED OR PROMOTE WASTE DIVERSION , NAMELY COMPOSTING , INDICATING A NEED FOR FURTHER RESEARCH ON ALTERNATIVE POLICY MECHANISMS
332	ENRE , ENVIRONMENT AND SUSTAINABILITY 
333	DOES INFORMATION MATTER , CONTESTS IN A COMPLEX STRUCTURE
333	CONSIDER A CONTEST CONDUCTED IN A TIER ORGANIZATION WHERE THE OWNER PROVIDES A WINNING PRIZE FOR BRANCHES TO COMPETE AND THE MANAGER OF EACH BRANCH OFFERS A REWARD TO MOTIVATE HIS AGENTS
333	THE STANDARD ECONOMIC THEORY PREDICTS THAT THE INFORMATION ON TOTAL WINNING PRIZE OR THE REWARD OFFERED TO THE OPPONENT AGENTS WOULD HAVE NO IMPACT ON THE EFFORT DECISIONS BY THE FOCAL AGENT
333	USING AN INCENTIVE ALIGNED LAB EXPERIMENT , HOWEVER , THE AUTHORS FIND THAT , , THE AGENTS ADJUST THEIR EFFORT BASED ON THEIR KNOWLEDGE ABOUT THE TOTAL WINNING PRIZE OR THE REWARD OFFERED TO THE OPPONENT AGENTS , , THE MANAGERS MODIFY THEIR REWARD UPWARD , DOWNWARD , WHEN EITHER , BOTH , OF THE INFORMATION IS REVEALED TO THE AGENTS
333	THESE BEHAVIORAL REGULARITIES ARE EXPLAINED BY A MODEL THAT INCORPORATES THE FAIRNESS CONCERNS , VERTICAL AND HORIZONTAL , INTO THE AGENT S UTILITY FUNCTION
333	FAIRNESS IN OPERATIONS BEHAVIORAL OPERATIONS MANAGEMENT DECISION ANALYSIS SOCIETY
334	DISCRETION TO ENCOURAGE INFORMATION ACQUISITION
334	HOW MUCH DISCRETION SHOULD A BIASED MANAGER GIVE TO AN EMPLOYEE WHEN THE LATTER HAS TO INCUR A COST TO ACQUIRE INFORMATION RELEVANT TO THE OPTIMAL ACTION PATH
334	WE SHOW THAT THE ANSWER DEPENDS ON THE NATURE OF THE TASK
334	IF THE TASK IS SUCH THAT THE EMPLOYEE EITHER EXERTS EFFORT OR NOT , THEN DISCRETION INCREASES WITH THE COST , UP TO THE POINT WHERE IT IS UNFEASIBLE TO PROVIDE INCENTIVES
334	IF THE TASK IS SUCH THAT THE COST OF EXERTING EFFORT INCREASES WITH THE EFFORT , THEN WHEN THERE IS SUFFICIENT DISAGREEMENT BETWEEN PARTIES , THE MANAGER PREFERS TO HEDGE BY LIMITING DISCRETION IN ORDER TO INSURE HERSELF AGAINST THE POSSIBILITY OF THE EMPLOYEE REMAINING UNINFORMED
334	OUR RESULTS PROVIDE GUIDANCE TO MANAGERS ON HOW MUCH DISCRETION TO GIVE DEPENDING ON THE TASK THEY FACE
334	FAIRNESS IN OPERATIONS BEHAVIORAL OPERATIONS MANAGEMENT DECISION ANALYSIS SOCIETY
335	INTERACTION OF FAIRNESS CONCERNS AND CHANNEL COMPETITION ON THE DYNAMIC PRICING STRATEGY IN A RETAIL PLATFORM
335	THE SUPPLIERS INCREASE THE RETAIL PRICES TO TRANSFER THE INCREMENT COSTS , HOWEVER , IT INDUCES THE INTER TEMPORAL FAIRNESS CONCERNS AMONG CONSUMERS AT THE SAME TIME
335	TO RAISE PRICES OR NOT IS STILL UNKNOWN , ESPECIALLY IN THE MULTI CHANNEL PLATFORM
335	THUS , WE EXPLORE THE INTERACTION OF CONSUMER FAIRNESS CONCERNS AND CHANNEL COMPETITION UNDER THREE CHANNEL STRATEGIES , RESELLING , STRATEGY R , , AGENCY SELLING , STRATEGY A , AND HYBRID CHANNEL , STRATEGY H , 
335	THE MOST INTERESTING RESULT IS THAT IN STRATEGY H , CONSUMER FAIRNESS CONCERNS BENEFITS BOTH THE SUPPLIER AND PLATFORM , WHILE IT ALWAYS HARMS BOTH OF THEIR PROFIT IN STRATEGY A AND ONLY BENEFITS THE SUPPLIER IN STRATEGY R
335	FAIRNESS IN OPERATIONS BEHAVIORAL OPERATIONS MANAGEMENT MSOM , SUPPLY CHAIN
335	THE DATA REVOLUTION INDUCES INTER TEMPORAL FAIRNESS CONCERNS WHICH IMPACTS OPERATION DECISIONS 
336	SHOULD I STOP OR SHOULD I GO , EARLY STOPPING WITH HETEROGENEOUS POPULATIONS
336	RANDOMIZED EXPERIMENTS OFTEN NEED TO BE STOPPED PREMATURELY DUE TO THE TREATMENT HAVING AN UNINTENDED HARMFUL EFFECT
336	EXISTING METHODS THAT DETERMINE WHEN TO STOP AN EXPERIMENT EARLY ARE TYPICALLY APPLIED TO THE DATA IN AGGREGATE AND DO NOT ACCOUNT FOR TREATMENT EFFECT HETEROGENEITY
336	IN THIS PAPER , WE STUDY THE EARLY STOPPING OF EXPERIMENTS FOR HARM ON HETEROGENEOUS POPULATIONS
336	WE FIRST ESTABLISH THAT CURRENT METHODS OFTEN FAIL TO STOP EXPERIMENTS WHEN THE TREATMENT HARMS A MINORITY GROUP OF PARTICIPANTS
336	WE THEN USE CAUSAL MACHINE LEARNING TO DEVELOP CLASH , THE FIRST BROADLY APPLICABLE METHOD FOR HETEROGENEOUS EARLY STOPPING
336	WE DEMONSTRATE CLASH S PERFORMANCE ON SIMULATED AND REAL DATA AND SHOW THAT IT YIELDS EFFECTIVE EARLY STOPPING FOR BOTH CLINICAL TRIALS AND A B TESTS
336	FAIRNESS IN OPERATIONS MSOM , HEALTHCARE 
336	OUR WORK ADDRESSES THE ETHICS AND FAIRNESS OF DATA COLLECTION IN LARGE RANDOMIZED EXPERIMENTS
337	TRAINING SCALABLE PERSONALIZATION POLICIES WITH CONSTRAINTS
337	PERSONALIZATION HAS ATTRACTED BROAD ATTENTION IN BOTH ACADEMIA AND INDUSTRY
337	WHILE MOST RESEARCH HAS FOCUSED ON TRAINING PERSONALIZATION POLICIES WITHOUT MANAGERIAL CONSTRAINTS , IN PRACTICE , MANY FIRMS FACE MANAGERIAL CONSTRAINTS WHEN IMPLEMENTING THESE POLICIES
337	FOR EXAMPLE , FIRMS MAY FACE VOLUME CONSTRAINTS ON THE MAXIMUM OR MINIMUM NUMBER OF ACTIONS THEY CAN TAKE
337	THEY MAY ALSO FACE SIMILARITY , FAIRNESS , CONSTRAINTS , THAT REQUIRE SIMILAR ACTIONS WITH DIFFERENT GROUPS OF CUSTOMERS
337	THESE CONSTRAINTS CAN INTRODUCE DIFFICULT OPTIMIZATION CHALLENGES , PARTICULARLY WHEN THE FIRM INTENDS TO IMPLEMENT PERSONALIZATION POLICIES AT SCALE
337	WE SHOW HOW RECENT ADVANCES IN LINEAR PROGRAMMING CAN BE ADAPTED TO THE PERSONALIZATION OF MARKETING ACTIONS
337	WE IMPLEMENT THE PROPOSED METHOD , AND COMPARE IT WITH BENCHMARK METHODS ON FEASIBILITY AND COMPUTATION SPEED
337	FAIRNESS IN OPERATIONS OPT , LINEAR AND CONIC OPTIMIZATION 
337	WE OFFER AN APPLICATION OF OR METHOD IN PERSONALIZATION
338	NEW ALGORITHMS FOR THE FAIR AND EFFICIENT ALLOCATION OF INDIVISIBLE CHORES
338	WE STUDY THE PROBLEM OF FAIRLY AND EFFICIENTLY ALLOCATING INDIVISIBLE CHORES AMONG AGENTS WITH ADDITIVE DISUTILITY FUNCTIONS
338	WE CONSIDER THE WIDELY USED ENVY BASED FAIRNESS PROPERTIES OF EF AND EFX , IN CONJUNCTION WITH THE EFFICIENCY PROPERTY OF FRACTIONAL PARETO OPTIMALITY , FPO , 
338	EXISTENCE , AND COMPUTATION , OF AN ALLOCATION THAT IS SIMULTANEOUSLY EF EFX AND FPO ARE CHALLENGING OPEN PROBLEMS , AND WE MAKE PROGRESS ON BOTH
338	WE SHOW EXISTENCE OF AN ALLOCATION THAT IS , I , EF FPO , WHEN THERE ARE THREE AGENTS , , II , EF FPO , WHEN THERE ARE AT MOST TWO DISUTILITY FUNCTIONS , , III , EFX FPO , FOR THREE AGENTS WITH BIVALUED DISUTILITY FUNCTIONS BR THESE RESULTS ARE CONSTRUCTIVE , BASED ON STRONGLY POLYNOMIAL TIME ALGORITHMS
338	WE ALSO INVESTIGATE NON EXISTENCE AND SHOW THAT AN ALLOCATION THAT IS EFX FPO NEED NOT EXIST , EVEN FOR TWO AGENTS
338	FAIRNESS IN OPERATIONS 
339	EXISTENCE AND COMPUTATION OF EPISTEMIC EFX ALLOCATIONS
339	FOR THE PROBLEM OF FAIRLY DIVIDING A SET OF INDIVISIBLE ITEMS AMONG AGENTS , ENVY FREENESS UP TO ANY ITEM , EFX , AND MAXIMIN FAIRNESS , MMS , ARE ARGUABLY THE MOST COMPELLING FAIRNESS CONCEPTS PROPOSED TILL NOW
339	UNFORTUNATELY , DESPITE SIGNIFICANT EFFORTS OVER THE PAST FEW YEARS , WHETHER EFX ALLOCATIONS ALWAYS EXIST IS STILL AN ENIGMATIC OPEN PROBLEM
339	FURTHERMORE , WE KNOW THAT MMS ALLOCATIONS ARE NOT GUARANTEED TO EXIST
339	THESE FACTS WEAKEN THE USEFULNESS OF BOTH EFX AND MMS DESPITE THEIR APPEALING CONCEPTUAL CHARACTERISTICS
339	WE PROPOSE AN ALTERNATIVE FAIRNESS CONCEPT CALLED EPISTEMIC EFX , EEFX , THAT IS INSPIRED BY EFX AND MMS
339	WE EXPLORE ITS RELATIONSHIP TO WELL STUDIED FAIRNESS NOTIONS AND PROVE THAT FOR ADDITIVE VALUATIONS , EEFX ALLOCATIONS ALWAYS EXIST AND CAN BE COMPUTED EFFICIENTLY
339	OUR RESULTS JUSTIFY THAT EEFX CAN BE AN EXCELLENT ALTERNATIVE TO EFX AND MMS
339	FAIRNESS IN OPERATIONS 
340	PERFORMANCE OF ACTIVE PORTFOLIO MANAGERS WHEN THE BENCHMARK IS NOT OBSERVED
340	IN THE FRAMEWORK OF ACTIVE PORTFOLIO MANAGEMENT , WE PROPOSE A METHODOLOGY TO EVALUATE THE PERFORMANCE OF ACTIVE PORTFOLIO MANAGERS WHEN THE BENCHMARK PORTFOLIO CANNOT BE EITHER OBSERVED OR DETERMINED BY THE AGENT PERFORMING THE ANALYSIS
340	THE SUGGESTED METHODOLOGY ASSESSES PERFORMANCE WITH RESPECT TO A COMBINATION OF FUNDS THAT MINIMIZES RESIDUAL RISK , AND , IT IS WELL SUITED FOR EVALUATING THE PERFORMANCE OF PENSION FUND MANAGERS IN DEFINED CONTRIBUTION PENSION SYSTEMS , ESPECIALLY THOSE OPERATING IN LATIN AMERICA
340	WE ALSO PROVIDE NUMERICAL RESULTS WHEN OUR METHODOLOGY IS APPLIED TO APPRAISE THE HISTORICAL PERFORMANCE OF THE PENSION FUND ADMINISTRATORS OF THE PERUVIAN PRIVATE PENSION SYSTEM
340	FINANCE APPLIED PROBABILITY OPTIMIZATION , OPT , 
341	EXTRA CONSTRAINTS OR MORE DIVERSIFICATION
341	, USING FACTOR PORTFOLIOS TO REDUCE ESTIMATION RISK IN PORTFOLIO OPTIMIZATION
341	UNDER THE EXPECTED LOSS FUNCTION OF KAN AND ZHOU , , , WE DETERMINE THE IMPACT ON OUT OF SAMPLE PERFORMANCE WHEN THE SAMPLE MEAN AND SAMPLE COVARIANCE MATRIX ARE USED TO CONSTRUCT THE OPTIMAL MEAN VARIANCE , MV , PORTFOLIO IN THE PRESENCE OF A SET OF LINEAR CONSTRAINTS ON PORTFOLIO WEIGHTS
341	THEN , WE PROPOSE A NOVEL PORTFOLIO RULE THAT COMBINES THE RISK FREE ASSET WITH TWO SAMPLE PORTFOLIOS WITH ZERO EXPECTED OUT OF SAMPLE COVARIANCE , A PORTFOLIO WITH MINIMUM VARIANCE AND FULL EXPOSITION TO THE FACTORS AND A PORTFOLIO WITH ZERO EXPOSITION TO THE FACTORS AND MAXIMUM EX ANTE PERFORMANCE
341	THE THEORETICAL IMPLICATION OF OUR RESULTS IS THAT AN OPTIMAL COMBINATION OF TWO UNCORRELATED PORTFOLIOS GENERATED BY ADDING CONSTRAINTS TO THE MV HAS AN IMPORTANT IMPACT IN REDUCING ESTIMATION RISK
341	FINANCE APPLIED PROBABILITY OPTIMIZATION , OPT , 
342	HIGH DIMENSIONAL SPARSE INDEX TRACKING PORTFOLIO SELECTION
342	DESIGNING AN INDEX TRACKING PORTFOLIO WITH LIMITED HISTORICAL DATA AND A LARGE NUMBER OF ASSETS IS CHALLENGING
342	WE EMPLOY PORTFOLIO CARDINALITY AND LEVERAGE RESTRICTIONS FOR A SPARSE DESIGN
342	MODELING NORM AND NORM OF ASSET POSITIONS AS CONSTRAINTS IN A QUADRATIC OPTIMIZATION PROBLEM , WE TUNE THE NORM THRESHOLDS USING CROSS VALIDATION IN SATISFYING SPARSITY AND LEVERAGE RESTRICTIONS PROBABILISTICALLY
342	OUR EMPIRICAL ANALYSES PROVIDE INSIGHTS ON SETTING THE THRESHOLDS AND LIMITS ON PORTFOLIO SPARSITY AND LEVERAGE , WHILE IMPROVING TRACKING PERFORMANCE FOR FIXED TARGET MEAN
342	FINANCE ARTIFICIAL INTELLIGENCE OPTIMIZATION , OPT , 
342	UTILIZE OPTIMIZATION AND MACHINE LEARNING TO EXTRACT INSIGHTS FROM SHORT TERM RAPID PHASE BIG DATA 
343	EXAMINING INDIVIDUALS FINANCIAL BEHAVIORS THE CONTRIBUTIONS OF PROACTIVE DECISION MAKING
343	BESIDES THE WELL ESTABLISHED INFLUENCE OF FINANCIAL LITERACY ON FINANCIAL BEHAVIORS , THE IMPACT OF PSYCHOLOGICAL DETERMINANTS IS CURRENTLY HIGHLY DEBATED
343	HOWEVER , UNDERSTANDING HOW SUCH DETERMINANTS LEAD TO INDIVIDUALS FINANCIAL BEHAVIORS IS STILL LIMITED
343	BY CONSIDERING PROACTIVE DECISION MAKING , A CONSTRUCT CAPABLE OF OPERATIONALIZING THE CONCEPT OF SELF NUDGING , WE PROVIDE VALUABLE INPUTS TO THE CURRENT DISCOURSE
343	OUR FINDINGS UNCOVER A TRAINABLE DECISION CENTRIC CONSTRUCT SHAPING SELECTED PSYCHOLOGICAL DETERMINANTS , FURTHER INFLUENCING INDIVIDUALS FINANCIAL BEHAVIORS , ALLOWING US TO CONTRIBUTE TO THE EMERGING PSYCHOLOGY LITERATURE IN BEHAVIORAL FINANCE
343	FINANCE BEHAVIORAL OPERATIONS MANAGEMENT 
344	ANALYZING HIGH FREQUENCY PRICE MOVEMENT WITH LIMIT ORDER BOOK IMBALANCE
344	WE IMPLEMENT SEVERAL MEASURES OF THE IMBALANCE OF THE LIMIT ORDER BOOK TO CONSTRUCT A MULTIDIMENSIONAL IMBALANCE INDEX , AND WE ANALYZE THE PRICE MOVEMENT USING HIGH FREQUENCY NASDAQ TRANSACTION DATA
344	WE COMBINE THE IMBALANCE INDEX WITH OUR PREVIOUSLY DEVELOPED RARE EVENTS DETECTION METHOD BASED ON D JOINT DISTRIBUTION OF RETURNS VOLUME TIME AND WE STUDY THE MEAN REVERSION BEHAVIOR OF THE PRICE MOVEMENT IN THE PROXIMITY OF RARE EVENTS
344	WE APPLY THE ANALYSIS TO A LARGE NUMBER OF EQUITIES TRADED ON NASDAQ AND WE PROVIDE A CLASSIFICATION OF THE PRICE MOVEMENT BEHAVIOR AND OPTIMAL FORECASTING HORIZON BASED ON EQUITY CHARACTERISTICS DETERMINED AT MARKET MICROSTRUCTURE LEVEL
344	FINANCE DATA MINING APPLIED PROBABILITY 
344	WE PRESENT ANALYTICAL METHODS FOR ANALYZING LARGE DATASETS TO PREDICT BEHAVIOR OF COMPLEX SYSTEMS 
345	THE DODD FRANK ACT AND HEDGE FUND OPERATIONAL RISK
345	IN THIS PAPER , WE EXAMINE THE IMPACT OF THE POST DODD FRANK CHANGE IN ON HEDGE FUND DISCLOSURE
345	OUR LASSO SELECTED INDICATORS FOR OPERATIONAL RISK ARE EFFECTIVE IN IDENTIFYING POTENTIAL NEGATIVE OUTCOMES FOR HEDGE FUNDS IN THE FUTURE
345	WE ALSO CONSTRUCT A MORE COMPREHENSIVE UNI DIMENSIONAL ADV BASED Ω SCORE TO PREDICT FUTURE APPRAISAL RATIO , STYLE ADJUSTED RETURN , LEVERAGE , AND ADVERSE LIQUIDATION EVENTS IN THE YEAR PANEL SAMPLE
345	OUR ANALYSIS INDICATES THAT THE AMENDED FORM ADV FILING IMPROVES THE ABILITY TO FORECAST FUTURE ADVERSE OPERATIONAL EVENTS COMPARED TO THE PRE DODD FRANK ERA
345	ADDITIONALLY , OUR ADV BASED Ω SCORE HAS A NEGATIVE ASSOCIATION WITH FUTURE FUND FLOWS , SUGGESTING THAT INVESTORS TAKE INTO ACCOUNT THE OPERATIONAL RISK EXPOSURE OF HEDGE FUNDS WHEN MAKING INVESTMENT DECISIONS
345	FINANCE DATA MINING ARTIFICIAL INTELLIGENCE
345	OUR DATA DRIVEN METHOD ENHANCES THE RISK ASSESSMENT OF HEDGE FUNDS
346	PREDICTING THE PRICE OF GOLD IN THE FINANCIAL MARKETS USING HYBRID MODELS
346	FORECASTING ACCURATE PRICES IN FINANCIAL MARKETS IS ONE OF THE MOST CHALLENGING ISSUES FOR MARKET PARTICIPANTS AND RESEARCHERS
346	THE USE OF TIME SERIES FORECASTING MODELS SUCH AS ARIMA , TECHNICAL ANALYSIS VARIABLES INDICATING TRADER BEHAVIOR , AND PSYCHOLOGICAL FACTORS CAN HELP TO CREATE A MORE ACCURATE MODEL
346	BY COMBINING THESE FACTORS WITH A STEPWISE REGRESSION AND NEURAL NETWORK , A HYBRID MODEL CAN BE CREATED FOR PREDICTING THE PRICE OF GOLD IN INTERNATIONAL FINANCIAL MARKETS
346	THIS HYBRID MODEL , CALLED ARIMA STEPWISE REGRESSION NEURAL NETWORK , COULD BE USED TO FORECAST STOCKS , COMMODITIES , CURRENCY PAIRS , AND OTHER FINANCIAL MARKET INSTRUMENTS
346	THE HYBRID MODEL OUTPERFORMS TIME SERIES , REGRESSION , AND STEPWISE REGRESSION MODELS IN TERMS OF ACCURACY
346	THE STUDY COULD HELP TRADERS IN FINANCIAL MARKETS MAKE BETTER DECISIONS BASED ON ACCURATE PRICE PREDICTIONS
346	FINANCE DATA MINING OPT , MACHINE LEARNING
347	PREDICTING THE STOCK MARKET RETURN USING TRANSFORMERS AND TIME EMBEDDINGS VIA NEWS SENTIMENT AND TECHNICAL INDICATORS
347	FINANCIAL TIME SERIES ARE HIGH FREQUENCY AND HIGH NOISE , MAKING IT DIFFICULT TO MAKE ACCURATE PREDICTIONS , BUT A SUCCESSFUL PREDICTION CAN MAKE A SIGNIFICANT CONTRIBUTION TO ITS CONTINUED DEVELOPMENT
347	IN THIS PAPER , TRANSFORMER NEURAL NETWORKS WITH SELF ATTENTION MECHANISMS ARE UTILIZED FOR PREDICTING S P RETURNS , HOWEVER , SINCE TRANSFORMER ARCHITECTURE CAN T EXTRACT TEMPORAL DEPENDENCIES FROM TIME SERIES DATA , TIME EMBEDDINGS ARE USED AS AN EMBEDDING LAYER TO CAPTURE THE TEMPORAL ORDER OF STOCK PRICES
347	A COMBINATION OF TECHNICAL INDICATORS AND NEWS SENTIMENTS IS USED IN THIS MODEL
347	THE NEWS SENTIMENT IS EXTRACTED USING MACHINE LEARNING TECHNIQUES THROUGH A FINANCIAL MARKET ADAPTED BERT MODEL
347	OUR RESULTS SHOW THAT TRANSFORMER NEURAL NETWORKS WITH TIME EMBEDDING HAS THE HIGHEST PREDICTION ACCURACY COMPARED TO THE PREVIOUS DEEP LEARNING SEQUENCE MODELS
347	FINANCE DATA MINING 
348	RESEARCH ON EARLY WARNING OF NON PERFORMING LOANS OF SMALL AND MICRO ENTERPRISES VIA LAD
348	IN ORDER TO SOLVE THE PROBLEM OF SMALL AND MICRO ENTERPRISES , SMES , LOAN DIFFICULTY , CHINESE MAJOR BANKS HAVE DEVELOPED SOME VERY RELAXED MICRO LOAN BUSINESS UNDER THE GUIDANCE OF THE POLICY
348	THESE BUSINESSES HELP THE VIGOROUS DEVELOPMENT OF SMES , WHILE BRING THE PROBLEM OF NON PERFORMING LOAN RATIO INCREASING YEAR BY YEAR
348	AND THIS PROBLEM HAS BECAME PARTICULARLY ACUTE SINCE , DUE TO THE INFLUENCE OF COVID TO SOLVE THIS , WE ANALYZE THE APPLICATION DATA OF THE SMES APPROVED FOR ONLINE LOANS IN A BANK IN , BY LOGICAL ANALYSIS OF DATA , LAD , , TO EXCAVATE THE PATTERN CHARACTERISTICS OF SMES WITH NON PERFORMING LOANS AFTER THE EPIDEMIC
348	THESE PATTERNS HELP BANKS TO IMPROVE THE CREDIT RISK ASSESSMENT MECHANISM AND THEIR EARLY WARNING ABILITY AGAINST THE FORCE MAJEURE FACTORS LIKE EPIDEMICS
348	FINANCE DATA MINING 
349	HOW BAD IS MYOPIA FOR A MEAN VARIANCE INVESTOR
349	THE MEAN VARIANCE FRAMEWORK IS WIDELY USED IN PORTFOLIO SELECTION BUT OFTEN OVERLOOKS THE INVESTMENT HORIZON
349	CURRENT INVESTMENT PRACTICES RELY ON MYOPIC MEAN VARIANCE APPROACHES THAT NEGLECT LONG TERM CONSIDERATIONS
349	EXISTING ALGORITHMS SOLVE SINGLE PERIOD MEAN VARIANCE PROBLEMS AND EXTEND THE SOLUTION OVER TIME
349	THIS PAPER CONTRIBUTES TO THE EXISTING RESEARCH BY INCORPORATING A TIME DIMENSION
349	WE COMPARE THE OUT OF SAMPLE PERFORMANCE OF THE DYNAMIC MEAN VARIANCE STRATEGY WITH MYOPIC STRATEGIES AND THREE N TYPE STRATEGIES
349	THE RESULTS DEMONSTRATE THAT THE DYNAMIC MEAN VARIANCE STRATEGY OUTPERFORMS THE MYOPIC APPROACH IN OUT OF SAMPLE SCENARIOS
349	ADDITIONALLY , WE HIGHLIGHT THE BENEFITS OF OPTIMIZATION IN A DYNAMIC CONTEXT COMPARED TO NAIVE DIVERSIFICATION
349	FINANCE DATA , OR , AND SOCIAL JUSTICE 
350	DO HOMEOWNERS CARE ABOUT SUSTAINABILITY
350	WE COMPILE A COMPREHENSIVE DATASET CONTAINING OF ALL RESIDENTIAL PROPERTY TRANSACTIONS IN THE UK FROM TO , AND PROVIDE LARGE SCALE EVIDENCE THAT HOMEOWNERS DERIVE BOTH PECUNIARY AND NON PECUNIARY BENEFITS FROM THE ENERGY EFFICIENCY OF THEIR DWELLINGS
350	HOMEOWNERS PRICE ENERGY EFFICIENCY BASED ON THE EXPECTED UTILITY SAVINGS AND ON THEIR ABILITY TO RECOUP THEIR INVESTMENTS
350	THE MARKET USES A SOCIAL DISCOUNT RATE , SDR , OF TO VALUE INVESTMENTS IN SUSTAINABILITY
350	HOMEOWNERS WHO PURCHASE GREENER DWELLINGS PAY A PREMIUM IN EXCESS OF THE PRESENT VALUE OF FUTURE ENERGY SAVINGS
350	WE OBSERVE A COMMENSURATE INCREASE IN PROPORTION OF ENERGY UPGRADES ACROSS MARKET SEGMENTS IMPACTED AND NOT IMPACTED BY REGULATION , BUT ABSENCE OF A PRICE IMPACT
350	THIS SUGGESTS THAT GOVERNMENT INTERVENTIONS FACILITATED SUSTAINABLE DEVELOPMENT THROUGH AN INDIRECT CHANNEL
350	FINANCE ENRE , ENVIRONMENT AND SUSTAINABILITY 
351	MODERN PANDEMIC CRISES AND DEFAULT RISK , A WORLDWIDE EVIDENCE
351	THIS PAPER EXAMINES THE RELATIONSHIP BETWEEN MODERN HEALTH PANDEMIC CRISES AND FINANCIAL STABILITY
351	SPECIFICALLY , IT COLLECTS DATA ON , FIRMS IN COUNTRIES , OR REGIONS , DURING FIVE MODERN PANDEMIC CRISES , SARS , , , H N , , , MERS , , , EBOLA , , , AND ZIKA , , , AND FINDS THAT PANDEMIC CRISES SIGNIFICANTLY INCREASE THE DEFAULT RISK OF ENTERPRISES
351	FURTHER ANALYSIS SHOWS THAT FORMAL AND INFORMAL INSTITUTIONS ACTED AS A CUSHION AGAINST THE PANDEMIC CRISIS
351	THIS PAPER ADDRESSES THE HITHERTO INADEQUACY OF COVID RELATED DATA
351	IN ADDITION , THIS PAPER ARGUES THAT GOVERNMENTS SHOULD BUILD SOUND STATE INSTITUTIONS TO WITHSTAND MACROECONOMIC SHOCKS AND HIGHLIGHTS THE HETEROGENEITY OF DEFAULT RISK FOR ENTERPRISES OPERATING IN COUNTRIES WITH DIFFERENT INSTITUTIONS
351	FINANCE HEALTH APPLICATIONS SOCIETY 
352	STRATEGIC LIQUIDITY PROVISION IN UNISWAP V 
352	UNISWAP IS THE LARGEST DECENTRALIZED EXCHANGE FOR DIGITAL CURRENCIES
352	IN UNISWAP V , LIQUIDITY PROVIDERS , LPS , CAN SELECTIVELY ALLOCATE LIQUIDITY TO TRADES THAT OCCUR WITHIN SPECIFIC PRICE INTERVALS
352	WHILE PRICES REMAIN IN THAT INTERVAL , LPS EARN FEE REWARDS PROPORTIONALLY TO THE AMOUNT OF LIQUIDITY ALLOCATED
352	THIS INDUCES THE PROBLEM OF STRATEGIC LIQUIDITY PROVISION , SMALLER INTERVALS RESULT IN HIGHER CONCENTRATION OF LIQUIDITY AND LARGER REWARDS WHEN PRICES REMAIN IN THE INTERVAL , BUT WITH HIGHER RISK AS PRICES MAY EXIT INTERVALS WHERE LIQUIDITY IS ALLOCATED AND THUS FAIL TO EARN REWARDS
352	DYNAMICALLY RE ALLOCATING LIQUIDITY CAN MITIGATE THESE LOSSES , BUT AT A COST , AS TRADERS MUST EXPEND GAS FEES TO DO SO
352	WE FORMALIZE THE DYNAMIC LIQUIDITY PROVISION PROBLEM AND PROVIDE AN OPTIMIZATION FRAMEWORK TO MAXIMIZE LP EARNINGS FOR A GENERAL CLASS OF LP STRATEGIES
352	FINANCE MACHINE LEARNING FOR OPTIMIZATION EMERGING TECHNOLOGIES AND APPLICATIONS 
352	OUR WORK USES HISTORICAL PRICE DATA TO INFORM THE LP EARNING OPTIMIZATION FRAMEWORK WE PROVIDE 
353	HOW DOES BLOCKCHAIN ENABLED GOVERNANCE CONFIGURATION ENHANCE FINANCING CREDIBILITY
353	THIS PAPER HIGHLIGHTS THE ROLE OF BLOCKCHAIN IN ADDRESSING THE TRUST CRISIS IN SUPPLY CHAIN FINANCE , SCF , 
353	WHILE PREVIOUS RESEARCH HAS ACKNOWLEDGED BLOCKCHAIN AS A RESPONSE TO TRUST ISSUES , LIMITED STUDIES HAVE EXPLORED ITS SPECIFIC CONTRIBUTIONS
353	DRAWING ON GOVERNANCE THEORY , WE INVESTIGATE THE RELATIONSHIP BETWEEN BLOCKCHAIN AND SCF THROUGH MULTIPLE CASE STUDIES
353	WE PROPOSE THAT BLOCKCHAIN ALONE DOES NOT AUTOMATICALLY GENERATE TRUST
353	TRUST IS ESTABLISHED THROUGH THE CONFIGURATION OF VARIOUS GOVERNANCE MECHANISMS , AND DERIVED FROM TWO MAIN FACTORS , CODIFIABILITY AND VERIFIABILITY
353	WHEN BOTH CODIFIABILITY AND VERIFIABILITY ARE HIGH , BLOCKCHAIN GOVERNANCE TENDS TO DOMINATE
353	WHEN ONLY ONE FACTOR IS HIGH , A CONFIGURATION OF BLOCKCHAIN GOVERNANCE AND RELATIONAL GOVERNANCE EMERGES
353	WHEN BOTH FACTORS ARE LOW , CONTRACTUAL GOVERNANCE PROVES TO BE EFFICIENT
353	FINANCE MSOM , SUPPLY CHAIN 
354	GRAPH NEURAL NETWORK FOR ESTIMATING BOND RETURNS
354	NETWORKS ARE UBIQUITOUS IN FINANCIAL SYSTEMS
354	HOLDING SIMILAR PORTFOLIOS FORMS IMPLICIT NETWORK CONNECTIONS BETWEEN ASSETS
354	THIS PAPER TURNS THE INSTITUTIONAL BOND HOLDING , EMAXX , INTO THIS TYPE OF NETWORK AND DEVELOPS AN ADVANCED TEMPORAL BIPARTITE GRAPH NEURAL NETWORK , TBGNN , MODEL TO CAPTURE VALUABLE INFORMATION FROM CONNECTIONS FOR CORPORATE BOND PRICING BR OUR BOND NETWORKS AND ASSOCIATED MODEL HAVE TWO ADVANTAGES , DEMONSTRATE THE NETWORKS OF COMMON BOND HOLDINGS EXPLAIN EXCESSIVE RETURNS AND PREDICT THE FUTURE BOND RETURNS
354	RESULTS SHOW THAT OUR MODEL CAN EXPLAIN ABOUT OF THE IN SAMPLE RETURN VARIATION , WITH AT LEAST IMPROVEMENT COMPARED TO BENCHMARKS
354	OVERALL , OUR FINDING STRONGLY SUGGESTS THAT INCORPORATING NETWORK ECONOMICALLY AND HIGHLY STATISTICALLY IMPROVES FUTURE BOND RETURN PREDICTION AND SUCH IMPACTS ARE ABOVE AND BEYOND PRICING FACTORS
354	FINANCE OPT , MACHINE LEARNING DATA MINING
355	FACTOR GLUT IN ASSET PRICING AND DODGING A ZILLION REGRESSIONS
355	THE ISSUE OF THE ZOO OF FACTORS HAS GARNERED MUCH ATTENTION IN RECENT YEARS , EG , COCHRANE , , JF , , BECAUSE OF THE PROLIFERATION OF PROPOSED FACTORS FOR EXPLAINING ASSET , ESPECIALLY STOCK , RETURNS
355	THE PRINCIPAL QUESTION THAT WE ANSWER IS , EVEN WHEN THE NUMBER OF POTENTIAL TEST FACTORS IS LARGE , CAN WE IDENTIFY THE BEST FACTORS THAT ENTER THE STOCHASTIC DISCOUNT FACTOR
355	WE DEVELOP ASSET PRICING AND ECONOMETRIC APPROACHES WITH THREE DESIRABLE FEATURES
355	FIRST , THE REALITIES OF BID ASK SPREADS IN PRICES AS WELL AS SHORT SALE CONSTRAINTS ARE ACCOMMODATED
355	SECOND , STOCHASTIC DISCOUNT FACTORS ARE STRICTLY POSITIVE
355	THIRD , THE APPROACH IS DISCIPLINED BY THE ABSENCE OF UNREASONABLY HIGH REWARDS FOR RISK
355	WE IDENTIFY WHICH , IN ADDITION TO A CONSTANT FACTOR , IS THE BEST ONE FACTOR , THE BEST TWO FACTORS , THE BEST THREE FACTORS , , THE BEST TEN FACTORS , ETC
355	FINANCE OPT , MACHINE LEARNING OPT , INTEGER AND DISCRETE OPTIMIZATION
355	BIG DATA IN FINANCE 
356	A HEURISTIC APPROACH TO LIQUIDITY MANAGEMENT AT ANT GROUP S GLOBAL CURRENCY NETWORK
356	ANT S INTERNATIONAL BUSINESS GROUP , IBG , CURRENTLY MANAGES A GLOBAL FOREIGN EXCHANGE , FX , AND LIQUIDITY NETWORK TO SUPPORT ITS CROSS BORDER PAYMENT AND MONEY TRANSFER BUSINESSES
356	THE NETWORK CONSISTS OF A HUB AND SPOKE STRUCTURE , WHERE COUNTRY LEVEL ACCOUNTS ARE CONNECTED TO AND FULFILL CASHFLOW REQUESTS ARISING FROM THE LOWER REGIONAL LEVEL
356	BASED ON FORECASTS , THE NETWORK NEEDS TO MAKE DAILY DECISIONS ON FUND RE BALANCING IN EACH COUNTRY LEVEL ACCOUNT , AS WELL AS ROUTE PICKING IN REAL TIME FOR EACH REQUEST , WHERE DIFFERENT OPTIONS MAY CARRY DISTINCT LEVELS OF TIMELINESS , FAILURE RATE AND COST
356	THIS TALK BRIEFLY DESCRIBES OUR PIONEER SOLUTION TO THIS PROBLEM WITH HEURISTICS
356	A FEW FUTURE WORK DIRECTIONS ARE DISCUSSED
356	FINANCE OPT , NETWORK OPTIMIZATION PRACTICE 
356	OUR SUPERB FORECAST ACCURACY RELIES HEAVILY ON THE MASSIVE AMOUNT OF CUSTOMER DATA NOW AVAILABLE
357	OPTIMAL PORTFOLIO EXECUTION STRATEGIES UNDER CHANCE CONSTRAINTS ON CAPITAL RATIO REQUIREMENT
357	WE INVESTIGATE THE OPTIMAL PORTFOLIO LIQUIDATION PROBLEM UNDER CAPITAL ADEQUACY REQUIREMENTS
357	IN THIS SETTING , SELLING RISKY ASSETS INDUCES TEMPORARY AND PERMANENT PRICE IMPACTS WHICH NEED TO BE CONSIDERED
357	WE FORMULATE THIS PROBLEM WITH CHANCE CONSTRAINTS FOR THE REGULATORY REQUIREMENTS
357	WE PRESENT A CONSERVATIVE REFORMULATION FOR THE PROBLEM AND ESTABLISH SUFFICIENT CONDITIONS FOR ITS CONVEXITY
357	OUR STUDY SHOWS THAT IN GENERAL THE OPTIMAL PORTFOLIO LIQUIDATION STRATEGY UNDER THE CAPITAL RATIO REQUIREMENT CONSTRAINTS DIFFERS FROM THE OPTIMAL STRATEGY IN THE ABSENCE OF THE CONSTRAINTS
357	FINANCE OPT , OPTIMIZATION UNDER UNCERTAINTY COMPUTING SOCIETY
357	THE DATA REVOLUTION CAN ASSIST IN MODEL VALIDATION AND THE EVALUATION OF VARIOUS STRATEGIES
358	PERSONALIZED FINANCIAL PLANNING WITH TAX ON AGGREGATE NET GAIN
358	PERSONALIZED FINANCIAL PLANNING REQUIRES THE MANAGEMENT OF BOTH ASSETS AND LIABILITIES BECAUSE MANY INDIVIDUAL INVESTORS NEED TO CONSIDER DEBT SUCH AS MORTGAGES
358	THEREFORE , PERSONALIZED MODELS ARE FORMULATED AS ASSET LIABILITY MANAGEMENT PROBLEMS
358	IN THIS STUDY , WE FOCUS ON CAPITAL GAINS TAX , WHICH IS CRITICAL FOR INDIVIDUAL INVESTORS IN PRACTICE
358	WE PROPOSE A MODEL BASED ON ASSET LIABILITY MANAGEMENT THAT FINDS THE OPTIMAL ALLOCATION WHILE CONSIDERING TAX ON AGGREGATE NET GAIN
358	THE MODEL PROVIDES MUCH FLEXIBILITY IN SETTING TAX DETAILS SUCH AS ASSET GROUPS , TAX EXEMPT AMOUNT , AND TAX RATE
358	BACKTEST SHOWS THAT TAX OPTIMIZATION RESULTS IN MORE DIVERSIFIED PORTFOLIOS DUE TO THE REDUCED UPSIDE FROM AGGREGATE TAX ON HIGH GAIN
358	FINANCE OPTIMIZATION , OPT , OPT , OPTIMIZATION UNDER UNCERTAINTY
359	SELECTIVE HEDGING POLICIES COMMODITY FIRMS , MODELS AND EVIDENCE
359	COMMODITY FIRMS AND THEIR HEDGING ACTIVITIES ARE A PROMINENT TOPIC OF INTEREST IN FINANCIAL ECONOMICS
359	ADDING TO THE CURRENT WAVE OF ATTENTION , THIS STUDY ADVANCES TWO THEORETICAL OPTIMIZATION MODELS GUIDED BY I MARKET DEPTH I , AS A PROXY FOR HEDGING DEMAND , AND I LIQUIDITY I TO , , DETECT AND SELECT THE MOST GENUINELY RELATED AND VIABLE COMMODITY FUTURES PERTINENT TO THE PRICE MOVEMENT OF COMMODITY COMPANIES TRADED IN THE STOCK MARKET , AND , , ELUCIDATE I WHEN I AND I HOW I THESE OPTIMAL SEARCH STRATEGIES CAN ENHANCE AND AFFECT HEDGING POSITIONS OF INVESTORS
359	LIKEWISE , WE EMPIRICALLY DOCUMENT THE JOINT DYNAMIC BEHAVIOR OF THESE GROUPS OF ASSETS WHILE ASSESSING THE EFFECTS OF INCLUDING AN I OPTIMAL I NUMBER OF HEDGING INSTRUMENTS
359	OUR INSIGHTS ARE VALUABLE FOR CORPORATE HEDGING , AND THIS WORK CARRIES WORTHWHILE IMPLICATIONS FOR PORTFOLIO MANAGEMENT UNDERTAKEN BY INSTITUTIONAL INVESTORS
359	FINANCE OPTIMIZATION , OPT , OPT , OPTIMIZATION UNDER UNCERTAINTY
359	AFTER DEVELOPING TWO THEORETICAL OPTIMIZATION MODELS , I HAVE TESTED THEM USING FINANCIAL DATA 
360	CVAR WITH RISK APPETITES , A NEW TAIL RISK MEASURE AND ITS APPLICATION IN PORTFOLIO OPTIMIZATION
360	CONDITIONAL VALUE AT RISK , CVAR , IS A WIDELY RECOGNIZED TAIL RISK MEASURE USED IN PORTFOLIO OPTIMIZATION
360	HOWEVER , IT FAILS TO DISTINGUISH THE RISK APPETITES OF DIFFERENT INDIVIDUALS SINCE IT GENERATES THE SAME PORTFOLIO FOR ALL
360	THEREFORE , WE PROPOSE A NEW TAIL RISK MEASURE , UTILITY VALUE AT RISK , UVAR , , TO RESOLVE THIS RIGIDITY
360	THE MAIN IDEA IS TO COMPUTE A WEIGHTED AVERAGE LOSS WHERE THE WEIGHT IS DETERMINED BY A UTILITY FUNCTION , AND THE UTILITY PARAMETER IDENTIFIES THE RISK PREFERENCES
360	FURTHERMORE , WE DERIVE ANALYTICAL SOLUTIONS UNDER CERTAIN DISTRIBUTIONAL ASSUMPTIONS , PROVE THE COHERENCE PROPERTY IN CONTINUOUS AND DISCRETE SETTINGS , AND PROVIDE EVIDENCE OF INCORPORATING CVAR INTO UVAR AS A SPECIAL CASE
360	FINALLY , WE DESIGN A UVAR OPTIMIZATION FRAMEWORK AND UTILIZE HIGH AND LOW FREQUENCY DATA IN THE US AND HK STOCK MARKETS TO DEMONSTRATE THE SUPERIORITY OF UVAR
360	FINANCE OPTIMIZATION , OPT , WOMEN IN O R MS , WORMS , 
361	CREDIT LINE AND INTEREST RATE OPTIMIZATION
361	INTEREST RATE AND CREDIT LINE ARE CRITICAL DECISIONS IN LENDING INDUSTRY , WHICH NEED TO CONSIDER THE MARKET ACCEPTANCE , CREDIT LOSS AND INTEREST INCOME
361	WE PROPOSE A MODEL FOR JOINT INTEREST RATE AND CREDIT LINE OPTIMIZATION
361	WE FIND THE OPTIMALITY CONDITIONS FOR CREDIT LINE AND INTEREST RATE WHEN EITHER INTEREST RATE OR CREDIT LINE IS GIVEN
361	WE SHOW THAT THE OPTIMAL CREDIT LINE IS DECREASING WITH LOSS GIVEN DEFAULT AND RISK FREE RATE AND THE OPTIMAL INTEREST RATE IS DECREASING WITH LOSS GIVEN DEFAULT AND CREDIT LINE
361	THEN , WE EXTEND THE ANALYSIS BY CONSIDERING THE MARKET ACCEPTANCE
361	WE PROVE THE OPTIMALITY CONDITIONS WITH RESPECT TO CREDIT LINE AND INTEREST RATE SEPARATELY
361	WE SHOW THAT THE OPTIMAL INTEREST RATE IS INCREASING WITH RISK FREE RATE
361	AND WE PROVE THAT THE OPTIMAL CREDIT LINE IS HIGHER AND THE OPTIMAL INTEREST RATE IS LOWER WHEN CONSIDERING THE MARKET ACCEPTANCE
361	FINANCE REVENUE MANAGEMENT AND PRICING OPT , OPTIMIZATION UNDER UNCERTAINTY
361	OUR ANALYSIS IS BASED ON STATISTICAL MODELS
361	IT IS A DATA DRIVEN APPROACH TO DECISION OPTIMIZATION 
362	A TERM STRUCTURE MODEL OF DEFAULT FREE AND DEFAULTABLE INTEREST RATES WITH REGIME SWITCHING PROPERTIES , USEFUL TOOL FOR RISK EVALUATION
362	LONG TERM HISTORICAL DATA ON INTEREST RATES AND CREDIT SPREADS CAN BE USED TO IDENTIFY DIFFERENT REGIMES , SPECIFICALLY , A CALM REGIME WITH LOWER DEFAULT RISK AND VOLATILITY AND A STRESSED REGIME WITH HIGHER DEFAULT RISK AND VOLATILITY
362	BASED ON THE DATA , WE PROPOSE A PRICING AND RISK EVALUATION MODEL OF INTEREST RATE RISK AND CREDIT RISK WITH THE MARKOVIAN REGIME SWITCHING PROPERTY
362	WE DISCUSS THE DYNAMICS OF A REGIME , THE INTEREST RATE , AND DEFAULT INTENSITY UNDER A PHYSICAL MEASURE AND A PRICING MEASURE , AND PROPOSE A TRACTABLE MODEL
362	IN IT , THE DEFAULT FREE INTEREST RATE AND THE DEFAULT INTENSITY ARE DEPENDENT ON THE REGIME
362	WE PROPOSE A CALIBRATION METHOD AND DEMONSTRATE SOME NUMERICAL EXAMPLES OF THE ZERO CURVES WITH DIFFERENT CREDIT RATINGS
362	WE HOPE THAT SUCH YIELD CURVE MODELS WILL REVEAL SOME NEW METHODS AND PERSPECTIVES FOR FINANCIAL RISK MANAGEMENT
362	FINANCE REVENUE MANAGEMENT AND PRICING QUALITY , STATISTICS AND RELIABILITY
363	THE IMPACT OF BUSINESS STRATEGY ON SELL SIDE ANALYSTS RECOMMENDATIONS
363	THIS STUDY INVESTIGATES WHETHER AND HOW BUSINESS STRATEGY CAN INFLUENCE FINANCIAL ANALYSTS RECOMMENDATIONS
363	IT ALSO EXAMINES THE ASSOCIATION BETWEEN TWO TYPES OF BUSINESS STRATEGY , PROSPECTOR AND DEFENDER , AND ANALYSTS RECOMMENDATIONS
363	USING U K SAMPLE DATA FROM TO , WE RUN DIFFERENT TYPES OF REGRESSION AND ANALYSES
363	WE FIND EVIDENCE THAT BUSINESS STRATEGY OBTAINS FAVORABLE RECOMMENDATIONS
363	WE ALSO FIND THAT PROSPECTOR STRATEGY FIRMS RECEIVE FAVORABLE RECOMMENDATIONS FROM SELL SIDE ANALYSTS
363	A SET OF ADDITIONAL TESTS CONFIRMS THESE MAIN FINDINGS
363	THE STUDY ESSENTIALLY ENRICHES OUR UNDERSTANDING ABOUT HOW FINANCIAL ANALYSTS ASSESS AND VALUE THE BUSINESS STRATEGY AND CHANNEL SUCH VALUE TO THE CAPITAL MARKET VIA THEIR INVESTMENT RECOMMENDATIONS
363	FINANCE SHARING ECONOMY , INNOVATIVE MARKETPLACES , AND DATA 
364	WHAT ARE THE MOTIVATIONS OF FINFLUENCERS
364	EVIDENCE FROM TIKTOK
364	POLICYMAKERS AND RESEARCHERS HAVE RECENTLY BECOME AWARE OF THE IMPORTANCE OF FINANCIAL LITERACY IN EMPOWERING INDIVIDUALS TO MAKE INFORMED DECISIONS ABOUT THEIR MONEY
364	IN THIS CONTEXT , SOCIAL MEDIA INFLUENCERS WHO COVER FINANCIAL ASPECTS IN THEIR SOCIAL MEDIA POSTS , SO CALLED FINFLUENCERS , HAVE RECENTLY BECOME VERY POPULAR
364	ALTHOUGH RECENT STUDIES SUGGEST THAT THOSE BORN BETWEEN THE LATE S AND EARLY S , I E , THE SO CALLED GENERATION Z , FOLLOW THEIR ADVICE , LITTLE IS KNOWN ABOUT FINFLUENCERS MOTIVES AND THE ACTUAL CONTENT OF THEIR POSTS
364	THIS STUDY FOCUSES ON FINFLUENCERS ON TIKTOK AND EXAMINES THEIR PROFILE PAGES FOR INDICATORS OF FINANCIAL MOTIVES , SUCH AS AFFILIATE LINKS OR LINKS TO THEIR OWN PREMIUM SUBSCRIPTION SERVICES
364	FINANCE SOCIAL MEDIA ANALYTICS 
365	MODIFIED MEAN VARIANCE ANALYSIS , PORTFOLIO OPTIMIZATION AND PROSPECT THEORY
365	WE CONSIDER THE USE OF MEAN VARIANCE , MV , ANALYSIS AND PORTFOLIO OPTIMIZATION FOR INVESTORS WITH DIFFERENT PREFERENCES UNDER PROSPECT THEORY
365	WE EXPLORE THE RELATIONSHIP BETWEEN THESE CONCEPTS AND PROSPECT THEORY , INCORPORATING PROSPECT STOCHASTIC DOMINANCE , PSD , TO MAKE THE RESULTS WIDELY RELEVANT
365	IT DEMONSTRATES HOW PARTIAL MOMENTS ALIGN WITH PSD AND CAN BE USED TO ELIMINATE PSD INEFFICIENT INVESTMENTS
365	USING PARTIAL MOMENTS , WE ALSO FORMULATE A RULE AKIN TO THE MV RULE TO RANK INVESTMENTS ACCORDING TO DIFFERENT VALUE FUNCTIONS UNDER PROSPECT THEORY
365	THIS RULE CAN PINPOINT PSD EFFICIENT SEGMENTS ON THE MV FRONTIER , HELPING TO IDENTIFY THE SUBSET OF MV PORTFOLIO CHOICES THAT ARE BOTH MV AND PSD EFFICIENT
365	ADDITIONALLY , PARTIAL MOMENTS ENABLE US TO DEVISE A PORTFOLIO OPTIMIZATION METHOD FOR BUILDING A PORTFOLIO THAT SURPASSES A TARGET INVESTMENT IN A PSD SENSE
365	FINANCE 
366	OPTIMAL GOAL BASED WEALTH AND RETIREMENT MANAGEMENT
366	WE EXAMINE AN INVESTOR WITH MULTIPLE SPENDING AND RETIREMENT GOALS WHO MUST CHOOSE THE OPTIMAL PORTFOLIO ALLOCATION , RETIREMENT ACCOUNT CONTRIBUTION , AND CONSUMPTION UNDER TAXES , STOCHASTIC INCOME , AND MARKET INCOME CORRELATION
366	WE FIND THE OPTIMAL PORTFOLIO AND INCOME ALLOCATION THAT MAXIMIZE THE INVESTOR S EXPECTED DISCOUNTED LIFETIME UTILITY AS A FUNCTION OF HIS OR HER PORTFOLIO VALUE , RETIREMENT ACCOUNT VALUE , AND INCOME
366	TAKING A MARTINGALE PERSPECTIVE OF FUTURE INVESTOR UTILITY , WE FIND CONTINUOUS TIME SOLUTIONS TO THIS PROBLEM
366	WE DEMONSTRATE THE MODEL S GENERAL APPLICABILITY WITH A SERIES OF NUMERICAL EXPERIMENTS SOLVING DISCRETE TIME PROBLEMS FOR HYPOTHETICAL INVESTORS
366	THE MODEL HIGHLIGHTS HOW DECISION MAKING CHANGES UNDER A VARIETY OF INVESTMENT CONDITIONS , INCLUDING DIFFERENT INCOME LEVELS , GOAL PRIORITIES , AND DURATION TO RETIREMENT
366	FINANCE 
367	TIME VARYING FACTOR SELECTION , A SPARSE FUSED GMM APPROACH
367	THIS PAPER PROPOSES A SPARSE FUSED GMM APPROACH , SFGMM , TO ESTIMATE A SPARSE TIME VARYING COEFFICIENT MODEL FOR SELECTING FACTORS WITH HETEROGENEOUS STRUCTURAL BREAKS
367	SFGMM OFFERS AN ALTERNATIVE ESTIMATION TO THE DYNAMIC STOCHASTIC DISCOUNT FACTOR MODEL , WHERE FACTOR RISK PRICES ARE SPARSE AND TIME VARYING , EMPLOYING A HIGH DIMENSIONAL SET OF CONDITIONING VARIABLES AND TEST ASSETS
367	WE FIND OURS OUTPERFORMS SEVERAL BENCHMARK MODELS , IMPROVING ASSET PRICING AND INVESTMENT PERFORMANCE
367	OUR RESULTS INDICATE RISK FACTORS HAVE THE STRONGEST EXPLANATORY POWER WHEN THE AGGREGATE DIVIDEND YIELD OR DEFAULT YIELD IS HIGH , BUT THEIR EFFECTIVENESS IS REDUCED WHEN MARKET LIQUIDITY IS LOW
367	MOREOVER , OUR STUDY REVEALS THE SELECTION OF FACTORS CHANGES OVER TIME , WITH SOME PREVIOUSLY SUCCESSFUL FACTORS DISAPPEARING IN THE RECENT DECADE , WHILE NEW FACTORS HAVE EMERGED
367	FINANCE WE HAVE PROVIDED A NEW METHOD FOR A NEW PERSPECTIVE OF TIME VARYING FACTOR SELECTION IN FINANCE 
368	OPTIMAL CURRENCY PORTFOLIO WITH IMPLIED RETURN DISTRIBUTION IN THE MEAN VARIANCE MODEL
368	WE CONSTRUCT AN OPTIMAL CURRENCY PORTFOLIO USING THE IMPLIED RETURN DISTRIBUTION IN THE MEAN VARIANCE APPROACH AND EXAMINE THE PERFORMANCE THROUGH A BACKTEST
368	WE ESTIMATE THE IMPLIED EXPECTED SPOT RETURN , IMPLIED VOLATILITY , AND IMPLIED CORRELATION FROM CURRENCY OPTION PRICE DATA , AND PROPOSE A METHOD OF CONSTRUCTING A FULLY FORWARD LOOKING OPTIMAL CURRENCY PORTFOLIO WITHOUT HISTORICAL DATA
368	WE IMPLEMENT THE BACKTEST FROM JANUARY TO OCTOBER ON A CURRENCY PORTFOLIO COMPRISING SEVEN CURRENCIES AND US DOLLAR INTEREST RATE , AND EXAMINE THE USEFULNESS OF THE PROPOSED METHOD
368	WE FIND THAT THE PROPOSED METHOD YIELDS A HIGHER PERFORMANCE THAN THE CONVENTIONAL METHOD IN PREVIOUS STUDIES THAT USE HISTORICAL DATA
368	FINANCE 
369	THE IMPACT OF MACROECONOMIC ANNOUNCEMENTS ON RISK , PREFERENCE , AND RISK PREMIUM THIS STUDY EXAMINES THE IMPACT OF MACROECONOMIC ANNOUNCEMENTS ON THE RISK PREMIUM AND ITS SOURCES UNDER TIME VARYING PREFERENCE
369	WE PROPOSE A NOVEL METHOD TO DECOMPOSE RISK PREMIUM CHANGES INTO THE RISK AND PREFERENCE COMPONENTS , WHICH ARE ESTIMATED FROM OPTION PRICES IMMEDIATELY BEFORE AND AFTER THE ANNOUNCEMENT USING THE RECOVERY THEOREM
369	THE RESULTS OF THE EMPIRICAL ANALYSIS FOR THE UNITED STATES STOCK MARKET INDICATE THAT , , THE NEGATIVE , POSITIVE , MACROECONOMIC ANNOUNCEMENT SURPRISE INCREASES , DECREASES , THE RISK PREMIUM , , , THE RISK COMPONENT MAINLY DRIVES THE INCREASE , DECREASE , IN THE RISK PREMIUM , AND , , THE PREFERENCE COMPONENT HAS LIMITED INFLUENCE ON THE RISK PREMIUM
369	FINANCE 
370	STATISTICAL VALIDATION OF CENTRALITY IN FINANCIAL NETWORKS
370	NETWORK ANALYSIS OFTEN RELIES ON ESTIMATED NETWORKS WHICH MAY DEVIATE FROM THE TRUE INTERLINKAGES , IMPACTING THE ACCURACY OF CENTRALITY MEASURE
370	WE INTRODUCE A STATISTICAL VALIDATION METHOD FOR THE CENTRALITY MEASURE , LEVERAGING A REGRESSION MODEL TO CONSTRUCT THE UNDERLYING NETWORK AND A CENTRALITY MEASURE REFLECTING CONTAGION RISK
370	OUR PROPOSED METHODOLOGY ENABLES RESEARCHERS TO DERIVE THE DISTRIBUTION OF THE CENTRALITY MEASURE , CONSTRUCT CONFIDENCE INTERVALS AND CONDUCT STATISTICAL TESTS TO ASSESS THE VALIDITY OF CENTRALITY VALUES
370	WE EMPLOY SIMULATIONS TO COMPARE THEORETICAL AND EMPIRICAL DISTRIBUTIONS WITH THE TRUE CENTRALITY
370	OUR RESULTS DEMONSTRATE THAT THE ESTIMATED CENTRALITIES CONSISTENTLY FALL WITHIN THE CONFIDENCE INTERVAL
370	WE APPLY OUR METHODOLOGY TO FINANCIAL DATA WHICH RESULTS IN IDENTIFYING STATISTICALLY SIGNIFICANT CENTRAL NODES
370	FINANCE 
371	INVESTMENT TIMING , UPPER REFLECTING BARRIER , AND DEBT EQUITY FINANCING
371	THIS STUDY CONSIDERS HOW AN UPPER REFLECTING BARRIER AFFECTS THE INTERACTION BETWEEN FINANCING AND INVESTMENT DECISIONS
371	HERE , A MAGNITUDE OF UPPER REFLECTING BARRIER CAN BE REGARDED AS THE DEGREE OF INTENSE MARKET COMPETITION
371	WE SHOW THAT FIERCE COMPETITION , A DECREASE IN UPPER REFLECTING BARRIER , REDUCES THE AMOUNT OF DEBT ISSUANCE AND DELAYS INVESTMENT , WHICH DECREASES THE CREDIT SPREADS AND LEVERAGE
371	FINANCE 
372	OUT OF SAMPLE PERFORMANCE BASED ESTIMATION OF EXPECTED RETURNS FOR PORTFOLIO SELECTION
372	THIS PAPER PROVIDES A FRAMEWORK FOR OBTAINING ESTIMATES OF EXPECTED ASSET RETURNS FOR PORTFOLIO SELECTION
372	THE FRAMEWORK RELIES ON A LINEAR MODEL BASED ON THE ESTIMATES OF OUT OF SAMPLE PORTFOLIO RETURNS , WHERE THE EXPECTED ASSET RETURNS ARE THE COEFFICIENTS TO BE ESTIMATED
372	THE MODEL IS FITTED BY BAYESIAN REGRESSION TO A SYNTHETIC DATA SET GENERATED FROM A SET OF HISTORICAL ASSET RETURNS OVER A LIMITED TIME HORIZON
372	THE ESTIMATOR IS COMPUTED USING A GIBBS SAMPLER , ALTHOUGH THE SET OF HISTORICAL ASSET RETURNS IS FINITE , IT IS CONSISTENT AND ASYMPTOTICALLY EFFICIENT AS THE SIZE OF THE SYNTHETIC DATA SET GROWS TO INFINITY
372	AN EMPIRICAL STUDY SHOWS THAT UNDER APPROPRIATE CONDITIONS , WITH OR WITHOUT NORM CONSTRAINTS , MEAN VARIANCE PORTFOLIOS CONSTRUCTED USING THIS ESTIMATOR PRODUCE BETTER OUT OF SAMPLE MEAN RETURNS AND SHARPE RATIOS THAN BENCHMARK PORTFOLIOS
372	FINANCE WE PROPOSE A DATA AUGMENTATION METHOD FOR ESTIMATING EXPECTED ASSET RETURNS FOR PORTFOLIO SELECTION 
373	LABOR MOMENTUM STOCK SELECTION STRATEGIES THROUGH SUPPLY CHAIN NETWORK
373	THIS STUDY FOCUSES ON THE PROPAGATION OF JOB POSTINGS THROUGH THE SUPPLY CHAIN STRUCTURE BETWEEN FIRMS AND PROPOSES AN INVESTMENT STRATEGY THAT USES THIS INFORMATION
373	SPECIFICALLY , WE FIND THAT AN INCREASING NUMBER OF JOB OPENINGS IN CUSTOMER FIRMS AFFECTS THE PERFORMANCE AND STOCK PRICE OF SUPPLIER FIRMS
373	THE EMPIRICAL ANALYSIS IN THE U S STOCK MARKET CONFIRMS THAT THE PROPOSED STRATEGY HAS A HIGH STOCK SELECTION EFFECT IN THE MANUFACTURING INDUSTRY , WHERE INTER FIRM TIES ARE STRONG
373	FINANCE 
374	LEVERAGING DYNAMIC MULTILAYER NETWORKS FOR MODELLING CREDIT RISK CONTAGION IN SMES
374	RESEARCHERS IN THE FIELD OF CREDIT RISK MANAGEMENT HAVE RECENTLY FOCUSED ON IMPROVING THE PERFORMANCE OF THESE MODELS BY INCORPORATING ALTERNATIVE DATA SOURCES SUCH AS NETWORK DATA
374	THIS STUDY USES COMPLEX , MULTILAYER NETWORK DATA ON SMES FROM A LARGE FINANCIAL INSTITUTION TO ESTIMATE CREDIT RISK
374	WE PROPOSE A NOVEL MODEL LEVERAGING DYNAMIC GRAPH ATTENTION NETWORKS TO PREDICT SME DEFAULT , WITH TWO SOURCES OF CONNECTIONS , NAMELY SHARED OWNERSHIP OF COMPANIES AND FINANCIAL TRANSACTIONS BETWEEN THEM , RESULTING IN A TWO LAYER NETWORK
374	WE SHOW HOW THIS INFORMATION , WHEN COMBINED WITH TRADITIONAL STRUCTURED DATA , CONTRIBUTES TO APPLICATION CREDIT SCORING PERFORMANCE , AND EXPLICITLY MODELS CONTAGION RISK ACROSS COMPANIES
374	FINANCE 
375	PURE SCALAR EQUILIBRIA FOR NORMAL FORM GAMES
375	A SCALAR EQUILIBRIUM , SE , IS AN ALTERNATIVE TYPE OF EQUILIBRIUM IN PURE STRATEGIES FOR AN N PERSON NORMAL FORM GAME G IT YIELDS A PURE STRATEGY FOR EACH PLAYER OF G BY MAXIMIZING AN APPROPRIATE UTILITY FUNCTION CHOSEN BY THE PLAYERS OR AN ARBITRATOR OVER THE ACCEPTABLE JOINT ACTIONS
375	AN SE IS AN EQUILIBRIUM SINCE NO PLAYERS OF G CAN INCREASE THE VALUE OF THIS UTILITY FUNCTION BY CHANGING THEIR STRATEGIES
375	EXAMPLES INCLUDE A GREEDY SE IN WHICH THE PLAYERS ACTION GIVE THEM THE LARGEST INDIVIDUAL PAYOFFS JOINTLY POSSIBLE , AS WELL AS A SATISFICING SE IN WHICH EACH PLAYER ACHIEVES A PERSONAL TARGET PAYOFF VALUE
375	THE VECTOR PAYOFF ASSOCIATED WITH EACH OF THESE SES IS SHOWN TO BE PARETO OPTIMAL AND COMPUTATIONALLY TRACTABLE
375	GROUP DECISION AND NEGOTIATION ARTIFICIAL INTELLIGENCE DECISION ANALYSIS SOCIETY
376	COURSE SELECTION UNDER SOCIAL NETWORK EFFECTS
376	WE CONSIDER A COURSE SELECTION MODEL THAT MATCHES A CONTINUUM OF STUDENTS TO A FINITE NUMBER OF COURSES
376	STUDENTS VALUATIONS FOR THE COURSES ARE SUBJECT TO THEIR INDIVIDUAL LEVEL SOCIAL NETWORK EFFECTS
376	WE ADOPT A PSEUDO MARKET ALLOCATION MECHANISM FOR COURSE SELECTION THAT TAKES THE STUDENTS REPORTED VALUATIONS FOR THE COURSES AS INPUT AND THEN OUTPUTS THE STUDENTS BID PRICE VECTOR FOR EACH COURSE AND THE CORRESPONDING ALLOCATIONS
376	WE SHOW THE EXISTENCE OF EQUILIBRIUM PRICES AND ALLOCATIONS UNDER ANY DISTRIBUTION OF STUDENTS REPORTED PREFERENCES FOR THE COURSES , AND SHOW THAT ONE SUCH EQUILIBRIUM CAN BE SOLVED BY A LINEAR PROGRAM
376	SIMULATIONS SUGGEST THAT THE WELFARE IS NON INCREASING IN THE STRENGTH OF THE NETWORK EFFECTS
376	GROUP DECISION AND NEGOTIATION AUCTIONS AND MARKET DESIGN SERVICE SCIENCE 
377	OPERATIONS RESEARCH GAMES UNDER UNCERTAINTY AND DISTRIBUTIONAL AMBIGUITY
377	THE AIM OF THIS PAPER IS TO ADDRESS A FUNDAMENTAL CHALLENGE OF INCORPORATING UNCERTAINTY INTO COOPERATIVE GAMES , PARTICULARLY OPERATIONS RESEARCH GAMES
377	WE INTRODUCE A NEW SOLUTION CONCEPT OF , ROBUST , LEAST CHANCE DECISIONS FOR COOPERATIVE GAMES UNDER UNCERTAINTY AND DISTRIBUTIONAL AMBIGUITY , WHICH IS MOTIVATED BY THE CONCEPT OF LEAST CORE SOLUTIONS FOR DETERMINISTIC COOPERATIVE GAMES
377	WE DEVELOP A FRAMEWORK TO FIND THOSE DECISIONS AND COMPUTE THEIR , ROBUST , LEAST CHANCE DISSATISFACTION FOR COOPERATIVE GAMES UNDER NORMALLY DISTRIBUTED UNCERTAINTY AND MOMENT BASED DISTRIBUTIONAL AMBIGUITY
377	WE DEMONSTRATE HOW THE FRAMEWORK CAN BE APPLIED TO SEVERAL OPERATIONS RESEARCH GAMES INCLUDING RESOURCE SHARING GAMES , PROJECT SELECTION GAMES , AND GENERAL LINEAR PRODUCTION GAMES WITH DETAILED ANALYTICAL RESULTS
377	GROUP DECISION AND NEGOTIATION FAIRNESS IN OPERATIONS OPT , OPTIMIZATION UNDER UNCERTAINTY
378	MULTI DISCIPLINARY LEARNING THROUGH COLLECTIVE ARTIFACTS FAVORS DECENTRALIZATION
378	MEMBERS OF MULTI DISCIPLINARY TEAMS OFTEN COMPLETE DISTINCT , INTERRELATED PIECES OF LARGER TASKS
378	THIS MAKES IT DIFFICULT FOR INDIVIDUALS TO SEPARATE THE PERFORMANCE EFFECTS OF THEIR OWN ACTIONS FROM THE ACTIONS OF INTERACTING NEIGHBORS
378	IN THIS WORK , WE SHOW THAT INDIVIDUALS CAN ALSO LEARN FROM NETWORK NEIGHBORS THROUGH ARTIFACTS , LIKE PERFORMANCE METRICS , 
378	WHEN INDIVIDUALS INNOVATE , EXPLORING SEARCHES , , DENSE NETWORKS HURT PERFORMANCE BY INCREASING UNCERTAINTY
378	IN CONTRAST , DENSE NETWORKS HELP PERFORMANCE WHEN INDIVIDUALS REFINE WORK , EXPLOITING SEARCHES , BY EFFICIENTLY FINDING OPTIMA
378	WE FIND THAT DECENTRALIZATION IMPROVES MULTI DISCIPLINARY TEAM PERFORMANCE ACROSS A BATTERY OF TASKS , SUGGESTING NEW DESIGN PRINCIPLES FOR MULTI DISCIPLINARY TEAMS
378	GROUP DECISION AND NEGOTIATION SIMULATION SOCIETY TECHNOLOGY , INNOVATION MANAGEMENT AND ENTREPRENEURSHIP
378	WE USE PARALLEL CLUSTER SIMULATIONS AND ANALYSIS TO YIELD NEW INSIGHTS FOR TEAM SCIENCE
379	DYNAMIC HUMAN ACTIVITY RECOGNITION AND ITS APPLICATION IN HEALTHCARE
379	HUMAN ACTIVITY RECOGNITION , HAR , USING MACHINE LEARNING IS A NOVEL APPROACH FOR SENSING AND DETECTION OF HUMAN ACTIVITIES , ESPECIALLY IN HEALTHCARE SYSTEMS
379	HOWEVER , LIMITED ATTENTION HAS BEEN PAID TO HUMAN ACTIVITY DYNAMICS
379	IN THIS STUDY , A FRAMEWORK OF DYNAMIC HUMAN ACTIVITY RECOGNITION , DHAR , IS PROPOSED BASED ON A PARTIALLY OBSERVABLE MARKOV DECISION PROCESS , POMDP , MODEL
379	IT IS MOTIVATED BY THE POTENTIAL INACCURACY OF CURRENT HAR MODELS IN REAL WORLD ENVIRONMENTS
379	GIVEN A SET OF HAR MODELS AVAILABLE , THE PROPOSED METHOD DYNAMICALLY SELECTS AN HAR MODEL , ACCORDING TO THE OBSERVED HUMAN ACTIVITIES , TO BETTER RECOGNIZE THE NEXT HUMAN ACTIVITY
379	THE SIMULATION EXPERIMENT IS CONDUCTED AND SHOWS BETTER PERFORMANCE OF THE FRAMEWORK THAN A SINGLE HAR MODEL
379	THIS APPROACH HAS POTENTIAL IN APPLICATIONS IN HEALTHCARE , SUCH AS FALL DETECTION
379	HEALTH APPLICATIONS SOCIETY APPLIED PROBABILITY 
380	COMPOSITE RISK PREDICTION OF ALL TYPES HOSPITAL ACQUIRED CONDITIONS USING MACHINE LEARNING FOR PEDIATRIC PATIENTS
380	HOSPITAL ACQUIRED CONDITIONS , HACS , ARE MOSTLY PREVENTABLE RISK TO THE SAFETY OF HOSPITALIZED CHILDREN , ESPECIALLY WITH MULTIPLE CHRONIC CONDITIONS , MCC , , THAT CAN RESULT IN ELEVATED MORTALITY MORBIDITY , LONGER HOSPITALIZATION , AND HIGHER COST OF CARE
380	UNLIKE PAST RESEARCH FOCUSING ON SPECIFIC HACS , MY STUDY DEVELOPS COMPOSITE RISK PREDICTION MODEL FOR ALL TYPES HACS AMONG CHRONICALLY ILL CHILDREN
380	I USED ADMINISTRATIVE DATA ON , PEDIATRIC HOSPITALIZATIONS , AGE , DAYS YEARS , INCLUDES , NEONATES , INFANTS , DURING Q Q AT ALL HOSPITALS IN TEXAS
380	I DEVELOPED POISSON REGRESSION , WITH RANDOM EFFECTS , MODEL FOR PREDICTING HACS COUNT WITH PREDICTORS INCLUDING MCC PATTERNS , ESTIMATED USING BERNOULLI MIXTURE MODEL CLUSTERING , , PATIENT FACTORS , HOSPITAL FACTORS , AND PHYSICIAN FACTORS CONTROLLING FOR ADMISSION TYPE AND TIME FACTORS
380	HEALTH APPLICATIONS SOCIETY ARTIFICIAL INTELLIGENCE 
380	MY STUDY USES NEARLY MILLION ADMINISTRATIVE DATA ON INPATIENTS REPORTED BY HOSPITALS IN TEXAS 
381	PREDICTION OF ADVERSE DRUG REACTIONS USING DEMOGRAPHIC AND NON CLINICAL DRUG CHARACTERISTICS IN FAERS DATA
381	THE PRESENCE OF ADVERSE DRUG REACTIONS , ADRS , IS A SIGNIFICANT PUBLIC HEALTH CONCERN
381	HOWEVER , CURRENT STUDIES ON ADR PREDICTION PRIMARILY FOCUS ON NON CLINICAL DATA , NEGLECTING THE POTENTIAL OF LEVERAGING BOTH DEMOGRAPHIC AND NON CLINICAL INFORMATION
381	ADDITIONALLY , THE IMPORTANCE OF INDIVIDUAL FEATURES IN ADR PREDICTION REMAINS UNEXPLORED
381	THIS STUDY AIMS TO FILL THESE GAPS BY DEVELOPING AN ADR PREDICTION MODEL THAT INCORPORATES DEMOGRAPHIC AND NON CLINICAL DATA , IDENTIFYING THE MOST INFLUENTIAL FACTORS
381	THE DEEP LEARNING AND RANDOM FOREST MODELS WERE USED AND EVALUATED USING THE AREA UNDER THE RECEIVER OPERATING CHARACTERISTIC CURVE AND THE MEAN AVERAGE PRECISION
381	RESULTS SHOWED THAT OUR RANDOM FOREST MODEL WITH ONLY THE TOP MOST IMPORTANT FEATURES OFFERS SIMILAR ADR PREDICTION PERFORMANCE COMPARED TO FEATURE RICH MODEL CONSISTING OF ALL FEATURES
381	HEALTH APPLICATIONS SOCIETY DATA MINING ARTIFICIAL INTELLIGENCE
382	A HYBRID AI AND OPTIMIZATION FRAMEWORK TO ADDRESS THE ISSUE OF FREQUENT MISSING VALUES , THE CASE OF A CLINICAL DECISION SUPPORT SYSTEM FOR PARKINSON S DISEASE
382	ANALYZING ELECTRONIC HEALTH RECORD , EHR , DATA CAN IMPROVE CLINICAL DECISION SUPPORT SYSTEMS , CDSS , 
382	HOWEVER , THE VOLUME OF DATA PRESENTS SIGNIFICANT CHALLENGES , INCLUDING HANDLING MISSING VALUES
382	EMPLOYING EXPLAINABLE AI TECHNIQUES , OPTIMIZATION , AND PREDICTIVE ANALYTICS , WE INTRODUCE A FRAMEWORK THAT ADDRESSES THE ISSUE OF INCOMPLETENESS IN EHR DATA , ENABLING RESEARCHERS TO SELECT THE MOST CRITICAL VARIABLES AT AN ACCEPTABLE LEVEL OF MISSING DATA
382	WE DEMONSTRATE THE EFFECTIVENESS OF THIS FRAMEWORK BY APPLYING IT TO DEVELOPING A CDSS FOR DETECTING PARKINSON S DISEASE , WHERE IN PRACTICE , PARKINSON S DISEASE IS HARD TO DIAGNOSE , AND EVEN SPECIALISTS DIAGNOSES CAN BE INACCURATE
382	OUR RESULTS SHOW THAT THE FRAMEWORK IMPROVES THE ACCURACY OF PREDICTIVE MODELS AND IDENTIFIES PATIENTS WITH PARKINSON S DISEASE WHO MIGHT OTHERWISE GO UNDIAGNOSED
382	HEALTH APPLICATIONS SOCIETY DATA MINING INFORMATION SYSTEMS
383	COMPARISON ANALYSIS ON PERFORMANCE OF MOBILE HEALTH APPS AMONG CULTURALLY SENSITIVE COMMUNITIES
383	SMARTPHONES ENABLES THE RAPID SPREAD OF APPS THAT PROVIDE SERVICES IN MANY ASPECTS OF LIFE SUCH AS EDUCATION , LIFESTYLE , SOCIAL MEDIA , PRODUCTIVITY , ENTERTAINMENT , AND GAME APPS
383	THE PANDEMIC ACCELERATES THE SPREAD OF MOBILE APPS , ESPECIALLY IN THE DOMAIN OF HEALTHCARE BECAUSE OF CULTURAL AND PRIVACY SENSITIVITY , BEING PORTABLE , AND BEING EASILY ACCESSIBLE
383	THE RESEARCH FOCUSES ON THE EFFECT OF THE MHEALTH APP IN THE DOMAIN OF MENTAL HEALTH INTERVENTION , AND AIMS TO COMPARE AND ANALYZE THE PERFORMANCE AND EFFECT OF MHEALTH APPS AMONG DIFFERENT COGNITIVE GAMES CULTURAL COMMUNITIES TO IMPROVE THE EFFECTIVENESS OF GAMES AND IMPROVE MEMORY AND CONCENTRATION IN THE DOMAIN OF THE MENTAL HEALTH APPS AND TO PROVIDE THE FRAMEWORK FOR THE APP DEVELOPERS BASED ON SERIOUS GAMES FOR WHICH AFFECT THE PERFORMANCE OF MHEALTH APPS AMONG DIFFERENT CULTURAL COMMUNITIES
383	HEALTH APPLICATIONS SOCIETY DATA , OR , AND SOCIAL JUSTICE DIVERSITY , EQUITY , AND INCLUSION
384	DEEP LEARNING CLASSIFICATION IN PRESENCE OF UNCERTAIN PREDICTORS FOR MEDICAL DECISION MAKING
384	DEEP LEARNING CLASSIFICATION MODELS ARE BECOMING INCREASINGLY APPLICABLE IN HEALTHCARE BUT ARE ALSO SIGNIFICANTLY CHALLENGING DUE TO THE INHERENT UNCERTAINTIES IN CLINICAL AND LABORATORY TEST DATA
384	THESE ERRORS ARE USUALLY PRESENTED AS SENSITIVITY AND SPECIFICITY MEASURES AND DO NOT FOLLOW A NORMAL BUT SOME DISCRETE DISTRIBUTION
384	WE DEMONSTRATE THE IMPACT OF THESE UNCERTAINTIES ON PREDICTIONS AND DEVELOP A FRAMEWORK TO HANDLE AND QUANTIFY THESE UNCERTAINTIES IN MEDICAL DECISION MAKING PROBLEMS
384	HEALTH APPLICATIONS SOCIETY DECISION ANALYSIS SOCIETY ARTIFICIAL INTELLIGENCE
385	A STUDY OF BIAS IN MACHINE LEARNING TECHNIQUES IN PREDICTING NON ALCOHOLIC FATTY LIVER DISEASE , NAFLD , 
385	NON ALCOHOLIC FATTY LIVER DISEASE , NAFLD , , WHICH AFFECTS TO OF THE WORLD S POPULATION , IS AN UMBRELLA TERM THAT REFERS TO A RANGE OF CONDITIONS CAUSED BY EXCESS FAT IN THE LIVER OF A PERSON WHO DRINKS LITTLE TO NO ALCOHOL
385	IN NAFLD REVIEW PAPERS , RACE AND ETHNICITY HAVE BEEN FOUND TO BE TWO OF THE SIGNIFICANT FACTORS CONTRIBUTING TO THE DEVELOPMENT OF NAFLD
385	HOWEVER , IN MANY PREDICTION STUDIES UTILIZING MACHINE LEARNING TECHNIQUES , RACE AND ETHNICITY ARE NOT INCLUDED AS SIGNIFICANT FACTORS
385	THEREFORE , WE USE MACHINE LEARNING TECHNIQUES TO STUDY WHETHER BIRTH COUNTRY , RACE , AND ETHNICITY ARE STATISTICALLY SIGNIFICANT TO THE PREDICTED OUTCOME OF A PATIENT HAVING NAFLD
385	HEALTH APPLICATIONS SOCIETY DECISION ANALYSIS SOCIETY DIVERSITY , EQUITY , AND INCLUSION
385	TO ANALYZE DATA , WE FIRST NEED TO UNDERSTAND OUR DATA AND ITS NUANCES
386	THE IMPACT OF PROVIDER COACHING ON PATIENT SATISFACTION IN EMERGENCY DEPARTMENT
386	PATIENT EXPERIENCE AND SATISFACTION ARE CRUCIAL FACTORS IN HEALTHCARE , AS THEY CORRELATE WITH BETTER HEALTH OUTCOMES AND FINANCIAL INCENTIVES
386	EMERGENCY DEPARTMENTS , EDS , FACE UNIQUE CHALLENGES IN ACHIEVING HIGH PATIENT SATISFACTION DUE TO FRAGMENTED INTERACTIONS AND LIMITED TIME FOR PROVIDERS TO BUILD TRUST
386	THIS STUDY AIMS TO INVESTIGATE THE INFLUENCE OF PROFESSIONAL COACHING ON PATIENT EXPERIENCE AND SATISFACTION IN EDS , CONSIDERING PATIENT , PROVIDER , AND VISIT CHARACTERISTICS
386	THE RESEARCH QUESTIONS ADDRESS THE IMPACT OF THESE FACTORS ON PATIENT SATISFACTION SCORES AND THE EFFECTIVENESS OF PROVIDER COACHING
386	BY UNDERSTANDING THE ROLE OF PROFESSIONAL COACHING , THIS STUDY AIMS TO HELP HEALTHCARE PROVIDERS IMPROVE PATIENT EXPERIENCE , POPULATION HEALTH , AND FINANCIAL PERFORMANCE
386	HEALTH APPLICATIONS SOCIETY DECISION ANALYSIS SOCIETY PRACTICE 
387	SPATIOTEMPORAL ANALYSIS OF VOLUNTEER FIRST RESPONDERS EFFECTIVENESS
387	RAPID FIRST AID IS VITAL FOR REDUCING MORTALITY AND IMPROVING LONG TERM PROGNOSIS DURING MEDICAL EMERGENCIES
387	ONE APPROACH TO ACHIEVING FASTER RESPONSE TIMES IS THROUGH SMARTPHONE BASED VOLUNTEER FIRST RESPONDER , VFR , NETWORKS
387	VFR EFFECTIVENESS IS MEASURED BY FACTORS SUCH AS ARRIVAL TIME , RELEVANT INTERVENTION , AND MEDICAL OUTCOMES
387	GEOGRAPHIC COVERAGE IS A COMMONLY USED MEASURE OF EMERGENCY MEDICAL SERVICE EFFECTIVENESS
387	THIS STUDY PRESENTS A NOVEL ANALYTICAL TECHNIQUE FOR ANALYZING VFR NETWORK EFFECTIVENESS IN TERMS OF GEOGRAPHIC COVERAGE USING REAL WORLD DATA FROM A FIELD STUDY
387	THE ANALYSIS CONSIDERS THE UNPREDICTABLE LOCATION AND AVAILABILITY OF VFRS DURING AN EMERGENCY EVENT , AIDING DECISION MAKING FOR RECRUITMENT AND RETENTION EFFORTS AND IMPROVING COLLABORATION WITH EMS
387	FINDINGS CAN ENHANCE VFR NETWORK ADMINISTRATORS EFFORTS TO SAVE LIVES
387	HEALTH APPLICATIONS SOCIETY LOCATION ANALYSIS MSOM , HEALTHCARE
387	WE PRESENT DATA DRIVEN DECISION MAKING TOOL 
388	MITIGATING UNDERREPORTED ERROR IN FOOD FREQUENCY QUESTIONNAIRE DATA USING A SUPERVISED MACHINE LEARNING METHOD AND ERROR ADJUSTMENT ALGORITHM
388	FOOD FREQUENCY QUESTIONNAIRES , FFQ , ARE ONE OF THE MOST USEFUL TOOLS FOR UNDERSTANDING DIET DISEASE RELATIONSHIPS
388	HOWEVER , THEY ARE SUSCEPTIBLE TO BIAS AND MISCLASSIFICATION
388	IN THIS PAPER , A MACHINE LEARNING METHOD IS PROPOSED TO ADJUST FOR MEASUREMENT ERROR FOUND IN MISREPORTED DATA BY USING A RANDOM FOREST CLASSIFIER AND AN ALGORITHM THAT ADJUSTS THE MEASUREMENT ERROR
388	WE SHOW THIS METHOD BY ADDRESSING UNDERREPORTING IN SELECTED FFQ RESPONSES
388	WE HAVE HIGH MODEL ACCURACIES RANGING FROM TO IN PARTICIPANT COLLECTED DATA AND IN SIMULATED DATA
388	THIS SHOWS THAT OUR PROPOSED METHOD OF USING A RF CLASSIFIER AND ERROR ADJUSTMENT ALGORITHM IS EFFICIENT TO CORRECT MOST OF THE UNDERREPORTED ENTRIES IN THE FFQ DATASET AND COULD BE USED INDEPENDENT OF DIET DISEASE MODELS
388	THIS COULD HELP NUTRITION EXPERTS TO USE DIETARY DATA ESTIMATED BY FFQS WITH LESS MEASUREMENT ERROR
388	HEALTH APPLICATIONS SOCIETY MACHINE LEARNING IN OPERATIONS DATA , OR , AND SOCIAL JUSTICE
389	MULTI STAGE HEART FAILURE READMISSION PREDICTION
389	HOSPITAL READMISSIONS ARE BURDENSOME FOR HEART FAILURE PATIENTS AS WELL AS THE HEALTHCARE SYSTEM
389	IN THIS PAPER , WE PROPOSE AN INTERPRETABLE MODEL THAT PREDICTS WHETHER A PATIENT WILL BE READMITTED TO THE HOSPITAL OR DIE WITHIN DAYS AFTER BEING DISCHARGED BASED ON DATA AVAILABLE AT DIFFERENT ADMISSION STAGES
389	OUR MODEL IS AN ATTENTION BASED NEURAL NETWORK MODEL , WHERE THE FEATURES AVAILABLE AT DIFFERENT TIME STEPS VARY
389	WE DEMONSTRATE OUR FRAMEWORK ON HEART FAILURE ADMISSION DATA FROM A MAJOR HEALTH SYSTEM , WHERE WE FIND THAT OUR PROPOSED FRAMEWORK CAN ACHIEVE COMPETITIVE PREDICTION ACCURACY WHILE IDENTIFYING HOW THE IMPORTANCE OF FEATURES VARIES OVER STAGES
389	HEALTH APPLICATIONS SOCIETY MSOM , HEALTHCARE ARTIFICIAL INTELLIGENCE
390	GEAP CASE STUDY , NUTRITION OPERATIONAL RESEARCH APP THAT RESULTED IN HEALTH COST REDUCTIONS ASSOCIATED WITH BETTER CLINICAL CONDITIONS
390	GEAP NUTRITION GROUP HAS DEVELOPED AN APP BASED ON O R AND NUTRITION MS THAT HAS HELPED SEVERAL PATIENTS IN THE CHRONIC DISEASE PROGRAM AND HOME CARE IMPROVED THEIR CLINICAL CONDITION
390	BASED ON SCIENCE EVIDENCE THE NUTRITION PRESCRIPTION WAS ASSOCIATED WITH MEDICAL PRESCRIPTION
390	AS AN EXAMPLE , A PATIENT THAT WAS SEND HOME AFTER A BELLY SURGERY RECEIVED A NUTRITION PROGRAM TO CLOSE THE CICATRIZATION OF THE BELLY WITH MORE PROTEIN
390	WITH REMOTE MONITORING WHEN THE CICATRIZATION WAS COMPLETED , HIS NUTRITION PROGRAM WAS CHANGED TO HELP HIM RECOVERY HIS DAILY FUNCTIONS
390	WITH THIS APP THAT NOW IS IN THE EXPANSION PHASE FOR OTHER AREAS OF OUR HEALTH INSURANCE COMPANY THE COMPANY WAS ABLE TO REDUCE OF THE NUTRITION EXPENSE IN HOME CARE THROUGH A FAST PATIENT RECOVERY AND SAVINGS WITH NON NECESSARY NUTRITION PURCHASES THAT WAS NOT PROPERLY MONITORED BEFORE THIS APP INTRODUCTION
390	HEALTH APPLICATIONS SOCIETY MSOM , HEALTHCARE GROUP DECISION AND NEGOTIATION
390	OR MS WAS THE BASIS FOR THE CONSTRUCTION OF OUR APP 
391	WHERE IS THE VALUE OF INFORMATION SHARING IN THE REGIONAL COLLABORATIVE EMERGENCY CARE SYSTEM EVIDENCE FROM A REGIONAL CHEST PAIN CENTER
391	TIMELY ACCESS TO A SPECIALIZED AND SYSTEMATIC CARE IS IMPORTANT FOR PATIENTS WITH TIME SENSITIVE AND LIFE CRITICAL CONDITIONS
391	WE EMPIRICALLY INVESTIGATE EFFECTS OF PRE HOSPITAL INFORMATION SHARING WITHIN A REGIONAL COLLABORATIVE EMERGENCY CARE SYSTEM , FOR INTER HOSPITAL TRANSFERRED PATIENTS WITH THE MOST SEVERE TYPE OF HEART ATTACK , FROM A REGIONAL CHEST PAIN CENTER
391	OUR RESULTS SHOW THAT PRE HOSPITAL INFORMATION SHARING NOT ONLY SIGNIFICANTLY IMPROVES OPERATIONAL EFFICIENCY OF THE RECEIVING HOSPITAL AND THE WHOLE COORDINATED SYSTEM BY REDUCING IN HOSPITAL DELAY AND SYSTEM DELAY , BUT ALSO EXERTS SIGNIFICANT EFFECT ON REDUCING DUPLICATE ELECTROCARDIOGRAM TESTS BY AND EMERGENCY DEPARTMENT UTILIZATION BY WE FURTHER EXPLORE THE UNDERLYING MECHANISM OF OPERATIONAL EFFICIENCY IMPROVEMENTS
391	HEALTH APPLICATIONS SOCIETY MSOM , HEALTHCARE INFORMATION SYSTEMS
392	DEVELOPING AN ENSEMBLE MODEL TO PREDICT SAFE AMBULATORY SURGERY
392	TO IMPROVE QUALITY AND DECREASE COST , HEALTH SYSTEMS ARE SEEKING TO PERFORM MORE AMBULATORY SURGERIES
392	AMBULATORY SURGERY CAN DECREASE COST AND INPATIENT BED UTILIZATION WHILE INCREASING PATIENT SATISFACTION
392	HOWEVER , THERE IS NO RELIABLE AND GENERALIZABLE MODEL THAT PREDICTS WHICH PATIENTS AND WHICH SURGERIES ARE APPROPRIATE FOR AMBULATORY VENUES
392	OUR AIM IS TO CREATE AN ENSEMBLE MODEL WHICH PREDICTS THE OPTIMAL SAFE SURGICAL VENUE
392	AMBULATORY CASES MUST BE LESS THAN HOURS , A PATIENT MUST STAY LESS THAN HOURS , AND THE PATIENT MUST GO HOME RATHER THAN TO A FACILITY
392	THEREFORE , WE ARE DEVELOPING AN ENSEMBLE MODEL TO PREDICT SAFE SURGICAL VENUE USING DISTINCT MACHINE LEARNING MODELS FOR OPERATIVE CASE LENGTH , ACCURATE WITHIN OF OPERATIVE TIME , , POST OPERATIVE LENGTH OF STAY ONE NIGHT OR LESS , AUC , , AND DISCHARGE DISPOSITION HOME , AUC , 
392	HEALTH APPLICATIONS SOCIETY MSOM , HEALTHCARE MACHINE LEARNING IN OPERATIONS USING DATA WITHIN HEALTHCARE TO FACILITATE OPERATIONAL DECISIONS 
393	A PARTIALLY FLEXIBLE STRATEGY FOR EMERGENCY DEPARTMENT ADMISSIONS TO HOSPITAL WARDS
393	WE PROPOSE A PARTIALLY FLEXIBLE ROUTING STRATEGY TO ADMIT EMERGENCY DEPARTMENT PATIENTS TO HOSPITAL WARDS , WITH THE GOAL OF REDUCING BOARDING TIMES WHILE ENSURING THAT THE QUALITY OF CARE AND STAFF SATISFACTION ARE NOT NEGATIVELY IMPACTED
393	THE PROPOSED POLICY UTILIZES PROCESS FLEXIBILITY PRINCIPLES AND INCORPORATES MATRIX ANALYTICS AND PROBABILITY GENERATING FUNCTIONS
393	SIMULATION OUTCOMES INDICATE THAT THE PROPOSED POLICY IS COMPARABLE TO A FULLY FLEXIBLE DESIGN IN TERMS OF BOARDING TIME , WHILE PRESERVING THE QUALITY OF CARE AND STAFF SATISFACTION
393	HEALTH APPLICATIONS SOCIETY MSOM , HEALTHCARE OPTIMIZATION , OPT , 
394	SELECTING AND SCHEDULING PATIENTS ON PARALLEL NON HOMOGENOUS SERVERS CONSIDERING SETUP TIMES AND TIME WINDOW CONSTRAINTS
394	IN THIS TALK , WE ADDRESS THE PROBLEM OF SELECTION AND SCHEDULING OF PATIENTS ON PARALLEL SERVERS WITH SEQUENCE DEPENDENT SETUP TIMES AND STRICTLY ENFORCED TIME WINDOWS
394	WE DEPART FROM EXISTING LITERATURE BY CONSIDERING CONTINUOUS TIME AND INTRODUCE A MATHEMATICAL PROGRAMMING MODEL BASED ON DISJUNCTIVE CONSTRAINTS TO SOLVE SMALL AND MEDIUM SIZE PROBLEMS TO OPTIMALITY AND PROPOSE HEURISTICS TO SOLVE LARGE SCALE PROBLEMS
394	THE EFFICIENCY AND EFFECTIVENESS OF PROPOSED ALGORITHMS ARE REPORTED AND APPLICATIONS IN PATIENT SCHEDULING IN HEALTHCARE INDUSTRY ARE HIGHLIGHTED
394	HEALTH APPLICATIONS SOCIETY MSOM , HEALTHCARE OPTIMIZATION , OPT , 
394	OUR APPROACH USES THE POWER OF DATA TO FIND OPTIMAL SCHEDULES FOR PATIENTS IN HEALTHCARE INDUSTRY 
395	A NOVEL THREE STAGE DECISION MAKING FRAMEWORK FOR SURGICAL SCHEDULING WITH DEMAND UNCERTAINTIES
395	WE WORK FOR THE SURGICAL SCHEDULING SYSTEM OF A PARTNER HOSPITAL IN JIANGSU PROVINCE , CHINA
395	WE PROPOSE A NOVEL THREE STAGE DECISION MAKING FRAMEWORK FOR SURGICAL SCHEDULING
395	THE CORE IDEA IS TO DISASSEMBLE THE VARIOUS UNCERTAINTIES INTO DIFFERENT STAGES
395	WE DEVELOP MATHEMATICAL PROGRAMMING MODELS FOR EACH DECISION MAKING STAGE
395	THE EXPERIMENTS VIA HISTORICAL DATA FROM THE PARTNER HOSPITAL INDICATE THAT OUR FRAMEWORK COULD IMPROVE OF YEARLY AMOUNT OF SURGERIES FOR THE PARTNER HOSPITAL
395	OUR APPROACHES ARE BEING DEVELOPED AND INTEGRATED INTO THE INFORMATION SYSTEM OF THE PARTNER HOSPITAL
395	HEALTH APPLICATIONS SOCIETY MSOM , HEALTHCARE PRACTICE 
396	A HYBRID SIMULATION OPTIMIZATION APPROACH TO SOLVE AN AMBULANCE LOCATION PROBLEM USING A TABU SEARCH ALGORITHM
396	EMERGENCY MEDICAL SERVICES , EMS , AIM TO PROVIDE PROMPT ASSISTANCE TO INDIVIDUALS INVOLVED IN EMERGENCIES
396	IN ORDER TO ACHIEVE THIS GOAL , AMBULANCES SHOULD BE LOCATED IN STRATEGIC AREAS , CLOSER TO THE GEOGRAPHICAL CENTER OF EMERGENCIES
396	MOREOVER , THE DEPLOYMENT OF AMBULANCES SHOULD CONSIDER DYNAMIC CONDITIONS SUCH AS TRAFFIC AND EMERGENCY PATTERNS
396	THIS WORK PRESENTS A SIMULATION MODEL THAT CAPTURES RELEVANT PERFORMANCE MEASURES SUCH AS RESPONSE TIME AND COVERAGE
396	THEN , A TABU SEARCH ALGORITHM IS USED TO OPTIMIZE THE SYSTEM , ALLOWING THE OPTIMIZATION OF A SIMULATION MODEL
396	THE PROPOSED METHOD IS ASSESSED USING THE CITY OF ANTOFAGASTA , CHILE , AS A CASE STUDY
396	METHODOLOGY , EXPERIMENTS , AND RESULTS WILL BE PRESENTED
396	HEALTH APPLICATIONS SOCIETY MSOM , HEALTHCARE PUBLIC SECTOR OR 
397	COLLABORATIVE SCHEDULING AND ROUTING OF HEALTHCARE SERVICE IN MULTIPLE HEALTHCARE CENTERS
397	THE HOME COMMUNITY SERVICE MODE IS A CRUCIAL HOME HEALTH CARE MODE IN CHINA , WHICH CONCERNS THE IMPACT OF HEALTH CARE CENTER IN EACH COMMUNITY AND COORDINATES THE MEDICAL RESOURCES AMONG COMMUNITIES
397	IN THIS PAPER , A NEW PROBLEM OF COLLABORATIVE SCHEDULING AND ROUTING OF CAREGIVERS IN MULTIPLE HEALTH CARE CENTERS IS PROPOSED
397	WE DEVELOP A MIXED INTEGER PROGRAMMING MODEL TO FORMULATE THE PROBLEM , WHICH CONSIDERED MORE COMPLEX REALISTIC CONSTRAINTS
397	AN ADAPTIVE LARGE NEIGHBORHOOD SEARCH , ALNS , ALGORITHM IS PROPOSED WITH NEW PROBLEM SPECIFIC OPERATORS
397	TO FURTHER ENHANCE THE PERFORMANCE OF ALGORITHM , TWO POST OPTIMIZATION TECHNIQUES , NAMELY HEURISTIC POST OPTIMIZATION METHOD AND SET PARTITIONING TECHNIQUE ARE DESIGNED AND IMPLEMENTED AT THE END OF ALNS BENCHMARK INSTANCES ARE GENERATED
397	THE RESULTS SHOW THAT OUR ALGORITHMS ARE QUITE EFFICIENT
397	HEALTH APPLICATIONS SOCIETY MSOM , HEALTHCARE TRANSPORTATION SCIENCE AND LOGISTICS , TSL , 
397	OUR WORK CAN IMPROVE THE SCHEDULING EFFICIENCY OF CAREGIVER THROUGH DATA PROCESSING 
398	OPTIMAL ROUTING FOR MOBILE METHADONE CLINICS
398	METHADONE TREATMENT IS PROVEN TO BE HIGHLY SUCCESSFUL IN COMBATING OPIOID ADDICTION AND PREVENTING OVERDOSES , BUT MANY PATIENTS HAVE GEOGRAPHIC RESTRICTIONS ON ACCESS
398	IN THE DRUG ENFORCEMENT AGENCY CHANGED REGULATIONS TO ALLOW FOR EASIER OPERATION OF NARCOTIC TREATMENT PROGRAMS WITH A MOBILE COMPONENT , ALSO KNOWN AS MOBILE METHADONE CLINICS
398	THESE MOBILE CLINICS CAN EXPAND ACCESS TO METHADONE IN RURAL AND UNDERSERVED COMMUNITIES
398	IN THIS TALK WE ESTIMATE THE DEMAND FOR METHADONE IN AREAS THAT DO NOT CURRENTLY HAVE ACCESS AND FORMULATE A MIP TO MAXIMIZE THE NUMBER OF CLIENTS SERVED
398	WE SOLVE THE MODEL TO OPTIMALITY WITHIN EACH STATE NATIONWIDE
398	WE FIND ADDITIONAL POLICY CHANGES NEED TO BE CONSIDERED AND EFFICIENCY IMPROVEMENTS MADE TO INCENTIVIZE THE OPERATION OF MOBILE METHADONE UNITS FOR SERVING RURAL AND UNMET DEMAND FOR METHADONE MAINTENANCE TREATMENT
398	HEALTH APPLICATIONS SOCIETY MSOM , HEALTHCARE 
398	UTILIZING PUBLIC HEALTH ESTIMATES TO PREDICT UNKNOWN QUANTITIES THAT ARE ENTERED AS PARAMETER VALUES 
399	EXPLORING THE IMPACT OF HEALTH IT FEATURES ON QUALITY OF HOSPITAL CARE 
399	AS POLICIES WITH STAGGERED ADOPTION SUCH AS MEDICAID EXPANSION ACROSS STATES HAVE BEEN GAINING TRACTION IN THE PUBLIC HEALTH SECTOR , SO HAS THE TOPIC OF DIFFERENCE IN DIFFERENCES , DID , METHODS WHICH ALLOW FOR TIME VARYING TREATMENT STRATEGIES
399	WE UTILIZE A NOVEL ADJUSTMENT FRAMEWORK FOR TIME DEPENDENT COVARIATES IN THE DID SETTING TO STUDY THE CAUSAL EFFECT OF IMPLEMENTING CERTAIN EHR SYSTEM FEATURES , E G CLINICAL DECISION SUPPORT , CARE COORDINATION ACROSS DEPARTMENTS , AUTOMATED DRUG INTERACTION CHECKS , ETC , ON HOSPITAL PERFORMANCE METRICS , E G DAY MORTALITY AND READMISSION RATES , OVER TIME
399	OUR RESULTS HELP INFORM HEALTH IT ADOPTION POLICIES AND EASE THE OPERATIONAL BURDEN ON HOSPITALS BY IDENTIFYING A SUFFICIENT SET OF EHR FEATURES ASSOCIATED WITH IMPROVED QUALITY OF CARE
399	HEALTH APPLICATIONS SOCIETY MSOM , HEALTHCARE 
400	A DYNAMIC PROGRAMMING APPROACH TO BALANCING WORKLOAD IN EMS THROUGH INTRA SHIFT CREW SWAPPING
400	THIS RESEARCH INTRODUCES AN INTRA SHIFT CREW SWAPPING STRATEGY FOR EMERGENCY MEDICAL SERVICES , EMS , TO BALANCE WORKLOAD AMONG AMBULANCE CREWS WITHIN A SHIFT
400	CURRENTLY , CREWS ARE ASSIGNED TO A HOME LOCATION FOR AN ENTIRE SHIFT
400	REASSIGNING CREWS TO DIFFERENT LOCATIONS DURING A SHIFT MAY REDUCE WORKLOAD DISPARITIES WITHOUT COMPROMISING OPERATIONAL PERFORMANCE
400	WE EMPLOY DYNAMIC PROGRAMMING TECHNIQUES TO DETERMINE OPTIMAL SWAPPING SCHEDULES
400	HEALTH APPLICATIONS SOCIETY MSOM , HEALTHCARE 
400	IT UTILIZES UTILIZES DATA DRIVEN STOCHASTIC DYNAMIC PROGRAMMING 
401	DYNAMIC INCENTIVE DESIGN IN THE MEDICARE SHARED SAVINGS PROGRAM
401	THE MEDICARE SHARED SAVINGS PROGRAM , MSSP , HAS SHOWN MODEST PROGRESS AND AN INCENTIVE PARTICIPATION DILEMMA SINCE ITS INCEPTION
401	THIS WORK REDESIGNS THE MSSP CONTRACT FROM A LONG TERM PERSPECTIVE , CONSIDERING PROVIDERS HETEROGENEITY , PRIVATE INFORMATION , RANDOM SAVINGS GENERATION , AND UNCONTACTABLE EFFORTS
401	WE CONSTRUCT OPTIMAL AND APPROXIMATED CONTRACTS , JUSTIFYING THE CURRENT CONTRACT FORM WITH DIFFERENTIAL TRACKS WHILE REFINING THE SHARING RATES AND BENCHMARKS TO RESOLVE THE INCENTIVE PARTICIPATION DILEMMA
401	IT ALSO SUGGESTS HOW TO SET APPROPRIATE TARGETS IN THE HEALTHCARE PAY FOR PERFORMANCE REFORM TO PREVENT THE RATCHET EFFECT
401	WE SHOW HOW THE RATCHET EFFECT ERODES HEALTHCARE PERFORMANCE AND SUSTAINABILITY IN THE LONG RUN , SUGGESTING THE CURSE OF PUBLIC EXTRACTING PROVIDER EFFICIENCY DEVELOPED FROM EXPERIENCE
401	HEALTH APPLICATIONS SOCIETY MSOM , HEALTHCARE 
401	WE USE REAL DATA TO ESTIMATE PARAMETERS AND FACILITATE OUR POLICY DESIGN
402	PERSONALIZED DISEASE SCREENING DECISIONS
402	THE NEEDS OF PATIENTS WITH MULTIPLE CHRONIC CONDITIONS , MCC , ARE POORLY ADDRESSED BY THE CLINICAL PRACTICE GUIDELINES
402	WE DEVELOP A STOCHASTIC MODELING FRAMEWORK TO PERSONALIZE THE DISEASE SCREENING DECISIONS FOR PATIENTS WITH OR AT RISK OF DEVELOPING A CHRONIC CONDITION
402	WE PRESENT OUR FRAMEWORK BY PERSONALIZING BREAST CANCER SCREENING FOR WOMEN WITH DIABETES USING OUR MODELING FRAMEWORK
402	WE UNCOVER SOME CRUCIAL POLICY INSIGHTS THAT THE PRIOR MEDICAL COMMUNITY DID NOT ACKNOWLEDGE
402	WE FIND SOME IMPORTANT POLICY INSIGHTS THAT WERE NOT RECOGNIZED BEFORE BY THE MEDICAL COMMUNITY
402	HEALTH APPLICATIONS SOCIETY MSOM , HEALTHCARE 
403	DO NEW PARTNER AND PROCEDURE EXPOSURE INFLUENCE OPERATING ROOM NURSE TURNOVER
403	HIGH OPERATING ROOM , OR , NURSE TURNOVER PRESENTS SIGNIFICANT FINANCIAL AND OPERATIONAL CHALLENGES FOR HOSPITALS
403	HOWEVER , THERE ARE LIMITED EMPIRICAL INSIGHTS FOR OR NURSE TURNOVER DESPITE A GROWING STREAM OF EMPIRICAL STUDIES ON NURSE TURNOVER OUTSIDE OF THE OR
403	MOTIVATED BY THESE RECENT INSIGHTS , WE CONDUCT AN EXPLORATORY EMPIRICAL STUDY TO INVESTIGATE THE IMPACT OF OR NURSE SCHEDULING DATA ON PREDICTING NURSE DEPARTURE
403	USING GRANULAR DATA FOR OR NURSES ACROSS , SURGERIES , WE SHOW SUBSTANTIAL CONNECTIONS BETWEEN NURSE SCHEDULING AND DEPARTURE , WE FIND NEW PROCEDURE AND PARTNER EXPOSURES AS WELL AS DIVERSITY AND FAMILIARITY OF PARTNERS AND PROCEDURES TO SIGNIFICANTLY INFLUENCE NURSE DEPARTURE CONDITIONAL ON NURSE TENURE AND ROLE
403	HENCE , OUR STUDY DOCUMENTS THE IMPORTANCE OF NURSE SCHEDULING FOR HOSPITAL MANAGERS WHILE REDUCING COSTLY OR TURNOVER
403	HEALTH APPLICATIONS SOCIETY MSOM , HEALTHCARE 
404	RISK FACTORS ASSOCIATED WITH STROKE READMISSIONS , A SYSTEMATIC LITERATURE REVIEW
404	HOSPITAL READMISSIONS IMPOSE A SUBSTANTIAL BURDEN ON THE HEALTHCARE SYSTEM IN THE UNITED STATES , COSTING MEDICARE ABOUT BILLION PER YEAR
404	THE CENTERS FOR MEDICARE AND MEDICAID SERVICES DEFINED READMISSION AS AN INDICATOR OF POOR HOSPITAL CARE AND HAS MADE REDUCING READMISSION RATES A NATIONAL HEALTHCARE REFORM GOAL
404	THIS STUDY PERFORMS A SYSTEMATIC LITERATURE REVIEW TO IDENTIFY THE RISK FACTORS ASSOCIATED WITH STROKE READMISSIONS BETWEEN DAYS TO YEARS
404	WEB OF SCIENCE AND PUBMED WERE SEARCHED FOR STUDIES RELATED TO STROKE READMISSIONS , AND ARTICLES MET THE INCLUSION CRITERIA
404	THE STUDY FOUND STROKE READMISSION RISK FACTORS AND INTERVENTIONS TO REDUCE STROKE READMISSIONS
404	THE RESULTS OF THIS STUDY CAN ASSIST IN DESIGNING INTERVENTIONS TO REDUCE STROKE READMISSION
404	HEALTH APPLICATIONS SOCIETY MSOM , HEALTHCARE 
404	A STROKE READMISSION RISK PREDICTIVE MODEL CAN BE CREATED FROM THE RESULTS OF THIS STUDY
405	DATA ENVELOPMENT ANALYSIS OF ACUTE CARE HOSPITALS IN PENNSYLVANIA BETWEEN AND THE PENNSYLVANIA RURAL HEALTH MODEL , PARHM , WAS INTRODUCED IN JANUARY IN AN EFFORT TO ENHANCE THE FINANCIAL VIABILITY OF RURAL HOSPITALS
405	WE EMPLOY A TWO STAGE DATA ENVELOPMENT ANALYSIS , INCLUDING A SECOND STAGE REGRESSION ANALYSIS , TO EXAMINE WHETHER THE PARHM HAS IMPROVED THE PERFORMANCE OF HOSPITALS IN PENNSYLVANIA S RURAL COUNTIES USING DATA
405	HEALTH APPLICATIONS SOCIETY MSOM , HEALTHCARE 
406	PREDICTING AND MANAGING HYPOTENSION IN PERIOPERATIVE MEDICINE
406	PERIOPERATIVE HYPOTENSION CAN CAUSE POSTOPERATIVE COMPLICATIONS SUCH AS RENAL INSUFFICIENCY , MYOCARDIAL INJURY , AND INCREASED MORTALITY
406	PREDICTING HYPOTENSION PRIOR TO THE EPISODE AND TAKING PREVENTATIVE MEASURES EARLY CAN BE CRUCIAL TO IMPROVING PATIENT OUTCOMES
406	IN THIS PAPER , WE USE BOTH PRE OPERATIVE AND INTRA OPERATIVE MEDICAL RECORD DATA TO PREDICT HYPOTENSION USING BAYESIAN INFERENCE WITH MIXED RESPONSES , AND TO OPTIMIZE PRE OPERATIVE AND INTRA OPERATIVE DECISIONS USING DECISION ANALYSIS AS WELL AS REINFORCEMENT LEARNING METHODS
406	NUMERICAL RESULTS BASED ON HIGH FIDELITY MULTI PARAMETER VITAL SIGNS IN THE OPEN SOURCE VITALDB DATABASE WILL BE REPORTED
406	HEALTH APPLICATIONS SOCIETY OPT , MACHINE LEARNING APPLICATION OF MACHINE LEARNING TO HYPOTENSION IN PERIOPERATIVE MEDICINE 
407	REVISITING THE OPERATING ROOM UTILIZATION PROBLEM IN SURGICAL SERVICES
407	OPERATING ROOM , OR , SCHEDULING SIGNIFICANTLY IMPACTS PATIENT AND HEALTHCARE PROVIDER SATISFACTION AND HAS CLINICAL AND FINANCIAL EFFECTS ON HOSPITALS
407	THIS STUDY INVESTIGATES THE APPLICATION OF DATA ANALYTICS AND OPTIMIZATION TO IMPROVING OR UTILIZATION WHILE CONSIDERING PATIENTS AND PROVIDERS CRITERIA
407	WE PERFORM NUMERICAL EXPERIMENTS ON REAL DATA FROM A LARGE URBAN HOSPITAL
407	HEALTH APPLICATIONS SOCIETY OPTIMIZATION , OPT , PRACTICE 
407	WE UTILIZE HISTORICAL DATA TO PROVIDE A FRAMEWORK TO IMPROVE DECISION MAKING
408	THE IMPACT OF HOSPITAL AND PATIENT CHARACTERISTICS ON PSYCHIATRY READMISSIONS
408	THE PRACTICE MAKES PERFECT CONSTITUTING A POSITIVE VOLUME OUTCOME RELATIONSHIP IN OPERATIONS MANAGEMENT PROBLEMS , MAY CHANGE IN PEOPLE CENTRIC ENVIRONMENTS
408	WE STUDY HOSPITALS OPERATIONAL CHARACTERISTICS CONTRIBUTING TO THE READMISSION OF PSYCHIATRY PATIENTS
408	WE FIND THAT THE NUMBER OF PATIENTS ADMITTED TO A HOSPITAL INCREASES THE RISK OF READMISSION
408	IN CONTRAST , THIS RISK REDUCES WITH THE DEGREE TO WHICH A HOSPITAL SPECIALIZES IN A SPECIFIC DIAGNOSIS CLASS
408	WE PROPOSE THAT LENGTH OF STAY , LOS , MEDIATES THESE EFFECTS AND PATIENT CHARACTERISTICS MODERATE THEM
408	WE PROVIDE EVIDENCE ON THE NEGATIVE VOLUME OUTCOME AND NONLINEAR LOS OUTCOME RELATIONSHIPS
408	OUR RESULTS PROVIDE INSIGHTS FOR POLICYMAKERS TO MANAGE THE FLOW OF PSYCHIATRY PATIENTS AND THE BURDEN IMPOSED ON THE HEALTH SYSTEMS BY UNPLANNED READMISSIONS FROM PATIENTS WITH CHRONIC DISORDERS
408	HEALTH APPLICATIONS SOCIETY PUBLIC SECTOR OR MSOM , HEALTHCARE
408	WE SHOW HOW PATIENTS AND HOSPITALS INFORMATION CAN BE EXPLOITED TO UNDERSTAND OPERATIONAL MEASURES 
409	IDENTIFYING EARLY MPOX SYMPTOMS IN CLINICAL NOTES USING NATURAL LANGUAGE CLASSIFICATION
409	NATURAL LANGUAGE PROCESSING MODELS TRAINED ON CLINICAL NOTES CAN SUPPORT EXTRACTION OF CRITICAL FEATURES ASSOCIATED WITH EMERGING CONDITIONS OF PUBLIC HEALTH IMPORTANCE
409	IN THIS STUDY , A PRETRAINED TRANSFORMER MODEL WAS APPLIED TO CLINICAL NOTES WITHIN AMERICAN BOARD OF FAMILY MEDICINE PRIME REGISTRY DATA , APRIL TO JANUARY , TO IDENTIFY POTENTIAL EARLY SYMPTOMS OF MONKEYPOX VIRUS INFECTION , I E , OCCURRING BEFORE RASH ONSET OR DIAGNOSIS , AMONG PATIENTS WITH SEXUALLY TRANSMITTED DISEASE RELATED OUTPATIENT VISITS
409	THE TRANSFORMER MODEL IDENTIFIED DIFFERENTIAL SYMPTOMS BETWEEN PATIENTS WITH AND WITHOUT MPOX DIAGNOSES , A RANDOM FOREST CLASSIFIER WAS USED TO IDENTIFY SYMPTOMS HAVING THE STRONGEST ASSOCIATION WITHIN EACH SUBGROUP
409	THESE FINDINGS COULD SUPPORT EARLY DIAGNOSIS OF MPOX TO AID PREVENTION AND TREATMENT EFFORTS
409	HEALTH APPLICATIONS SOCIETY PUBLIC SECTOR OR MSOM , HEALTHCARE
410	IDENTIFYING DISPARITIES IN ACCESS TO PSYCHOSOCIAL SERVICES FOR THE MEDICAID INSURED CHILDREN IN GEORGIA
410	THE SHORTAGE OF WORKFORCE PROVIDING PSYCHOSOCIAL SERVICES IS ONE OF THE MOST CITED BARRIERS OF ACCESS TO MENTAL HEALTH TREATMENT , RESULTING IN LONG TRAVEL DISTANCES OR WAIT TIMES FOR THOSE SEEKING CARE
410	HOWEVER , THE LACK OF ACCESS DOES NOT AFFECT THE POPULATION EVENLY
410	WE QUANTIFY SUCH ACCESS DISPARITY FOR COMMUNITIES THROUGH DEVELOPING AN OPTIMIZATION MODEL WITH ESTIMATED POTENTIAL SUPPLY , CASELOAD OF PSYCHOSOCIAL SERVICES , AND DEMAND , COMMUNITY LEVEL PSYCHOTHERAPY VISIT COUNTS , FOR MEDICAID INSURED CHILDREN IN GEORGIA
410	THE STATISTICAL INFERENCE BASED ON THE MODEL OUTPUT IS THEN USED TO PROVIDE POLICY RECOMMENDATIONS ON INTERVENTIONS FOR ADDRESSING PSYCHOSOCIAL SERVICES ACCESS DISPARITIES
410	HEALTH APPLICATIONS SOCIETY PUBLIC SECTOR OR MSOM , HEALTHCARE
410	INCREASED AMOUNT OF DATA CONTRIBUTES TO BETTER ESTIMATES OF MODEL INPUTS , 
411	OPTIMIZING UNIT LOCATIONS IN EMERGENCY SERVICE SYSTEMS WITH BAYESIAN OPTIMIZATION
411	THIS PAPER PRESENTS A NEW APPROACH TO SOLVING THE OPTIMAL UNIT LOCATION PROBLEM IN A STOCHASTIC EMERGENCY SERVICE SYSTEM THAT TAKES INTO ACCOUNT STATE TRANSITIONS AND UNIT AVAILABILITIES
411	THE GOAL IS TO MINIMIZE THE SYSTEM WIDE MEAN RESPONSE TIME
411	WE SHOW THAT THIS PROBLEM IS NP HARD AND DEVELOP LOWER AND UPPER BOUNDS FOR THE OPTIMAL SOLUTION USING A SPECIAL CASE OF THE CLASSIC P MEDIAN PROBLEM
411	TO SOLVE THE PROBLEM , WE DEVELOP A BAYESIAN OPTIMIZATION ALGORITHM THAT WE SHOW ALWAYS CONVERGES TO THE OPTIMAL SOLUTION AND ACHIEVES A SUBLINEAR REGRET
411	WE EVALUATE OUR APPROACH THROUGH NUMERICAL EXPERIMENTS AND A CONSTRUCTED STUDY USING REAL DATA FROM THE ST
411	PAUL , MINNESOTA EMERGENCY RESPONSE SYSTEM AND SHOW THAT OUR MODEL CONSISTENTLY AND QUICKLY CONVERGES TO THE OPTIMAL SOLUTION
411	WE ALSO SHOW HOW OUR APPROACH CAN BE ADAPTED TO OPTIMIZE OTHER OBJECTIVE FUNCTIONS
411	HEALTH APPLICATIONS SOCIETY PUBLIC SECTOR OR MSOM , SERVICE OPERATIONS
412	ENHANCING THE EMERGENCY RESCUE SYSTEM , AN ANALYSIS OF INCORPORATING DRONE AMBULANCES
412	PERFORMING IMMEDIATE CARDIO PULMONARY RESUSCITATION WITHIN MINUTES OF CARDIAC ARREST IS CRUCIAL TO ACHIEVE A SURVIVAL RATE OF OR ABOVE
412	HOWEVER , PARAMEDICS MEDIAN ARRIVAL TIME IS MINUTES IN KOREA , WHICH EXCEEDS PATIENTS GOLDEN TIME 
412	ACCORDING TO THIS ISSUE , WE COME UP WITH AN IDEA TO USE HUMAN CREWED DRONE AMBULANCES THAT CAN TRANSPORT PARAMEDICS TO PATIENTS RAPIDLY
412	THIS STUDY AIMS TO DETERMINE THE OPTIMAL LOCATION OF A HUMAN CREWED DRONE AMBULANCE STATION TO MINIMIZE THE AVERAGE DISPATCH TIME DURING CARDIAC ARREST EMERGENCIES
412	WE EXPECT THAT THIS STUDY PROVIDES A WAY TO IMPROVE THE PATIENTS SURVIVAL RATE BY ENABLING PARAMEDICS TO RESPOND PROMPTLY , WITHIN MINUTES , TO CARDIAC ARREST CASES
412	HEALTH APPLICATIONS SOCIETY SERVICE SCIENCE 
413	MEDICAL LOCATIONS AND STAFFING FOR A MASS ENDURANCE EVENT
413	MASS ENDURANCE EVENTS POSE AN INHERENT RISK OF INJURY TO THEIR PARTICIPANTS AND MEDICAL TEAM RESPONSE TIMES DIRECTLY IMPACT PARTICIPANT OUTCOMES
413	THEREFORE , LOCATIONS OF MEDICAL STATIONS AND SPACE TIME DISTRIBUTION OF MEDICAL PERSONNEL REQUIRE CRITICAL CONSIDERATION
413	WE EMPLOY A MIXED INTEGER LINEAR PROGRAM TO A HALF MARATHON CASE STUDY , EXTENDING THE CAPACITATED FACILITY LOCATION PROBLEM TO ADDITIONALLY INCORPORATE MOVEMENT OF MEDICS BETWEEN FIXED MEDICAL LOCATIONS
413	IN AN APPLICATION AREA DOMINATED BY VARIOUS GENERAL GUIDELINES AND HISTORICAL OBSERVATIONS FOR PARTICULAR RACE COURSES , WE TAKE AN OPTIMIZATION APPROACH WHICH CAN BE APPLIED TO VARIOUS TOPOLOGIES AND EVEN NEW RACES WHICH LACK THE BENEFITS OF INSTITUTIONAL KNOWLEDGE
413	HEALTH APPLICATIONS SOCIETY SPORTS OPTIMIZATION , OPT , 
413	WE TAKE A DATA DRIVEN OPTIMIZATION APPROACH TO HALF MARATHON MEDICAL LOCATIONS AND STAFFING 
414	PHARMACEUTICAL CRO RELATIONSHIPS , ARE STRATEGIC PARTNERSHIPS THE WAY FORWARD
414	IN ORDER TO CONDUCT CLINICAL DEVELOPMENT IN A MORE COST AND TIME EFFICIENT MANNER , PHARMACEUTICAL COMPANIES HAVE LARGELY OUTSOURCED DEVELOPMENT TO CONTRACT RESEARCH ORGANIZATIONS , CROS , 
414	TO OFFER AN ANALYTICAL PERSPECTIVE ON HOW PHARMACEUTICAL MANAGERS CHOICE OF OUTSOURCING RELATIONSHIP TYPE CAN AFFECT TIMELINES , WE INVESTIGATE STRATEGIC PARTNERSHIPS AND TRANSACTIONAL ARRANGEMENTS
414	HEALTH APPLICATIONS SOCIETY 
415	A GRAPH GENERATIVE MODEL FOR IMPROVING GRAPH STRUCTURE AND REPRESENTATION FROM MEDICAL ELECTRONIC DATABASES
415	CHRONIC DISEASES , CD , ARE A MAJOR CHALLENGE TO HEALTHCARE SYSTEMS , WITH MULTIPLE CHRONIC CONDITIONS , MCC , RAISING THE RISK OF MORTALITY AND THE EMERGENCE OF NEW CDS
415	THE DEVELOPMENT OF MCC IS INFLUENCED BY SPECIFIC FACTORS AND EXISTING CONDITIONS , UNFOLDING A COMPLEX STOCHASTIC PROCESS
415	WE SUGGEST A GENERATIVE MODEL TO CAPTURE THIS COMPLEXITY , THE MODEL LEARNS DIRECTLY FROM PATIENT DATA , INCLUDING MODIFIABLE AND NON MODIFIABLE RISK FACTORS , AND EXISTING CONDITIONS
415	GRAPH STRUCTURE PLAYS A CRITICAL ROLE IN PREDICTING MCC DEVELOPMENT USING GRAPH NEURAL NETWORKS
415	AS AN N GRAPH CAN HAVE N REPRESENTATIONS , FINDING THE OPTIMAL G IS CRUCIAL , ESPECIALLY WHEN DIFFERENT ADJACENCY MATRICES CAN YIELD THE SAME GRAPH STRUCTURE
415	OUR GOAL IS TO OPTIMIZE GRAPH REPRESENTATION BASED ON THE DATA SET AND FEED IT INTO A LEARNING GRAPH NEURAL NETWORK TO STUDY THE INTERACTIONS BETWEEN FIVE CDS
415	HEALTH APPLICATIONS SOCIETY 
416	INSURANCE COVERAGE FOR TELEHEALTH SERVICES AND ANALYSIS OF APPOINTMENT SCHEDULING METRICS FOR SELECTED HEALTHCARE SPECIALTIES
416	THE COVID PANDEMIC TRIGGERED POLICY CHANGES IN , ALLOWING INSURANCE COMPANIES TO REIMBURSE TELEHEALTH SERVICES , WHICH LED TO INCREASED TELEHEALTH USE
416	HOWEVER , WITH MANY EMERGENCY RULES ENDING IN , THERE IS A CONCERN ABOUT A POTENTIAL DECREASE IN TELEHEALTH SERVICES
416	THIS STUDY EXAMINES TELEHEALTH USE IN ARKANSAS FROM TO WE EMPLOYED STATISTICAL TOOLS TO COMPARE THE NUMBER OF TELEHEALTH AND IN PERSON VISITS FOR SPECIFIC SPECIALTIES AND INVESTIGATED INSURANCE COVERAGE TRENDS FOR EACH
416	OUR EVALUATION ALSO INCLUDED A PROCEDURE TO CALCULATE APPOINTMENT PERFORMANCE METRICS SUCH AS WAITING TIME AND APPOINTMENT LENGTH
416	WE PRESENTED OUR RESULTS FOR SPECIFIC SPECIALTIES TO HIGHLIGHT THE POTENTIAL BENEFITS OF TELEHEALTH
416	HEALTH APPLICATIONS SOCIETY 
417	TRANSFER REINFORCEMENT LEARNING FOR MOMDPS WITH TIME VARYING INTERVAL VALUED PARAMETERS AND ITS APPLICATION IN PANDEMIC CONTROL
417	WE INVESTIGATE A NOVEL TYPE OF ONLINE SEQUENTIAL DECISION PROBLEM , NAMELY , I MIXED OBSERVABILITY MARKOV DECISION PROCESS WITH TIME VARYING INTERVAL VALUED PARAMETERS I 
417	WE PROPOSE A NOVEL TRANSFER REINFORCEMENT LEARNING , TRL , BASED ALGORITHMIC APPROACH THAT INGRATES TRANSFER LEARNING INTO DEEP REINFORCEMENT LEARNING IN AN OFFLINE ONLINE SCHEME
417	TO ACCELERATE THE ONLINE RE OPTIMIZATION , WE PRE TRAIN A COLLECTION OF PROMISING NETWORKS AND FINE TUNE THEM WITH NEW OBSERVATION DYNAMICALLY
417	OUR APPROACH IS THE FIRST EVER ENDEAVOR OF EMPLOYING INTENSIVE NEURAL NETWORK TRAINING IN SOLVING MDPS REQUIRING ONLINE SYSTEM IDENTIFICATION AND RE OPTIMIZATION
417	TRL OUTPERFORMS EXISTING METHODS IN SOLUTION OPTIMALITY , ROBUSTNESS , EFFICIENCY , AND SCALABILITY
417	A RETROSPECTIVE STUDY ON A PANDEMIC CONTROL SHOWS IT IMPROVES DECISION MAKING ON SEVERAL PUBLIC HEALTH METRICS
417	HEALTH APPLICATIONS SOCIETY 
418	ASSESSING THE ATTITUDES OF AL NEELAIN MEDICAL STUDENTS TOWARDS LEARNING COMMUNICATION SKILLS AND ITS IMPLICATIONS ON HEALTH PRACTICES IN CLINICAL WARDS , OBJECTIVES , WE AIM TO FIND A CORRELATION BETWEEN STUDENT S ATTITUDES AND VIEWS REGARDING COMMUNICATION SKILLS LEARNING AND THEIR PRACTICE OF COMMUNICATION SKILLS AT CLINICAL WARDSMETHODS , CROSS SECTIONAL STUDY WITH WE USED COMMUNICATION SKILLS ATTITUDE SCALE TO ASSESS STUDENT S ATTITUDES AND OPINIONS , AND MEDICAL COMMUNICATION , ME CO , TO ASSESS THEIR CLINICAL COMMUNICATION
418	WE THEN ASSESSED THE CORRELATION BETWEEN THEM AND COMPARED BOTH GENDER GROUPS IN REGARDS TO POSITIVE AND NEGATIVE ATTITUDES RESULTS , THERE WERE POSITIVE CORRELATION , P , BETWEEN POSITIVE ATTITUDES AND CLINICAL COMMUNICATION , WHILE AN INVERSE CORRELATION , P , BETWEEN NEGATIVE ATTITUDES AND CLINICAL COMMUNICATION WAS DETECTED
418	FEMALES APPEARED TO HAVE MORE POSITIVE ATTITUDES THAN MALES WHEN COMPARING THEIR MEAN RANKS , P , HEALTH APPLICATIONS SOCIETY 
419	INCORPORATING SUSTAINABILITY IN COST EFFECTIVENESS OF CANCER SURVEILLANCE PROGRAMS
419	SUSTAINABILITY IN HEALTHCARE IS BECOMING A GREAT CONCERN AS CARBON EMISSIONS PRODUCED AT HEALTHCARE FACILITIES IS SIGNIFICANT
419	COST EFFECTIVENESS ANALYSES , COMMONLY USED IN HEALTH OUTCOMES RESEARCH , DO NOT TAKE CARBON FOOTPRINT COSTS INTO ACCOUNT WHEN IDENTIFYING THE MOST COST EFFECTIVE INTERVENTION
419	MRI AND CT AS DIAGNOSTIC TOOLS ARE AND TIMES MORE COSTLY THAN ULTRASOUND PER ABDOMINAL SCAN ALTHOUGH , ESPECIALLY FOR LOW RISK GROUPS , THERE MAY NOT BE A SIGNIFICANT DIFFERENCE IN THE HEALTH OUTCOMES DUE TO UNDERGOING MRI CT VS ULTRASOUND
419	IN THIS STUDY , WE CONSIDER THE COST OF CARBON FOOTPRINT IN OUR COST EFFECTIVENESS ANALYSIS FOR LIVER CANCER SURVEILLANCE AND SUMMARIZE DIFFERENT SURVEILLANCE PROTOCOLS WITHOUT SACRIFICING HEALTH OUTCOMES
419	HEALTH APPLICATIONS SOCIETY 
420	IDENTIFYING HIGH RISK STATES AND MEDICATIONS IN T DM PATIENTS USING DEAD ENDS
420	PATIENTS WITH TYPE DIABETES OFTEN REQUIRE COMPLEX MEDICATION REGIMENS AND ARE LIKELY TO DEVELOP IRREVERSIBLE COMPLICATIONS WHICH SIGNIFICANTLY WORSEN THEIR QUALITY OF LIFE
420	WE FORMULATE DIABETES MEDICATION MANAGEMENT PROBLEM AS A REINFORCEMENT LEARNING FRAMEWORK BY REPRESENTING T DM PATIENT S DIABETIC STATUS AND ITS TRANSITION ACROSS A SEQUENCE OF VISIT RECORDS
420	DEAD ENDS DISCOVERY APPROACH IS USED TO IDENTIFY HIGH RISK PATIENT CONDITIONS AND MEDICATIONS TO AVOID THAT LIKELY LEAD TO DEAD ENDS FROM WHICH NEGATIVE OUTCOMES ARE UNAVOIDABLE
420	WE SET NEGATIVE OUTCOMES FOR DIABETES PATIENTS AS DEVELOPING DIABETIC COMPLICATIONS AND AIM TO IDENTIFY HEALTH CONDITIONS FROM WHICH DIABETES COMPLICATIONS ARE HIGHLY LIKELY TO DEVELOP AND PINPOINT MEDICATIONS THAT SHOULD BE AVOIDED
420	HEALTH APPLICATIONS SOCIETY 
421	IDENTIFYING ACCESS AND ATTENDANCE DISPARITIES TO OPIOID RELATED PREVENTION PROGRAMS IN PENNSYLVANIA
421	THE OPIOID EPIDEMIC IS A SIGNIFICANT PUBLIC HEALTH CRISIS IN THE UNITED STATES , WITH RURAL AREAS EXPERIENCING GREATER CHALLENGES IN ACCESS TO PREVENTION PROGRAMS
421	THIS STUDY EXAMINES THE IMPACT OF COUNTY POPULATION DENSITY ON ACCESS AND ATTENDANCE TO OPIOID RELATED PREVENTION PROGRAMS IN PENNSYLVANIA
421	USING DATA FROM FOUR COUNTIES AND MULTILEVEL OLS REGRESSION MODELS , THE ANALYSIS REVEALS THAT RURAL COUNTIES HAVE REDUCED ACCESS AND ATTENDANCE COMPARED TO URBAN COUNTIES
421	FINDINGS SUGGEST THE NEED FOR TARGETED STRATEGIES TO IMPROVE ACCESS AND ATTENDANCE IN RURAL AREAS , THEREBY REDUCING THE BURDEN OF OPIOID OVERDOSES
421	HEALTH APPLICATIONS SOCIETY 
422	SURGE LEVEL RESPONSES IN EMERGENCY MEDICAL SERVICES
422	THIS STUDY PROPOSES A MACHINE LEARNING AND SIMULATION BASED APPROACH FOR CATEGORIZING SURGE LEVELS IN EMERGENCY MEDICAL SERVICES
422	INSTEAD OF USING TRADITIONAL PERFORMANCE METRICS , THIS STUDY WILL USE SIMULATION TO EVALUATE THE MACHINE LEARNING BASED CATEGORIZATION MODELS
422	PARTICULARLY , SIMULATION S RESPONSES TO DIFFERENT INTERVENTIONS BASED ON DIFFERENT SURGE LEVELS CATEGORIZATION ARE USED TO EVALUATE THE MACHINE LEARNING MODELS
422	HEALTH APPLICATIONS SOCIETY 
423	ACCESS VERSUS PHYSICAL ACCESS , AN EXAMINATION OF TELEHEALTH ADOPTION
423	WHILE OUR CURRENT CONCEPTION OF TELEMEDICINE HAS EXISTED FOR HALF A CENTURY , BEGINNING WITH THE SPACE TECHNOLOGY APPLIED TO RURAL PAPAGO ADVANCED HEALTH CARE , STARPAHC , , ONLY RECENT TELECOMMUNICATION ADVANCEMENTS HAVE INCREASED THE PACE OF ADOPTION AMONGST PATIENTS AND PRACTITIONERS
423	THEREFORE , WE EXAMINE THE IMPACT OF TELEMEDICINE ADOPTION ON PRIMARY CARE USE , SPECIFICALLY EXAMINING THE CONDITIONS BY WHICH TELEHEALTH CONSULTATIONS BECOME A SUBSTITUTE FOR IN PERSON CARE OR A COMPLIMENT TO IN PERSON CARE
423	USING A UNIQUE DATASET OF INSURANCE CLAIMS FOR PRIMARY CARE VISITS , WE EXAMINE IN PERSON , ASYNCHRONOUS , AND SYNCHRONOUS PRIMARY CARE VISITS
423	HEALTH APPLICATIONS SOCIETY UTILIZES A MULTITUDE OF PUBLIC RESOURCES TO TRACK THE DEPLOYMENT OF TELEHEALTH 
424	EMPLOYEES RESPONSE TO ARTIFICIAL INTELLIGENCE
424	THIS STUDY EXPLORES THE EMOTIONAL RESPONSES OF INDIVIDUAL EMPLOYEES TOWARDS THE INTRODUCTION OF ARTIFICIAL INTELLIGENCE , AI , IN THEIR WORK
424	PREVIOUS RESEARCH HAS FOCUSED ON THE MACROECONOMIC AND LABOR MARKET IMPACTS OF AI , BUT LITTLE ATTENTION HAS BEEN GIVEN TO EMPLOYEES EMOTIONAL REACTIONS
424	DRAWING ON EXISTING FRAMEWORKS , THE STUDY EXAMINES EMPLOYEES APPRAISALS OF AI ADOPTION , THEIR EMOTIONAL RESPONSES , AND THEIR SUBSEQUENT REACTIONS
424	BY INVESTIGATING THE EMOTIONAL ASPECTS OF AI IMPLEMENTATION , THIS RESEARCH AIMS TO PROVIDE VALUABLE INSIGHTS INTO THE HUMAN EXPERIENCES AND PERCEPTIONS ASSOCIATED WITH THIS TRANSFORMATIVE TECHNOLOGY
424	INFORMATION SYSTEMS ARTIFICIAL INTELLIGENCE TECHNOLOGY , INNOVATION MANAGEMENT AND ENTREPRENEURSHIP
424	MANAGEMENT SCIENCE HAS RELATIONS WITH EMPLOYEES AND DATA REVOLUTION IS RELATED WITH AI 
425	UNDERSTANDING CHILDREN S DIGITAL MATURITY , A MACHINE LEARNING APPROACH
425	OUR RESEARCH UTILIZES SOPHISTICATED MACHINE LEARNING TO IDENTIFY PATTERNS OF ICT USAGE IN CHILDREN ANALYZE THEIR DIGITAL MATURITY
425	USING A DATA DRIVEN APPROACH WE CLASSIFY CHILDREN INTO DIFFERENT CATEGORIES BASED ON THEIR DIGITAL MATURITY ICT USAGE PATTERNS WITH HIGH ACCURACY
425	OUR FINDINGS SUGGEST THAT CHILDREN WITH HIGH DIGITAL MATURITY ARE RESPONSIBLE , RESPECTFUL SELF LEARNERS , WHILE CHILDREN WITH MODERATE DIGITAL MATURITY LACK INDIVIDUAL GROWTH
425	THOSE WITH LOW DIGITAL MATURITY ARE PRONE TO MALADAPTIVE BEHAVIORS , CYBERCRIMES POOR WELLBEING
425	OUR RESEARCH PROVIDES VALUABLE INSIGHTS INTO DIGITAL INEQUALITIES AMONG CHILDREN , ALLOWING TARGETED INTERVENTIONS TO ALLEVIATE DIFFERENCES IMPROVE FAMILY FUNCTIONING
425	THE IMPLICATIONS OF THIS RESEARCH EXTEND TO SCHOOLS AS OUR RESULTS CAN INFORM EFFECTIVE PROGRAMS PROMOTING HIGHER DIGITAL MATURITY IN CHILDREN
425	INFORMATION SYSTEMS ARTIFICIAL INTELLIGENCE 
425	USING ML TO IDENTIFY PATTERNS OF ICT USAGE IN CHILDREN WE BETTER UNDERSTAND YOUTH DIGITAL BEHAVIOR 
426	AN INCREMENTAL APPROACH TO TEAM FORMATION , A MARKOV DECISION PROCESS FRAMEWORK
426	FINDING GOOD TEAM MEMBERS FOR COMPLEX TASKS IN ONLINE PLATFORMS CAN BE DIFFICULT WHEN MANY CANDIDATES WITH DIVERSE SKILLS ARE AVAILABLE
426	WE PROPOSE A NOVEL RECOMMENDATION FRAMEWORK THAT FORMS TEAMS INCREMENTALLY USING A MARKOV DECISION PROCESS
426	THE FRAMEWORK SUGGESTS POTENTIAL COLLABORATORS TO A FOCAL PARTICIPANT , REQUESTER , BASED ON THE CURRENT TEAM STATE AND THE EXPECTED CONTRIBUTION OF POTENTIAL CANDIDATES
426	OUR APPROACH AIMS TO OPTIMIZE TEAM PERFORMANCE WHILE ACCOUNTING FOR THE UNCERTAINTY ASSOCIATED WITH CANDIDATES WILLINGNESS TO JOIN THE TEAM
426	INFORMATION SYSTEMS COMPUTING SOCIETY APPLIED PROBABILITY 
426	OUR WORK SHOWS HOW OR MS CAN ENHANCE ONLINE COLLABORATION WITH DATA DRIVEN METHODS 
427	A UNIFIED DEMAND FORECASTING FRAMEWORK FOR ECOMMERCE ADVERTISING PRODUCTS
427	DEMAND FORECAST PLAYS A CRITICAL ROLE IN SALES PLANNING AND MANAGEMENT OF ADVERTISING BUSINESS , WHICH REQUIRES ACCURATE PREDICTION OF THE EXPECTED ADVERTISING PRODUCT DEMAND AT SCALE FOR WALMART ECOMMERCE
427	HOWEVER , UNCERTAINTY IN CUSTOMER BEHAVIORS , SUPPLY CHAIN DISRUPTIONS , DEMAND SURGES AND PLUMMETS , LACK OF HISTORICAL RECORDS AND PATTERNS CAN MAKE THE FORECASTS INADEQUATE
427	IN OUR WORK , WE INTRODUCE A FRAMEWORK THAT INCORPORATES VARIOUS MACHINE LEARNING MODELING METHODOLOGIES , INCLUDING STATISTICAL MODELS AND DEEP LEARNING BASED TRANSFER LEARNING MODELS , ETC , AS WELL AS EVALUATION METHODS TO HELP MAKE ROBUST DEMAND FORECASTS FOR ALL ADVERTISING PRODUCTS AND ACCOUNTS IN A HIERARCHICAL STRUCTURE
427	AT THE END , WE ALSO DISCUSS OUR EXPERIMENTAL FINDINGS AND DEMONSTRATE THE EFFECTIVENESS AND EFFICIENCY OF OUR PROPOSED FRAMEWORK
427	INFORMATION SYSTEMS DATA MINING ARTIFICIAL INTELLIGENCE
427	OUR WORK TALK USES OR MS MODELS TO GUIDE DECISION MAKING AND PRODUCE MEANINGFUL DATA IN THE CYCLE
428	THE SPREAD OF A POST OF AN INFLUENCER VIRAL MARKETING ON TWITTER A BRANCHING PROCESS APPROACH
428	THIS RESEARCH INVESTIGATES HOW AN INFLUENCER S TWEET THAT PROMOTES A PRODUCT SPREAD AMONG TWITTER USERS
428	ONCE AN INFLUENCER UPLOADS A MARKETING TWEET , HIS FOLLOWERS , THE FIRST GENERATION , VIEW IT , AND PARTS OF THEM CAN RETWEET IT , AND SHOW IT TO THEIR FOLLOWERS
428	THIS PROCESS CONTINUES UNTIL NO USER IN A LATER GENERATION RETWEETS THE TWEET
428	WE SUGGEST A BRANCHING PROCESS MODEL THAT PREDICTS THE NUMBER OF RETWEETS FROM EACH GROUP OF FOLLOWERS BASED ON THE ANALYZING DATA WE CRAWLED THROUGH THE TWITTER SERVER
428	THE MODEL LET US MEASURE THE VIRAL MARKETING EFFECT ON TWITTER BASED ON THE IMPRESSION NUMBER AND VIEWERS INTERESTS , HELPING FIRMS TO EXPECT A RETURN FROM THEIR EXPENDITURE ON INFLUENCER MARKETING ON THE SOCIAL NETWORK SERVICE PLATFORM
428	INFORMATION SYSTEMS DATA MINING EBUSINESS
429	CYBER RISK MANAGEMENT OF RANSOMWARE ATTACKS , A SEMI STRUCTURED DATA MODEL APPROACH
429	THIS STUDY ATTEMPTS TO MITIGATE RANSOMWARE ATTACKS BY COMBINING STRUCTURED AND UNSTRUCTURED DATA
429	IT COMPRISES THREE MODULES
429	SPECIFICALLY , OUR CYBER RISK ASSESSMENT MODULE USES INPUT SUCH AS RANSOMWARE ATTACK CHARACTERISTICS , ATTACK RANSOM AMOUNT AND DURATION , VULNERABILITY DATA SUCH AS VULNERABILITY COUNTS , SEVERITY , TRENDS , AND TOPICS EXTRACTED FROM WEB ARTICLES
429	FOLLOWING THIS , WE CALCULATE THE EXPECTED LOSS RESULTING FROM RANSOMWARE ATTACKS
429	WE CONCLUDE BY SUGGESTING CYBER RISK MITIGATION STRATEGIES SUCH AS SELF PROTECTION , TECHNOLOGY , COMPLIANCE , AND LEGAL DETERRENCE , , SELF INSURANCE , OR CYBER INSURANCE
429	INFORMATION SYSTEMS DATA MINING SHARING ECONOMY , INNOVATIVE MARKETPLACES , AND DATA 
430	ENHANCING MACHINE LEARNING PERFORMANCE WITH INSTANCE BASED DATA COLLECTION
430	ADVANCEMENTS IN MACHINE LEARNING , ML , PERFORMANCE ARE INCREASINGLY RELIANT ON DATA DIVERSITY
430	TRADITIONAL CLASS BASED DATA COLLECTION METHODS , HOWEVER , CAN LIMIT THIS DIVERSITY DUE TO THEIR PREDEFINED CATEGORIES AND ATTRIBUTES , POTENTIALLY LEADING TO AN INADEQUATE REPRESENTATION OF COMPLEX SUBJECTS
430	IN CONTRAST , INSTANCE BASED DATA COLLECTION CAPTURES A MORE COMPREHENSIVE ATTRIBUTES , THEREBY ENHANCING THE ACCURACY AND RELIABILITY OF ML MODELS
430	BY IDENTIFYING THE MOST RELEVANT ATTRIBUTES AND POTENTIAL CONFOUNDERS , AND AVOIDING OVERFITTING , INSTANCE BASED METHODS OFFER A RICHER DATA SOURCE FOR FEATURE SELECTION
430	EMPHASIZING THE POTENTIAL OF INSTANCE BASED DATA COLLECTION , THIS STUDY HIGHLIGHTS ITS ROLE IN IMPROVING ML PERFORMANCE ACROSS VARIOUS APPLICATIONS , PROVIDING A MORE ACCURATE , DIVERSE , AND EFFECTIVE APPROACH FOR DATA GATHERING IN THE ML FIELD
430	INFORMATION SYSTEMS DATA DRIVEN INNOVATIONS IN OR EDUCATION ARTIFICIAL INTELLIGENCE
430	TRADITIONAL CLASS BASED DATA COLLECTION METHODS , HOWEVER , CAN LIMIT THIS DIVERSITY DUE TO THEIR PRED 
431	WHY DO PEOPLE GIVE UP THEIR PRIVACY WHEN INTERACTING WITH CHATBOTS THAT USE ARTIFICIAL INTELLIGENCE
431	AI CHATBOTS ARE BECOMING POPULAR FOR CUSTOMER CARE AND PERSONALIZED RECOMMENDATIONS
431	HOWEVER , PRIVACY CONCERNS HAVE ARISEN REGARDING THEIR USE
431	THIS PAPER ADDRESSES THE POTENTIAL THREATS POSED BY AI CHATBOTS TO USERS DATA AND PRIVACY
431	IT HIGHLIGHTS HOW CERTAIN HOSTING SERVICES MAY COLLECT AND UTILIZE DATA WITHOUT CLEAR DISCLOSURE , RAISING THE RISK OF PROFILING AND TARGETED ADVERTISING
431	THERE ARE ALSO RISKS OF HACKING , IDENTITY THEFT , AND UNAUTHORIZED DATA SHARING
431	THE RESEARCH AIMS TO INVESTIGATE THE FACTORS INFLUENCING USERS PRIVACY CONCERNS AND THEIR WILLINGNESS TO DISCLOSE INFORMATION WHEN INTERACTING WITH AI CHATBOTS
431	THE STUDY AIMS TO EXPLORE THE FACTORS INFLUENCING USERS PRIVACY CONCERNS AND THEIR WILLINGNESS TO SHARE INFORMATION WITH AI CHATBOTS
431	IT SUGGESTS STRATEGIES TO PROTECT USER PRIVACY AND PROMOTE RESPONSIBLE USE OF AI CHATBOT TECHNOLOGY
431	INFORMATION SYSTEMS DECISION ANALYSIS SOCIETY ARTIFICIAL INTELLIGENCE
432	A CROSS CULTURAL COMPARISON OF INFORMATION SEEKING AND UNCERTAINTY REDUCTION AMONG NEWCOMERS DURING ORGANIZATIONAL ENTRY
432	NATIONAL CORPORATIONS HAVE UNIQUE ONBOARDING PROCESSES , DURING WHICH NEWCOMERS EXPERIENCE UNCERTAINTY BECAUSE THEY CANNOT PREDICT VETERAN EMPLOYEES BEHAVIOR
432	NEWCOMERS CAN REDUCE THEIR UNCERTAINTY BY ENGAGING IN INFORMATION SEEKING BEHAVIORS
432	THIS STUDY INVESTIGATES THE EFFECTS OF INTERNATIONAL AND DOMESTIC NEWCOMERS INFORMATION SEEKING BEHAVIORS IN REDUCING THEIR UNCERTAINTY DURING THE ENTRY PHASE OF U S NATIONAL CORPORATIONS
432	A SURVEY WILL BE CREATED TO CAPTURE CROSS SECTIONAL DATA ADDRESSING THE THEORETICAL CONSTRUCTS NEWCOMERS WILL BE RECRUITED , AND RESPOND TO MEASURES , OF INFORMATION SEEKING BEHAVIORS , INFORMATION ACCESSIBILITY , UNCERTAINTY REDUCTION , FAMILIARITY OF ORGANIZATIONAL CULTURE , AND INTERCULTURAL COMMUNICATION COMPETENCE , THAT WILL EMPLOY A LIKERT TYPE POINT SCALE , STRONGLY DISAGREE TO STRONGLY AGREE , 
432	INFORMATION SYSTEMS DIVERSITY , EQUITY , AND INCLUSION OPT , OPTIMIZATION UNDER UNCERTAINTY
433	ORDER BIAS IN ONLINE REVIEW HELPFULNESS , IDENTIFICATION , SOURCE , AND MITIGATION
433	MANY ONLINE PLATFORMS ENABLE A HELPFUL REVIEW VOTE TO COLLECT READERS PERCEPTIONS OF REVIEW HELPFULNESS SO AS TO RANK REVIEWS EFFICIENTLY
433	THIS STUDY FLIPS THIS PERSPECTIVE AND INVESTIGATES THE INFLUENCE OF THE RANKING ORDER ON REVIEW VOTING , THEREBY REVEALING AN ORDER BIAS IN ONLINE REVIEW HELPFULNESS
433	BY COLLECTING AND ANALYZING THE DYNAMIC RANKING ORDERS OF , REVIEWS UNDER SIX PRODUCT CATEGORIES WITHIN DAYS AS WELL AS THE ASSOCIATED VOTING INFORMATION , WE UNCOVER THAT , THE RANKING ORDER NEGATIVELY AFFECTS REVIEW HELPFULNESS
433	THE REVIEW THAT APPEARS LOWER IN THE RANKING ARE LESS HELPFUL BECAUSE OF A DECREASE IN THE VISIBILITY AND THE INCREMENTAL INFORMATIVENESS
433	WE PROPOSE AN ADJUSTMENT METHOD TO MITIGATE THE ORDER BIAS
433	THIS STUDY OFFERS GUIDELINES FOR THE PLATFORM TO MAKE NECESSARY ADJUSTMENTS WHEN ADOPTING USER VOTING AS THE WISDOM OF THE CROWD 
433	INFORMATION SYSTEMS EBUSINESS DATA MINING
434	ILLEGAL CONTENT AND MONITORING STRATEGIES ON DIGITAL PLATFORMS
434	IN THIS TALK , WE CONSIDER A SCENARIO WHERE A SUBSCRIPTION BASED LEGAL CONTENT HAS TO COMPETE WITH FREE BUT ILLEGAL CONTENT ON THE SAME DIGITAL PLATFORM
434	IN BOTH THESE SCENARIOS , THE DIGITAL PLATFORM GENERATES REVENUE FOR ITSELF
434	WE ANALYZE DIFFERENT CONTENT MONITORING STRATEGIES AND IDENTIFY CONDITIONS UNDER WHICH IT IS BENEFICIAL FOR THE PLATFORM TO EXERT HIGHER MONITORING EFFORTS THAN THE CONTENT PROVIDER
434	WE ALSO FIND CONTENT MONITORING STRATEGIES THAT GENERATE HIGHER PAYOFFS FOR THE DIGITAL PLATFORM AND THE CONTENT PROVIDER
434	INFORMATION SYSTEMS EBUSINESS SERVICE SCIENCE 
435	PRIVACY DECISIONS , THE ROLES OF INDIVIDUAL S MINDSET AND THE DEFAULT SETTING
435	RECENT PRIVACY SCANDALS HAVE STIRRED INCREASED INTEREST IN UNDERSTANDING CONSUMERS DECISIONS ON PRIVACY PROTECTION AND DISCLOSURE
435	THIS RESEARCH COMPARES THE PRIVACY DECISIONS OF INDIVIDUALS WITH TWO DIFFERENT MINDSETS , I MAXIMIZERS I WHO STRIVE FOR THE BEST POSSIBLE CHOICE , AND I SATISFICERS I WHO ACCEPT A GOOD ENOUGH OPTION
435	AN ONLINE EXPERIMENT WAS CONDUCTED TO MANIPULATE MINDSETS AND DEFAULT PRIVACY SETTINGS
435	THE RESULTS SHOW THAT INDIVIDUALS LEAN TOWARDS THE DEFAULT PRIVACY SETTING , PARTICULARLY MAXIMIZERS
435	FOR EXAMPLE , WHEN ASKED TO CHOOSE A PRIVACY OPTION FOR POST ON YOUR PRIVATE PAGE , SATISFICERS ARE TIMES MORE LIKELY AND MAXIMIZERS ARE TIMES MORE LIKELY TO CHOOSE EVERYONE WHEN PRESENTED WITH THE EVERYONE DEFAULT , VS ONLY ME DEFAULT , 
435	INFORMATION SYSTEMS EBUSINESS SOCIAL MEDIA ANALYTICS
435	RELATED TO DATA PRODUCTION , IT STUDIES INDIVIDUAL S ONLINE DATA SHARING DECISION MAKING 
436	THE IMPACT OF GAMIFIED COMPETITIVE STRUCTURES ON USER ENGAGEMENT IN THE EDUCATIONAL ONLINE PLATFORMS
436	WE STUDY THE IMPACT OF LEADERBOARD COMPETITION INTENSITY ON USER ENGAGEMENT IN AN ONLINE LEARNING PLATFORM CONTEXT
436	OUR RANDOMIZED FIELD EXPERIMENT WITH STUDENTS PREPARING FOR THE FINAL SCHOOL EXAMS REVEALS THAT STUDENTS ENGAGE MORE WHEN COMPETITION IS LESS INTENSE
436	SPECIFICALLY , THEY ARE MORE ENGAGED WHEN COMPETING AGAINST GROUPS WITH MORE SPREAD OUT SCORES AND WHEN THEY ARE FARTHER AWAY FROM BOTH THEIR UPWARD AND DOWNWARD COMPETITORS
436	MOREOVER , LOW CONFIDENCE STUDENTS BECOME MORE ACTIVE WHEN THEIR UPWARD COMPETITOR IS FARTHER AWAY , WHILE COMPETITIVE STUDENTS DECREASE ACTIVITY UNDER THE SAME CONDITIONS
436	OUR FINDINGS SUGGEST THAT IMPLEMENTING A COMPETITIVE FEATURE DEMANDS ATTENTION TO THE CREATED COMPETITIVE CONDITIONS AND THE TYPE OF USER PARTICIPATING IN THE COMPETITIVE ENVIRONMENT
436	A ONE SIZE FITS ALL APPROACH IS NOT EFFECTIVE IN PROMOTING USER ENGAGEMENT
436	INFORMATION SYSTEMS EBUSINESS TECHNOLOGY , INNOVATION MANAGEMENT AND ENTREPRENEURSHIP
437	CONNECTEDNESS FOR ON DEMAND LEARNING , A FIELD EXPERIMENT ON SOCIAL PRESENCE CUES
437	ON DEMAND LEARNING PLATFORMS FACE A FUNDAMENTAL CHALLENGE OF ENHANCING USERS LEARNING OUTCOMES AND RETAINING THEM BY CONSTANTLY MOTIVATING THEM TO MAKE PROGRESS AND COMPLETE COURSES
437	TO ADDRESS THIS CHALLENGE , WE PROPOSE A NOVEL APPROACH BASED ON SOCIAL PRESENCE THEORY THAT ENHANCES THE LEARNER S CONNECTEDNESS TO THE INSTRUCTOR AND PLATFORM , LEADING TO INCREASED ENGAGEMENT AND PROGRESS
437	SPECIFICALLY , WE EXAMINE THE EFFICACY OF PUSH NOTIFICATIONS WITH SOCIAL PRESENCE CUES RELATED TO INSTRUCTOR AND HUMOR BASED ON INTERNET MEMES , BY CONDUCTING A RANDOMIZED FIELD EXPERIMENT
437	THE RESULTS INDICATE THAT BOTH TREATMENTS INCREASE CLICKTHROUGH AND PROGRESS RATES , BUT ONLY INSTRUCTOR INITIATED INTERVENTIONS RETAIN A POSITIVE EFFECT OVER TIME
437	THIS STUDY PROVIDES VALUABLE INSIGHTS INTO THE EFFECTIVE USE OF SOCIAL PRESENCE AND MEME MARKETING IN ON DEMAND LEARNING
437	INFORMATION SYSTEMS EBUSINESS 
438	AUTOMATED BENCHMARKING FOR HIGH PERFORMANCE COMPUTING WORKLOADS IN LIFE SCIENCES
438	RUNNING HIGH PERFORMANCE COMPUTING WORKLOADS SUCH AS GENOMICS WORKFLOWS REQUIRES LARGE POOLS OF COMPUTE INSTANCES THAT PROCESS DATA AT A PETABYTE SCALE
438	BENCHMARKING HELPS EVALUATE WORKFLOW PERFORMANCE AND DISCOVER FASTER AND CHEAPER WAYS OF RUNNING THEM
438	IN PRACTICE , PERFORMANCE EVALUATIONS HAPPEN IRREGULARLY BECAUSE OF THE ASSOCIATED HEAVY LIFTING
438	USING ACTION RESEARCH , WE BUILD A PROTOTYPE BASED ON CLOUD COMPUTING SERVICES OF AMAZON WEB SERVICES TO HELP LIFE SCIENCE RESEARCH TEAMS AUTOMATE SUCH EVALUATIONS
438	OUR AUTOMATED BENCHMARKING SOLUTION MEASURES PERFORMANCE ON TIMING AND PRICING DIMENSIONS AND PROVIDES , , MORE ACCURATE ENTERPRISE RESOURCE PLANNING BY PERFORMING HISTORICAL ANALYTICS , , LOWER COST TO THE BUSINESS BY COMPARING PERFORMANCE ON DIFFERENT RESOURCE TYPES , AND , COST TRANSPARENCY TO THE BUSINESS BY QUANTIFYING PERIODICAL CHARGEBACK
438	INFORMATION SYSTEMS EMERGING TECHNOLOGIES AND APPLICATIONS FINANCE
439	USER GENERATED CONTENT SHAPES JUDICIAL REASONING , EVIDENCE FROM A RANDOMIZED CONTROL TRIAL ON WIKIPEDIA
439	WHILE WIKIPEDIA ARTICLES ARE EASILY ACCESSIBLE , THEY HAVE UNKNOWN PROVENANCE AND RELIABILITY AND IS PROBLEMATIC TO BE USED IN PROFESSIONAL SETTINGS
439	USING AN RCT , WE FIND THAT THE PRESENCE OF A WIKIPEDIA ARTICLE ABOUT IRISH SUPREME COURT DECISIONS MAKES IT MORE LIKELY THAT THE CORRESPONDING CASE WILL BE CITED IN SUBSEQUENT JUDGMENTS
439	THESE EFFECTS ARE ONLY PRESENT FOR CITATIONS BY THE HIGH COURT , NOT FOR THE HIGHER LEVELS OF THE JUDICIARY
439	SINCE THE HIGH COURT FACES HIGHER CASELOADS , THIS MAY INDICATE THAT SETTINGS WITH GREATER TIME PRESSURES ENCOURAGE GREATER RELIANCE ON WIKIPEDIA
439	OUR RESULTS ADD TO THE GROWING RECOGNITION THAT WIKIPEDIA AND OTHER FREQUENTLY ACCESSED SOURCES OF USER GENERATED CONTENT HAVE PROFOUND EFFECTS ON IMPORTANT SOCIAL OUTCOMES
439	GREATER ATTENTION SHOULD THEREFORE BE PAID TO ENSURING THAT THEY CONTAIN THE HIGHEST QUALITY OF INFORMATION
439	INFORMATION SYSTEMS EMERGING TECHNOLOGIES AND APPLICATIONS 
440	NO NEWS ABOUT CLIMATE ACTION IS GOOD NEWS FOR THE FIRM
440	HEIGHTENED SOCIETAL FOCUS ON CORPORATE ENVIRONMENTAL RESPONSIBILITY ENCOURAGES FIRMS TO PUBLICIZE CLIMATE ACTIONS VIA MEDIA
440	YET , MEDIA SPOTLIGHT CAN ALSO UNVEIL NEGATIVE ENVIRONMENTAL ACTIVITIES
440	DESPITE EXTENSIVE STUDY ON MEDIA INFLUENCE ON CORPORATE FINANCE , THE IMPACT OF MEDIA SPOTLIGHT ON FIRMS CLIMATE ACTION ON THEIR FINANCIAL PERFORMANCE REMAINS UNEXPLORED
440	OUR STUDY FILLS THIS VOID , REVEALING THAT INCREASED MEDIA SPOTLIGHT NEGATIVELY IMPACTS FINANCIAL PERFORMANCE DUE TO HIGHER COSTS INCURRED BY THE FIRM
440	INTERESTINGLY , THIS NEGATIVE EFFECT IS LESS FOR HIGH POLLUTION INDUSTRIES AND FIRMS WITH POOR ENVIRONMENTAL PERFORMANCE
440	THIS RESEARCH INFORMS CORPORATE LEADERS ON THE FINANCIAL IMPLICATIONS OF MEDIA EXPOSURE OF ENVIRONMENTAL INITIATIVES , GUIDING INFORMED DECISION MAKING ABOUT MEDIA ENGAGEMENT AND STRATEGIC RESPONSES
440	INFORMATION SYSTEMS ENRE , ENVIRONMENT AND SUSTAINABILITY SOCIALLY RESPONSIBLE AND SUSTAINABLE OPERATIONS
441	ENHANCING CARDIOVASCULAR HEALTH WITH FEDERATED ON DEVICE RECOGNITION OF ENVIRONMENTAL AND SOCIAL ACTIVITIES
441	CARDIOVASCULAR HEALTH REMAINS A SIGNIFICANT PUBLIC HEALTH CONCERN WORLDWIDE
441	WE PRESENT A NOVEL APPROACH TO ENHANCE CARDIOVASCULAR HEALTH BY LEVERAGING FEDERATED ON DEVICE RECOGNITION OF ENVIRONMENTAL AND SOCIAL ACTIVITIES EMPLOYING MACHINE LEARNING TECHNIQUES AND UBIQUITOUS MOBILE DEVICES
441	WE DELIVER INTELLIGENT INTERVENTIONS UTILIZING ON DEVICE SENSORS AND DATA WHILE ACTIVITIES ARE MONITORED AND ANALYZED TO IDENTIFY THEIR RELATIONSHIP WITH POOR SELF CARE FACTORS FOR CARDIOVASCULAR HEALTH
441	THIS INTELLIGENT INTERVENTION SYSTEM PROVIDES PERSONALIZED RECOMMENDATIONS AND PRESERVES PRIVACY WHILE LEARNING COLLABORATIVELY
441	THE OBJECTIVE IS TO EMPOWER INDIVIDUALS TO ADOPT HEALTHIER BEHAVIORS AND IMPROVE CARDIOVASCULAR CONDITIONS
441	INFORMATION SYSTEMS HEALTH APPLICATIONS SOCIETY ARTIFICIAL INTELLIGENCE
441	WE INTEGRATE ARTIFICIAL INTELLIGENCE , AI , TECHNIQUES TO ANALYZE DATA PATTERNS , MAKE PREDICTIONS , AND 
442	IDENTIFYING FAKE PHYSICIAN REVIEWS USING TRANSFORMERS AND GENERATIVE MODELS , EVIDENCE FROM A NOVEL DATASET
442	THIS STUDY COMPARES STATE OF THE ART LANGUAGE MODELS , GPT AND BERT IN RECOGNIZING TEXTUAL PATTERNS TO DETECT FRAUDULENT REVIEWS
442	THE DATASET CONSISTS OF PRE ANNOTATED PHYSICIAN REVIEWS , LABELLED AS FRAUDULENT IF SELF AUTHORED BY THE DOCTORS AND AUTHENTIC IF PROVIDED BY THE PATIENTS
442	THIS WORK HIGHLIGHTS THE COMPARATIVE CAPABILITIES OF THE TWO MODELS AND ESTABLISHES THE EFFICACY OF PATTERN RECOGNITION WITH GPT GPT S SEQUENTIAL TEXT GENERATION FACILITATES ENHANCED INTERPRETABILITY , PROVIDING A MORE INTUITIVE UNDERSTANDING , WHEREAS BERT S WORD LEVEL EMBEDDINGS POSE CHALLENGES IN STRAIGHTFORWARD INTERPRETATION
442	GPT EXCELS IN CAPTURING SUBTLE NUANCES LEVERAGING ITS VAST PARAMETER SIZE , AND SHOWCASES GENERALIZABILITY OF FINDINGS
442	INFORMATION SYSTEMS HEALTH APPLICATIONS SOCIETY COMPUTING SOCIETY
442	THIS WORK APPLIES STATE OF THE ART ALGORITHMS ON A LARGE DATASET OF DOCTOR REVIEWS 
443	SATIATION AND MOTIVATION FOR THE LONG RUN , WHAT MOTIVATES PHYSICIANS IN ONLINE COMMUNITIES
443	A VARIETY OF INCENTIVES HAVE BEEN ADOPTED TO ENCOURAGE VOLUNTARY CONTRIBUTIONS IN ONLINE COMMUNITIES
443	HOWEVER , THE MAJORITY OF RELATED RESEARCH EITHER EXAMINES THE EFFECT OF INCENTIVES OVER THE SHORT RUN OR IGNORES THE INTERPLAY BETWEEN SUPPLY SIDE CONTRIBUTIONS AND DEMAND SIDE REQUESTS IN MULTISIDED PLATFORMS
443	FROM A TWO SIDED PERSPECTIVE , OUR STUDY INVESTIGATES THE TIME VARYING EFFECTS OF DIFFERENT INCENTIVES ON PHYSICIAN CONTRIBUTIONS IN A DOCTOR PATIENT INTERACTION PLATFORM
443	THE MAIN CHALLENGE FACED WHEN ADDRESSING THIS PROBLEM IS A SIMULTANEITY AND REVERSE CAUSALITY ISSUE
443	WE ADOPT SIMULTANEOUS EQUATION MODEL TO COPE WITH THIS PROBLEM
443	OUR RESULTS VERIFY THE EXISTENCE OF SATIATION AND THE TIME VARYING EFFECTS OF DIFFERENT INCENTIVES ON THE EXAMINED PHYSICIANS EFFORTS
443	INFORMATION SYSTEMS HEALTH APPLICATIONS SOCIETY EMERGING TECHNOLOGIES AND APPLICATIONS 
444	STUDY OF HEALTH OUTCOMES IN A TECHNOLOGY ENABLED VIRTUAL SETTING
444	THIS PAPER PRESENTS AN EMPIRICAL ANALYSIS OF HEALTH INSURANCE CLAIMS DATA TO EXPLORE TELEMEDICINE OUTCOMES
444	SPECIFICALLY , I UTILIZE CAUSAL FORESTS AND A RETROSPECTIVE MATCHED CASE CONTROL STUDY DESIGN TO DEMONSTRATE STATISTICALLY SIGNIFICANT CHANGES IN COSTS , UTILIZATION , AND MEDICATION ADHERENCE OF TELEHEALTH USERS
444	INFORMATION SYSTEMS HEALTH APPLICATIONS SOCIETY REVENUE MANAGEMENT AND PRICING
444	DUE TO DATA REVOLUTION PROCESSES THAT RELIED ON PHYSICAL INTERACTION TRANSITIONED INTO VIRTUAL 
445	USER PATH ANALYSIS ON ADOPTION OF COMMUNICATION SERVICE ON PHARMACEUTICAL E COMMERCE PLATFORM
445	PHARMACEUTICAL E COMMERCE PLATFORMS ARE INTRODUCING ONLINE CONSULTATION SERVICES THAT ENABLE USERS TO CONSULT WITH DOCTORS AND PHARMACISTS , AS WELL AS BIND WITH DEDICATED PHARMACISTS
445	THE RESULTING CHANGE IN USER ENGAGEMENT FOLLOWING THE BINDING PROCESS IS THE FOCUS OF THIS STUDY , WHICH USES TRANSACTION DATA OBTAINED FROM A REPRESENTATIVE PHARMACEUTICAL E COMMERCE PLATFORM IN CHINA
445	SPECIFICALLY , WE INVESTIGATE CHANGES IN USER BEHAVIOR TO GAIN VALUABLE INSIGHTS INTO THE ADOPTION OF ONLINE COMMUNICATION SERVICES AND CONTRIBUTE TO THE RESEARCH OF ONLINE HEALTHCARE SERVICES
445	INFORMATION SYSTEMS HEALTH APPLICATIONS SOCIETY SERVICE SCIENCE 
446	THE BIDIRECTIONAL RELATIONSHIP BETWEEN SOCIAL NETWORKING SITE USE AND DEPRESSION EXPLORING THE IMPACT OF USAGE PATTERNS AND ACTIVE VS
446	PASSIVE ENGAGEMENT
446	THIS STUDY EXAMINES THE COMPLEX RELATIONSHIP BETWEEN THE USE OF SOCIAL NETWORKING SITES , SNS , AND DEPRESSION
446	DRAWING ON THE REFLECTIVE IMPULSIVE MODEL AND THE COGNITIVE THEORY OF DEPRESSION , WE EXPLAIN THE CIRCULAR CAUSE AND EFFECT RELATIONSHIP
446	WE ALSO EXPLORE THE IMPACT OF SNS USE PATTERNS AND USER ENGAGEMENT ON THE RELATIONSHIP
446	BASED ON THREE CROSS SECTIONAL AND ONE LONGITUDINAL NATIONAL SURVEY DATASETS , WE FOUND A POSITIVE BIDIRECTIONAL RELATIONSHIP BETWEEN THE FREQUENCY OF SNS USE AND DEPRESSION
446	THIS RELATIONSHIP FOLLOWS A U SHAPED PATTERN , SUGGESTING THAT INDIVIDUALS WHO ARE HEAVY USERS OR ABSTAIN FROM SNS MAY EXPERIENCE GREATER LEVELS OF DEPRESSION THAN MODERATE USERS
446	MOREOVER , WE FOUND THAT PASSIVE SNS USE , E G , WATCH VIDEOS VIA SNS , MAY EXACERBATE DEPRESSION , WHILE ACTIVE USE , E G , PARTICIPATE IN CURRENT EVENTS VIA SNS , DOES NOT HAVE THE SAME EFFECT
446	INFORMATION SYSTEMS HEALTH APPLICATIONS SOCIETY SOCIAL MEDIA ANALYTICS
446	OUR STUDY USES PUBLICLY AVAILABLE NATIONAL SURVEY DATASET TO ADDRESS AN IMPORTANT PROBLEM
447	FLTRUETRUST , A TRUST MODEL MECHANISM FOR SECURE FEDERATED LEARNING
447	WITH GROWING CONCERNS OVER PRIVACY BREACHES , USERS ARE HESITANT TO STORE PERSONAL INFORMATION IN THE CLOUD , POSING A CHALLENGE FOR DEVELOPERS WHO RELY ON SUCH DATA
447	FEDERATED LEARNING TECHNOLOGY HAS EMERGED AS A SOLUTION , BUT IS VULNERABLE TO MALICIOUS ATTACKS THAT CAN DISRUPT MODEL AGGREGATION AND ACCURACY
447	TO ADDRESS THIS , THE PAPER PROPOSES FLTRUETRUST , A DEFENSE METHOD THAT EMPLOYS A TRUST MODEL MECHANISM TO RESIST MALICIOUS ATTACKERS AND IMPROVE THE EFFICIENCY OF GLOBAL MODEL TRAINING BY REDUCING THE LIKELIHOOD OF SELECTING SUCH ATTACKERS
447	INFORMATION SYSTEMS OPT , NETWORK OPTIMIZATION TELECOMMUNICATIONS AND NETWORK ANALYTICS
448	LEARNING FROM STRESS , DECISION MAKING IN DYNAMIC EVENTS
448	DYNAMIC CONDITIONS CREATE UNIQUE TENSIONS FOR DECISION PROCESSES
448	AS CONDITIONS CHANGE , DECISION MAKERS NEED TO REMAIN OPEN TO INCOMING INFORMATION AND UPDATE THEIR UNDERSTANDING OF THE OPERATIONAL CONTEXT IN REAL TIME
448	YET , MOBILIZING RESPONSE TO CHANGING CONDITIONS REQUIRES SUFFICIENT CONTROL OVER INFORMATION TO MAINTAIN A COHERENT OPERATIONAL FRAMEWORK AND LOGIC OF ACTION
448	THIS TENSION BETWEEN OPENNESS AND CONTROL VARIES WITH INTENSITY , SEVERITY OF THREAT AND CAPACITY OF DECISION MAKERS TO COMPREHEND THE RATE OF CHANGE AND ADAPT THEIR ACTIONS ACCORDINGLY
448	BALANCING OPENNESS WITH CONTROL GOES BEYOND RESILIENCE TO ACHIEVE A STRONGER ANTIFRAGILE STATE
448	DATA DRAWN FROM CALFIRE FIELD REPORTS OF WILDFIRE OPERATIONS DOCUMENT THE RATE OF CHANGE IN KEY OPERATIONAL FUNCTIONS ENTERED AS PARAMETERS IN A SYSTEM DYNAMICS MODEL TO EXPLORE LEARNING FROM STRESS IN PRACTICE
448	INFORMATION SYSTEMS OPT , OPTIMIZATION UNDER UNCERTAINTY ENRE , ENERGY CLIMATE
448	THIS ANALYSIS USES OPERATIONS DATA FROM FIELD REPORTS TO MEASURE CHANGE IN A DYNAMIC SYSTEM 
449	ASSESSING THE COMPLEMENTARY ROLE OF FIRM AND FRIEND RECOMMENDATIONS IN MOBILE ENVIRONMENTS
449	WE INVESTIGATE THE EFFECTIVENESS OF RECOMMENDATIONS FROM FRIENDS AND FIRMS , AND WE ANALYZE HOW THEY INTERACT IN AFFECTING THE CONVERSION OF MOBILE PROMOTIONS
449	FOR FRIEND RECOMMENDATIONS , WE PROPOSE AN IDENTIFICATION APPROACH TO SEPARATE THE UNDERLYING I SELECTION I AND DIRECT I INFLUENCE I EFFECTS , WHILE CONTROLLING FOR I HOMOPHILY I 
449	USING A UNIQUE DATASET FROM A MOBILE PLATFORM THAT SENDS GEO TARGETED COUPONS TO CUSTOMERS AND ALLOWS THEM TO RECOMMEND TO FRIENDS , WE SHOW THAT GEO TARGETING MAKES A CONSUMER MORE LIKELY TO CONSIDER AN OFFER , AND FRIENDS RECOMMENDATIONS INCREASE CONVERSIONS
449	WHEN DISENTANGLING THE MECHANISMS DRIVING THE EFFECTS OF FRIEND RECOMMENDATIONS , WE FOUND THAT THEY ARE MOSTLY ATTRIBUTED TO THE SELECTION EFFECT AND THAT THE EFFECT IS ENHANCED WHEN RECOMMENDERS ARE MORE SELECTIVE AND HAVE STRONGER TIES WITH THE RECIPIENTS
449	INFORMATION SYSTEMS SHARING ECONOMY , INNOVATIVE MARKETPLACES , AND DATA SOCIAL MEDIA ANALYTICS
449	WE COMBINE NOVEL AND MASSIVE DATA SOURCES TO GUIDE PROMOTIONAL DECISION MAKING 
450	THE PERCEIVED QUALITY PARADOX , UNRAVELING THE IMPACT OF BITCOIN PRICE VOLATILITY ON DARK WEB MARKETPLACES
450	THIS RESEARCH STUDIES THE INTRICATE RELATIONSHIP BETWEEN PRICE VOLATILITY , RESULTING FROM THE NATURE OF BITCOIN , AND ITS INFLUENCE ON PERCEIVED QUALITY WITHIN DARK WEB MARKETPLACES
450	DARK WEB PLATFORMS HAVE GAINED SIGNIFICANT PROMINENCE AS HUBS FOR ILLICIT TRADE , THUS COMPREHENDING THE DYNAMICS OF PERCEIVED QUALITY IN SUCH ENVIRONMENTS BECOMES CRUCIAL
450	BY UTILIZING A COMPREHENSIVE DATASET ENCOMPASSING THREE MAJOR DARKNETS FROM TO , THIS STUDY EMPIRICALLY REVEALS A NOTEWORTHY NEGATIVE ASSOCIATION BETWEEN BITCOIN PRICE VOLATILITY AND PRODUCT RATINGS
450	THE IMPLICATIONS EXTEND BEYOND ACADEMIA , OFFERING VALUABLE INSIGHTS INTO MARKET REGULATION , CONSUMER BEHAVIOR IN ILLICIT ONLINE MARKETPLACES , AND THE ONGOING EFFORTS IN CYBERSECURITY
450	INFORMATION SYSTEMS SHARING ECONOMY , INNOVATIVE MARKETPLACES , AND DATA 
451	CATCHING THE VIEWER S EYE , EXAMINING EXPLORATION AND EXPLOITATION STRATEGIES IN THE LIVE STREAMING MARKET
451	MORE AND MORE CREATORS ARE COMPETING ON LIVE STREAMING PLATFORMS LIKE TWITCH TO MAXIMIZE THE ATTENTION THEY RECEIVE FROM VIEWERS
451	TO ATTRACT AND MAINTAIN ATTENTION , IT IS CRUCIAL FOR CONTENT CREATORS TO EFFECTIVELY DEVELOP INNOVATIVE CONTENT THAT CAPTURES CONSUMER INTEREST AND FACILITATES THE DISCOVERY OF THEIR CONTENT
451	WE EXAMINE HOW THESE CONTENT CREATORS EMPLOY AN EXPLORATION EXPLOITATION STRATEGY TO DESIGN THEIR CONTENT AND ATTRACT VIEWERSHIP
451	WE COMBINE TRADITIONAL METHODS WITH RECENT NLP TECHNIQUES TO MEASURE EXPLORATION , EXPLOITATION , AND LEARNING FROM VIEWERS AND STREAMERS TO ASSESS THE POSITIONING OF CONTENT CREATORS
451	UTILIZING OUR PROPOSED METRICS , WE ESTIMATE CONSUMER UTILITY DERIVED FROM THE VARYING STRATEGIES USING THE BLP MODEL
451	OUR FINDINGS HOLD IMPLICATIONS FOR CONTENT CREATORS , PLATFORM BUSINESSES , AND SEVERAL STREAMS OF LITERATURE
451	INFORMATION SYSTEMS SOCIAL MEDIA ANALYTICS EBUSINESS
451	WE DEVELOP NEW METHODS TO DETERMINE COMPETITIVE POSITIONING FROM LARGE SCALE UNSTRUCTURED DATA 
452	COLLECTIVE BEHAVIOR OF VICTIMS AND TRAFFICKERS IN CYBERSEX TRAFFICKING , CREATING DATA DEVELOPMENT PLAN FOR SOCIAL MEDIA SEX TRAFFICKING AWARENESS SYSTEM
452	CYBERSEX TRAFFICKING IS A GROWING ISSUE THAT REQUIRES IMMEDIATE ATTENTION
452	IN THIS PAPER , WE DEVELOP A DATA STRUCTURE PLAN TO INVESTIGATE THE DESIGN OF AN ARTIFACT AS AN AWARENESS SYSTEM TO DISRUPT CYBERSEX TRAFFICKING
452	AS A CASE STUDY , WE FOCUS ON THE SEX TRAFFICKING DILEMMA IN MEXICO
452	WE IDENTIFY VARIOUS ONLINE BEHAVIORS THAT MAY INDICATE AN INDIVIDUAL IS AT RISK OF BECOMING A VICTIM OR SUSPECT OF PRACTICING AS A TRAFFICKER IN SOCIAL MEDIA
452	WE RELIED ON THE COLLECTIVE BEHAVIOR OF SOCIAL INFORMATION SHARING AND SEEKING PRACTICES THAT CAN BE CAPTURED AS INDIVIDUAL FLOW DATA OR GROUP BEHAVIOR
452	THE ONLINE SOCIAL BEHAVIOR OF POTENTIAL VICTIMS AND TRAFFICKERS IS REVIEWED AT THREE STAGES OF COLLECTIVE BEHAVIOR , SEPARATION , COHESION , AND ALIGNMENT
452	FINALLY , SOME REMARKS REGARDING THE LIMITATION AND BARRIERS TO IMPLEMENTING AN AWARENESS SYSTEM , ESPECIALLY IN MEXICO , IS PRESENTED
452	INFORMATION SYSTEMS SOCIAL MEDIA ANALYTICS SOCIALLY RESPONSIBLE AND SUSTAINABLE OPERATIONS
453	EXPLORING HUMAN DECISION MAKING IN COLLABORATION WITH AI IN RISKY TASKS
453	THE STUDY INVESTIGATES THE DECISION MAKING PROCESS OF HUMANS WHEN COLLABORATING WITH ARTIFICIAL INTELLIGENCE , AI , IN TASKS INVOLVING VARYING LEVELS OF DIFFICULTY AND RISK
453	WE EXAMINE HOW HUMANS UTILIZE THEIR OWN UNIQUE KNOWLEDGE AND THE META KNOWLEDGE OF AI TO INFORM THEIR DECISION MAKING
453	TO ADDRESS THE LIMITATION OF THE LACK OF META KNOWLEDGE , AN UNCONSCIOUS TRAIT THAT HAMPERS EFFECTIVE COLLABORATION , WE PROPOSE AN INTERVENTION WHEREIN HUMANS ARE EDUCATED WITH INFORMATION ON AI KNOWS WHAT BEFORE ENGAGING IN COLLABORATION WITH AI
453	BY LEVERAGING AI IN DECISION MAKING , HUMANS CAN MITIGATE THE ADVERSE EFFECTS OF AFFECT , EMOTION , AND STRESS , WHICH OFTEN IMPAIR DECISION MAKING OUTCOMES
453	THE FINDINGS OF THIS STUDY HOLD SIGNIFICANT IMPLICATIONS FOR THE FUTURE OF WORK PARADIGM , PARTICULARLY IN THE DESIGN OF HUMAN AI COLLABORATIVE ENVIRONMENTS
453	INFORMATION SYSTEMS TECHNOLOGY , INNOVATION MANAGEMENT AND ENTREPRENEURSHIP ARTIFICIAL INTELLIGENCE
454	VOTE DELEGATION IN DAO
454	IN THIS PAPER , WE AIM TO INVESTIGATE THE VOTING PROCESS IN DECENTRALIZED AUTONOMOUS ORGANIZATION , DAO , 
454	SINCE LARGE TOKEN HOLDERS CAN CONTROL THE VOTING OUTCOME OF A PROPOSAL AND LEAD TO PLUTOCRACY , MANY DAOS ALLOW VOTE DELEGATION AMONG COMMUNITY MEMBERS
454	WE STUDY HOW THE VOTE DELEGATION SERVES THE INTEREST OF THE COMMUNITY
454	MORE SPECIFICALLY , WE ANALYZE IF VOTERS WITH HIGH DELEGATED VOTING POWER FOLLOW THE MAJORITY VOTE ON A DAO PROPOSAL
454	BY USING A DATASET FROM A PROMINENT VIRTUAL REALITY PLATFORM , WE SHOW THAT VOTERS WITH HIGH DELEGATED VOTING POWER STRATEGICALLY TIME THEIR VOTES AND SUPPORT THE LEADING OUTCOME OF A PROPOSAL INFORMATION SYSTEMS TECHNOLOGY , INNOVATION MANAGEMENT AND ENTREPRENEURSHIP EBUSINESS
455	UNDERSTANDING THE IMPACT OF PRELAUNCH ENDORSEMENTS ON CROWDFUNDING PERFORMANCE , A FIELD EXPERIMENT
455	OBSERVATIONAL LEARNING MAKES PROMOTING EARLY FUNDING ESSENTIAL TO ACHIEVE BETTER CROWDFUNDING PERFORMANCE
455	THIS STUDY TAKES A SIGNALING PERSPECTIVE AND EVALUATES THE EFFICACY OF PRELAUNCH ENDORSEMENTS IN PROMOTING EARLY FUNDING
455	PRELAUNCH ENDORSEMENTS CAN SERVE AS A SUPPLEMENTARY SIGNAL , ESPECIALLY WHEN CUMULATIVE PRIOR FUNDING IS LOW , PROMOTING MORE EARLY FUNDING
455	BY CONDUCTING A FIELD EXPERIMENT IN A CROWDFUNDING PLATFORM , WE FIND THAT MORE PRELAUNCH ENDORSEMENTS LEAD TO GREATER EARLY FUNDING , ESPECIALLY FOR HIGH PRICED PROJECTS AND THOSE LAUNCHED BY NEW FUNDRAISERS
455	OUR QUANTILE ANALYSIS REVEALS THAT PRELAUNCH ENDORSEMENTS HAVE LARGER IMPACTS AT LOWER QUANTILES , ALLEVIATING THE HIGHLY SKEWED FUNDING DISTRIBUTION AND ENHANCING THE OVERALL FUNDRAISING EFFICACY OF THE PLATFORM
455	THIS STUDY OFFERS BOTH THEORETICAL AND PRACTICAL CONTRIBUTIONS
455	INFORMATION SYSTEMS TECHNOLOGY , INNOVATION MANAGEMENT AND ENTREPRENEURSHIP 
456	IS TOKEN AIRDROP EFFECTIVE AGAINST THE VAMPIRE ATTACK FOR DECENTRALIZED EXCHANGES
456	THE PROSPERITY OF CRYPTOECONOMICS IN RECENT YEARS INSPIRES THE NEED FOR RELIABLE CRYPTO EXCHANGE PLATFORMS
456	DUE TO SEVERE ISSUES OF CENTRALIZED EXCHANGES , DECENTRALIZED EXCHANGES , DEX , AS TWO SIDED ON CHAIN PLATFORMS WITHOUT INTERMEDIARIES HAVE BECOME A VIABLE ALTERNATIVE
456	BASED ON A SERIES OF EVENTS ON THE LARGEST DEX IN THE WHOLE BLOCKCHAIN ECOSYSTEM , OUR STUDY AIMS TO EMPIRICALLY INVESTIGATE THE IMPACT OF ITS TOKEN AIRDROP CAMPAIGN ON INVESTOR RETENTION
456	IN PARTICULAR , WE EXAMINE WHETHER IT IS EFFECTIVE AGAINST ITS IMITATOR S VAMPIRE ATTACK , A STRATEGY OF OFFERING TOKENIZED INCENTIVES TO USERS OUT OF AN EXISTING PLATFORM INTO A COMPETING ONE
456	OUR STUDY PROVIDES VALUABLE INSIGHTS INTO MOTIVATING USER ENGAGEMENT FOR DEFI APPLICATIONS AND THE BLOCKCHAIN COMMUNITY
456	INFORMATION SYSTEMS TECHNOLOGY , INNOVATION MANAGEMENT AND ENTREPRENEURSHIP 
457	LOW REVENUE IN DISPLAY AD AUCTIONS , ALGORITHMIC COLLUSION VS
457	NON QUASILINEAR PREFERENCES
457	MOST DISPLAY AD EXCHANGES MOVED FROM SECOND TO FIRST PRICE AUCTIONS IN RECENT YEARS
457	THE EFFECT ON REVENUE IS DIFFICULT TO EVALUATE EMPIRICALLY
457	RECENT LITERATURE ON ALGORITHMIC COLLUSION FINDS THAT , IN CONTRAST TO THE SECOND PRICE AUCTION , FIRST PRICE AUCTIONS CAN INDUCE Q LEARNING AGENTS TO BID BELOW THE NASH EQUILIBRIUM IN A REPEATED COMPLETE INFORMATION VERSION OF THE AUCTION
457	WE ANALYZE A VARIETY OF ONLINE LEARNING ALGORITHMS AND SHOW THAT THEY ALL CONVERGE TO EQUILIBRIUM IN BOTH , THE COMPLETE AND INCOMPLETE INFORMATION MODEL
457	WE ALSO COMPUTE EQUILIBRIUM FOR ROI OPTIMIZING AGENTS AND SHOW THAT THEIR REVENUE IN THE FIRST PRICE AUCTION IS LOWER THAN IN THE SECOND PRICE AUCTION IN EQUILIBRIUM
457	INFORMATION SYSTEMS 
458	TO PARTNER OR NOT TO PARTNER
458	THE PARTNERSHIP BETWEEN PLATFORMS AND DATA BROKERS IN TWO SIDED MARKETS
458	AS DATA HAS BECOME AN IMPORTANT COMPETITIVE ASSET , PLATFORMS USUALLY PARTNER WITH DATA BROKERS TO ACQUIRE EXTERNAL DATA TO ENHANCE THEIR TARGETING CAPABILITIES , BUT THIS PRACTICE HAS STOKED CONSUMER PRIVACY CONCERNS
458	THIS STUDY DEVELOPS A GAME THEORETIC MODEL TO EXAMINE THE ECONOMIC MECHANISM UNDERLYING THE PARTNERSHIP BETWEEN COMPETING PLATFORMS AND A DATA BROKER IN A TWO SIDED MARKET
458	INTERESTINGLY , OUR ANALYSIS SHOWS THAT THE INCREASE IN CONSUMER PRIVACY CONCERNS CAUSED BY THE DATA BROKER MAY INCENTIVIZE PLATFORMS TO PARTNER WITH THE DATA BROKER RATHER THAN DISCOURAGING THEM
458	WE FIND THAT THE PLATFORM DATA BROKER PARTNERSHIP HURTS CONSUMER SURPLUS WHEN PLATFORMS ADOPT A PURE AD SPONSORED MODEL WITHOUT CHARGING CONSUMERS , BUT IT MAY BENEFIT CONSUMER SURPLUS WHEN PLATFORMS ADOPT A MIXED MODEL WITH AD SPONSORED AND SUBSCRIPTION BASED REVENUE
458	INFORMATION SYSTEMS 
459	WHY USERS CONTINUE TO USE CONVERSATIONAL AI AFTER ACCEPTING IT INITIALLY
459	CONVERSATIONAL AI , WHICH USES NATURAL LANGUAGE PROCESSING TECHNOLOGY TO CONVERSE WITH USERS AND PROVIDE APPROPRIATE RESPONSES , SEEMS TO HOLD GREAT PROMISE FOR PROVIDING CONSUMERS WITH QUICK , CONVENIENT , AND FRIENDLY SERVICES
459	CONTINUANCE INTENTION IS CRITICAL FOR ULTIMATE SUCCESS OF CONVERSATION AI BECAUSE SOME USERS DISCONTINUE TO USE CONVERSATIONAL AI AFTER ACCEPTING IT INITIALLY
459	THIS STUDY EXAMINES THE CONTINUANCE INTENTION OF CONVERSATIONAL AI , BASED ON THE EXPECTATION CONFIRMATION MODEL
459	THE MODEL IS VALIDATED USING AN ONLINE SURVEY OF INDIVIDUALS WHO HAVE EXPERIENCE CONVERSATIONAL AI SUCH AS CHAT GPT
459	THE RESULT OF ANALYSIS WILL BE PRESENTED IN THE CONFERENCE IN DETAILS
459	WE WILL ALSO DISCUSS THE SUGGESTION FOR FURTHER WORK
459	INFORMATION SYSTEMS 
460	WHAT IS MISSING , A META ANALYSIS OF USER PARTICIPATION BEHAVIOR IN ONLINE COMMUNITIES 
460	ACTIVE USER PARTICIPATION IS ESSENTIAL FOR SUSTAINABLE AND SUCCESSFUL ONLINE COMMUNITIES
460	HOWEVER , RESEARCH ON THE KEY DRIVERS OF USER PARTICIPATION AND THEIR PERFORMANCE UNDER DIFFERENT CONDITIONS REMAINS INCONSISTENT
460	TO ADDRESS THIS , WE CONDUCTED A META ANALYSIS OF OVER EMPIRICAL PAPERS , CLASSIFYING THEIR ANTECEDENTS INTO CATEGORIES BASED ON ESTABLISHED THEORETICAL FRAMEWORKS OF TECHNOLOGY ACCEPTANCE MODEL AND SOCIAL CAPITAL THEORY
460	WE ANALYZE EACH CATEGORY S RELATIONSHIP WITH USER PARTICIPATION AND MULTIPLE MODERATORS THAT AFFECT THESE RELATIONSHIPS TO ADDRESS VARIATIONS IN ONLINE COMMUNITY RESEARCH THOROUGHLY
460	PRACTITIONERS CAN USE OUR RESULTS TO ENHANCE USER ENGAGEMENT AND SUSTAINABILITY THROUGH INFORMED DESIGN AND MANAGEMENT OF ONLINE COMMUNITIES
460	INFORMATION SYSTEMS 
461	THE CHARACTERISTICS OF ONLINE VOTING SYSTEM , OVS , OF THE DIGITAL MEDIA APPLICATION AND ITS IMPACT ON TRUST 
461	THIS STUDY AIMS TO VERIFY THE IMPACTS OF OVS TRAITS ON TRUST AND INTENTION TO USE INTERNET VOTING BY USERS
461	THE STUDY WILL EXAMINE QUESTIONNAIRES OBTAINED FROM THE ONLINE VOTERS USING MNET PLUS PLATFORM
461	RESULTS ARE EXPECTED TO FIND THAT THE TRAITS OF ONLINE VOTING SYSTEM HAD A POSITIVE EFFECT ON TRUST THAT HAVE A POSITIVE EFFECT ON INTENTION TO USE INTERNET VOTING
461	MOREOVER , POSITIVE INTENTION OF WORD OF MOUTH IS EXPECTED TO MODERATE THE RELATIONSHIP BETWEEN TRUST AND INTENTION TO USE INTERNET VOTING
461	THIS STUDY IS EXPECTED TO PROVIDE VALUABLE INFORMATION FOR OVS SERVICE PROVIDERS IN UNDERSTANDING USERS BEHAVIORS
461	INFORMATION SYSTEMS THE STUDY NEEDS THE INFORMATION OF CHARACTERISTICS OF OVS AND USER PARTICIPATING IN OVS
462	EFFECT OF GAMIFICATION ON KNOWLEDGE TRANSFER IN STACK OVERFLOW , SO , 
462	STACK OVERFLOW , SO , IS A POPULAR QUESTION AND ANSWER COMMUNITY FOR SOFTWARE DEVELOPMENT
462	GAMIFICATION IN SO TAKES THE FORM OF BADGES AND BOUNTIES EARNED BY USERS
462	BADGES ARE DESIGNED TO ENCOURAGE PARTICIPATION
462	USERS CAN GET DIFFERENT LEVELS OF BADGES , GOLD , SILVER , BRONZE , 
462	BOUNTIES ARE REPUTATION POINTS OFFERED BY USERS WHO WANT ANSWERS TO QUESTIONS
462	WHILE THESE GAMIFICATION MECHANISMS ARE POPULAR , THERE IS LIMITED RESEARCH ON WHETHER BADGES AND BOUNTIES ARE EFFECTIVE AND EXISTING RESEARCH IS INCONCLUSIVE
462	WE DEVELOP AND EMPIRICALLY TEST MODELS OF KNOWLEDGE TRANSFER THAT INCLUDE THE EFFECTS OF GAMIFICATION AND EXPLORE THE EFFECTIVENESS OF THESE TWO FORMS OF GAMIFICATION MECHANISMS ON KNOWLEDGE TRANSFER IN SO
462	INFORMATION SYSTEMS ILLUSTRATES HOW DATA IN Q A SITES CAN BE USED 
463	IMPLEMENTING AN ANALYTICS AND OPERATIONS RESEARCH PROJECT IN A SECOND YEAR ENGINEERING SCIENCE DESIGN COURSE
463	THE SECOND YEAR ENGINEERING SCIENCE DESIGN COURSE AT THE UNIVERSITY OF AUCKLAND INCLUDES A SIX WEEK ANALYTICS AND OPERATIONS RESEARCH PROJECT , WHERE STUDENTS FORMULATE AND SOLVE A MODERATELY LARGE VEHICLE ROUTING PROBLEM
463	IN GROUPS , THEY ARE EXPECTED TO APPLY THEIR STATISTICS AND VISUALISATION SKILLS TO ESTIMATE PROBLEM DATA , OPTIMISATION FOR PROBLEM FORMULATION , AND SIMULATION TO ESTIMATE THE SOLUTION QUALITY
463	PROFESSIONAL SKILLS DEMANDED BY INDUSTRY , SUCH AS REPORT WRITING , TEAMWORK , ETHICS AND SYSTEMS THINKING , ARE FURTHER DEVELOPED
463	THE LESSONS LEARNT AFTER FIVE YEARS OF COURSE DEVELOPMENT , INCLUDING TWO YEARS OF ONLINE DELIVERY , WILL BE DISCUSSED , AND POTENTIAL IDEAS FOR FURTHER COURSE AND CURRICULUM DEVELOPMENT EXPLORED
463	INFORMS COMMITTEE ON TEACHING AND LEARNING AND EDUCATION OUTREACH DATA DRIVEN INNOVATIONS IN OR EDUCATION 
464	IMPACT OF TRAINING ON FACULTY S MOTIVATION TO ADOPT THE SIMULATION PEDAGOGY
464	SIMULATIONS ARE CONSIDERED TO BE VERY EFFECTIVE IN TEACHING PEDAGOGY
464	THE ADOPTION OF SIMULATION PEDAGOGY IS LIMITED IN ONLINE CLASSES DUE TO A LACK OF FAMILIARITY WITH ONLINE TEACHING PLATFORMS
464	THIS PAPER MAKES AN ASSESSMENT OF THE ONLINE TRAINING SESSIONS ON THE FACULTY S MOTIVATION LEVEL TO ADOPT THE SIMULATION PEDAGOGY
464	THE POST TRAINING SESSION FEEDBACK FROM THE FACULTY , WHICH WAS ANALYZED USING MIXED METHODS , SUCH AS BAR CHARTS , SENTIMENT ANALYSIS , AND CHI SQUARE , INDICATED THAT MOST WERE MOTIVATED TO ADOPT SIMULATION PEDAGOGY IN THEIR CLASSES
464	THE ANALYSIS ALSO REVEALED THAT DEMOGRAPHIC CHARACTERISTICS , SUCH AS GENDER , DESIGNATION , YEARS OF EXPERIENCE , AND AREA OF EXPERTISE , DO NOT AFFECT THE SENTIMENTS
464	INFORMS COMMITTEE ON TEACHING AND LEARNING AND EDUCATION OUTREACH JUNIOR FACULTY INTEREST GROUP SIMULATION SOCIETY
465	TEACHING OR USING R AFTER YEARS OF TEACHING INTRODUCTORY MANAGEMENT SCIENCE USING SPREADSHEETS , I RECENTLY PIVOTED TO USING R AND THE R ECO SYSTEM OF TOOLS AS A WAY TO INTRODUCE ANALYTICS TO FUTURE TECHNICAL PROFESSIONALS
465	THIS HAS A NUMBER OF BENEFITS INCLUDING MAKING THEM AWARE OF PLATFORMS , DOCUMENTATION PRACTICES , REPRODUCIBLE RESEARCH , AND VERSION CONTROL
465	THIS ENABLES STUDENTS WITH DIFFERENT TECHNICAL BACKGROUNDS TO DO PARTICIPATE MORE DEEPLY AS WELL INCLUDING MAKING GITHUB CONTRIBUTIONS
465	IN THIS PRESENTATION , WE TALK ABOUT THE JOURNEY FROM SPREADSHEETS TO R AND LINKS TO THE DEVELOPED OPEN RESOURCES
465	INFORMS COMMITTEE ON TEACHING AND LEARNING AND EDUCATION OUTREACH OPTIMIZATION , OPT , TECHNOLOGY , INNOVATION MANAGEMENT AND ENTREPRENEURSHIP
466	ANALYTICS COURSE PROJECT
466	A COURSE ASSIGNMENT PROJECT THAT CAN BE USED FOR LEARNING AND ASSESSMENT PURPOSES IN A STATISTICS OR ANALYTICS CLASS WILL BE PRESENTED
466	INFORMS COMMITTEE ON TEACHING AND LEARNING AND EDUCATION OUTREACH THE PRESENTATION DISCUSSES A COURSE ASSIGNMENT PROJECT THAT HELPS STUDENTS LEARN ANALYTICS CONCEPTS 
467	MULTI OBJECTIVE WILDFIRE MITIGATION PLANNING ASSESSMENT AND EVALUATION
467	CONSIDERABLE ATTENTION IN LAND USE PLANNING HAS FOCUSED ON SOFTWARE AND APPROACHES THAT RELY ON HEURISTIC METHODS TO GENERATE SOLUTIONS FOR MULTIPLE OBJECTIVE PROBLEMS
467	WHILE FAST AND ACCESSIBLE , THERE REMAIN UNCERTAINTIES ABOUT THE QUALITY OF SOLUTIONS OBTAINED BY EMPLOYED HEURISTIC METHODS AND WHETHER THEY ARE INDEED MEETING THE NEEDS OF LAND USE AGENCIES
467	THIS PAPER EXPLORES FOREST TREATMENT PLANNING FOR WILDFIRE RISK MITIGATION SEEKING TO BALANCE MULTIPLE OBJECTIVES AND WHEN THE SPATIAL PATTERN OF TREATMENT IS RESTRICTED
467	LOCATION ANALYSIS ENERGY , NATURAL RESOURCES AND THE ENVIRONMENT , ENRE , 
468	MULTISTAGE STOCHASTIC FACILITY LOCATION UNDER FACILITY DISRUPTION UNCERTAINTY
468	FACILITY DISRUPTIVE INCIDENTS LIKE POWER OUTAGES , INDUSTRIAL ACCIDENTS , PROBLEMS WITH THE TRANSPORTATION INFRASTRUCTURE , AND NATURAL CATASTROPHES MAY CAUSE FACILITY FAILURES FOR A LONGER PERIOD OF TIME
468	IN THIS PAPER , WE DESCRIBE A MULTISTAGE VARIANT OF THE CLASSIC STOCHASTIC FACILITY LOCATION PROBLEM UNDER FACILITY DISRUPTION UNCERTAINTY
468	NUMERICAL RESULTS FROM THE STATE OF THE ART ALGORITHM TO SOLVE SUCH CLASS OF PROBLEMS STOCHASTIC DUAL DYNAMIC INTEGER PROGRAMMING , SDDIP , SHOW INFERIORITY OVER A RATHER NOVEL SOLUTION ALGORITHM SHADOW PRICE APPROXIMATION , SPA , BASED ON TRAINING PARAMETERS OF THE LINEAR VALUE FUNCTION APPROXIMATION WHICH MINIMIZES AN UPPER BOUND OF THE OPTIMAL OBJECTIVE VALUE
468	LOCATION ANALYSIS OPT , OPTIMIZATION UNDER UNCERTAINTY 
468	WE USE REAL WORLD DATA FOR OUR NUMERICAL INVESTIGATIONS 
469	A BRANCH AND PRICE ALGORITHM FOR THE ANGULAR SET COVERING PROBLEM
469	THE SET COVERING PROBLEM , SCP , IS A WELL KNOWN LOCATION PROBLEM WITH MANY APPLICATIONS
469	ITS MAIN OBJECTIVE IS TO DETERMINE THE MINIMUM COST SET OF FACILITIES FROM A FINITE AND DISCRETE SET OF OPTIONS , COVERING ALL THE DEMAND POINTS AROUND A GIVEN GEOGRAPHIC AREA
469	WE PROPOSE A MATHEMATICAL FORMULATION AND A MODEL FOR THE ANGULAR COVERING PROBLEM , WHICH CONSIDERS ESTABLISHING THE COVERAGE AT SPECIFIC ANGLES GUARANTEEING COVERING ANGULAR ZONES WHERE THE DEMAND POINTS ARE LOCATED , AND AVOIDING COVERING UNNECESSARY SPACE WHERE THERE ARE NO DEMAND POINTS
469	THIS COVERING STRUCTURE HAS SEVERAL APPLICATIONS , SUCH AS THE LOCATION OF SURVEILLANCE SECURITY CAMERAS
469	WE PROPOSE A BRANCH AND PRICE ALGORITHM TO SOLVE LARGE INSTANCES FOR THE ANGULAR COVERING PROBLEM
469	WE REALIZE COMPUTATIONAL EXPERIMENTS TO SHOW THE COMPUTATIONAL EFFECTIVENESS OF THE SOLUTION METHOD
469	LOCATION ANALYSIS OPTIMIZATION , OPT , OPT , INTEGER AND DISCRETE OPTIMIZATION
470	UTILIZING CROWDSOURCED DELIVERY DATA FOR CHAIN STORE LOCATION SELECTION
470	THE OUTBREAK OF COVID EPIDEMIC HAS INCREASED THE USAGE OF CROWDSOURCED FOOD DELIVERIES
470	THIS RESEARCH UTILIZES THE DELIVERY SYSTEM GENERATED DATA AT A CHAIN STORE S END TO MEASURE EACH STORE S SERVICE BOUNDARY
470	TOGETHER WITH THE RETAIL GRAVITY MODEL , THE HUFF MODEL , THE CENTRAL PLACE THEORY , AND THE INFORMATION OF LOCAL COMPETITORS AND POTENTIAL NUMBER OF CUSTOMERS , WE BUILD A NOVEL MODEL FOR THE CHAIN STORE TO EVALUATE POTENTIAL LOCATIONS FOR NEW STORES
470	LOCATION ANALYSIS SHARING ECONOMY , INNOVATIVE MARKETPLACES , AND DATA WE INCORPORATE THE CROWDSOURCED FOOD DELIVERY DATA OF A CHAIN STORE TO OUR LOCATION SELECTION MODEL 
471	OPTIMIZING MODERN RETAILERS LOCATION IN EMERGING MARKETS MEGACITIES
471	IN THIS PAPER , WE STUDY THE LOCATION PROBLEM FOR MODERN RETAIL STORES IN A DENSELY POPULATED MEGACITY IN AN EMERGING MARKET
471	A TRADE OFF IS MADE BETWEEN A HIGHER POPULATION DENSITY , AND HENCE DEMAND , WHEN GETTING CLOSER TO THE CITY CENTER , AND HIGHER OPENING AND LOGISTICS COST
471	WE EXTEND HOTELLING S LINE MODEL TO AN ANALYTICAL FRAMEWORK THAT INCORPORATES THE SPECIFIC CHARACTERISTICS OF TRADITIONAL AND MODERN RETAILERS
471	WE ANALYZE THE SINGLE STORE MODEL ANALYTICALLY AND DETERMINE THE OPTIMAL LOCATION FOR A HYPERMARKET
471	OUR NUMERICAL STUDY SHOWS HOW CUSTOMERS TRAVEL COST , APPRECIATION , AND PRICE SETTING INFLUENCE THE OPTIMAL LOCATIONS AND PROFITS
471	GIVEN THE COMPLEXITY OF THE MODEL , ANALYSIS BECOMES INTRACTABLE WHEN MULTIPLE STORES ARE OPENED
471	THEREFORE , WE DEVISE AN APPROXIMATION AND SHOW THAT IT CAN YIELD ACCURATE RESULTS
471	LOCATION ANALYSIS TSL , URBAN TRANSPORTATION PLANNING AND MODELING OPTIMIZATION , OPT , 
472	OPTIMAL REGULARIZATION OF THE FIRST PRINCIPAL COMPONENT
472	IN THIS STUDY , WE INTRODUCE A NOVEL REGULARIZATION TECHNIQUE , DIRECTION REGULARIZED PRINCIPAL COMPONENT ANALYSIS , DRPCA , , WHICH AMALGAMATES TRADITIONAL ESTIMATORS WITH A STRUCTURED TARGET , A METHOD WIDELY ADOPTED IN HIGH DIMENSIONAL DATA ANALYSIS
472	THIS METHOD AIMS TO DETERMINE THE MAXIMUM VARIANCE DIRECTION WITHIN THE DATA , WHILE ADHERING TO A PRE SPECIFIED TARGET DIRECTION , THEREBY OFFERING A SOLUTION TO THE PCA PROBLEM
472	WE DEPLOY THE HIGH DIMENSIONAL , LOW SAMPLE SIZE FRAMEWORK FOR AN ASYMPTOTIC ANALYSIS OF THE SOLUTION , YIELDING AN OPTIMAL TUNING PARAMETER THAT MINIMIZES AN ASYMPTOTIC LOSS FUNCTION
472	AS A RESULT , THE DATA RAPIDLY ASSIMILATES THE ESTIMATOR CORRESPONDING TO THIS OPTIMAL TUNING PARAMETER
472	MACHINE LEARNING FOR OPTIMIZATION APPLIED PROBABILITY OPT , OPTIMIZATION UNDER UNCERTAINTY
473	RL VACCINATOR , LEVERAGING REINFORCEMENT LEARNING FOR OPTIMAL IMMUNIZATION IN CONTACT NETWORKS
473	THE EFFECTIVE CONTROL OF INFECTIOUS DISEASES HEAVILY RELIES ON DESIGNING EFFICIENT VACCINATION POLICIES
473	HOWEVER , THE COMPLEX NATURE OF HUMAN CONTACT NETWORKS POSES SIGNIFICANT CHALLENGES IN DETERMINING THE OPTIMUM ALLOCATION OF VACCINE RESOURCES
473	THIS RESEARCH EXPLORES THE UTILIZATION OF REINFORCEMENT LEARNING , RL , TECHNIQUES TO ADDRESS THIS PROBLEM
473	SPECIFICALLY , WE INVESTIGATE HOW RL ALGORITHMS CAN BE EMPLOYED TO OPTIMIZE VACCINATION POLICIES BY CONSIDERING THE DYNAMICS OF DISEASE SPREAD OVER HUMAN CONTACT NETWORKS WHILE TARGETING THE INDIVIDUALS WHO ARE THE BEST IMMUNIZATION CANDIDATES
473	FOR THIS PURPOSE , A REINFORCEMENT LEARNING APPROACH BASED ON GRAPH NEURAL NETWORKS IS COUPLED WITH A PANDEMIC SIMULATOR TO ESTIMATE THE FUTURE STATUS OF THE DISEASE SPREAD
473	THROUGH SIMULATIONS AND ANALYSES , WE DEMONSTRATE THE EFFICACY OF THE PROPOSED METHOD
473	MACHINE LEARNING FOR OPTIMIZATION ARTIFICIAL INTELLIGENCE HEALTH APPLICATIONS SOCIETY
473	THIS PAPER UTILIZES MACHINE LEARNING ALGORITHMS FOR LARGE SCALE OPERATIONS RESEARCH PROBLEMS 
474	DATA DRIVEN PORTFOLIO MANAGEMENT FOR MOTION PICTURES INDUSTRY , A NEW DATA DRIVEN OPTIMIZATION METHODOLOGY USING CHAT GPT AS AN EXPERT
474	PORTFOLIO MANAGEMENT IS ONE OF THE UNRESPONDED PROBLEMS OF THE MOTION PICTURES INDUSTRY , MPI , 
474	TO DESIGN AN OPTIMAL PORTFOLIO FOR AN MPI INVESTOR , IT IS ESSENTIAL TO PREDICT THE BOX OFFICE OF EACH PROJECT
474	MOREOVER , FOR AN ACCURATE BOX OFFICE PREDICTION , IT IS CRITICAL TO CONSIDER THE EFFECT OF THE CELEBRITIES INVOLVED IN EACH MPI PROJECT WHICH WAS NOT POSSIBLE WITH ANY PRECEDENT EXPERT BASE METHOD
474	IN THIS PAPER , FIRSTLY , THE FAME SCORE OF THE CELEBRITIES IS DETERMINED USING CHAT GPT
474	THEN TO TACKLE THE UNBALANCED CHARACTER OF MPI S DATA , PROJECTS ARE CLASSIFIED
474	FURTHERMORE , THE BOX OFFICE PREDICTION IS TAKEN PLACE FOR THE PROJECTS IN EACH CLASS
474	FINALLY , USING A HYBRID MULTI ATTRIBUTE DECISION MAKING TECHNIQUE , THE PREFERABILITY OF EACH PROJECT FOR THE INVESTOR IS CALCULATED , AND BENEFITTING FROM A BI OBJECTIVE OPTIMIZATION MODEL , THE OPTIMAL PORTFOLIO IS DESIGNED
474	MACHINE LEARNING FOR OPTIMIZATION EMERGING TECHNOLOGIES AND APPLICATIONS MULTIPLE CRITERIA DECISION MAKING
474	IT IS A NEW DATA DRIVEN PORTFOLIO OPTIMIZATION METHOD BENEFITING FROM CHAT GPT AS AN EXPERT 
475	APPLICATION OF MACHINE LEARNING MODELS FOR WILDFIRE PREDICTION IN SOUTH KOREA
475	THIS STUDY AIMS TO DEVELOP A MODEL THAT PREDICTS DOMESTIC FOREST FIRE OCCURRENCES DURING FIRE OUTBREAKS USING MACHINE LEARNING TECHNIQUES
475	FOR THE MODELING METHODS , LOGISTIC REGRESSION ANALYSIS AND ENSEMBLE TECHNIQUES , SUCH AS GRADIENT BOOST AND RANDOM FOREST , WERE USED WHILE THE OVERSAMPLING TECHNIQUE WAS UTILIZED TO ADDRESS THE IMBALANCE PROBLEM OF THE FOREST FIRE DATA
475	THE MODEL DEVELOPED IN THIS STUDY PREDICTED OUT OF FOREST FIRE OCCURRENCES DURING THE NATIONWIDE FOREST FIRE PERIOD IN WITH A PREDICTION ACCURACY OF APPROXIMATELY WE FOUND THAT FOREST FIRE OCCURRENCES ARE NOT JUST INFLUENCED BY CLIMATE FACTORS , SUCH AS TEMPERATURE , HUMIDITY , AND PRECIPITATION , BUT ALSO BY FARMLAND DENSITY AND STEM VOLUME PER HECTARE AS HUMAN ASSOCIATED FACTORS IN THE MINIMUM LEVEL OF ADMINISTRATIVE REGIONS OF THE REPULIC OF KOREA
475	MACHINE LEARNING FOR OPTIMIZATION ENRE , ENVIRONMENT AND SUSTAINABILITY ENRE , NATURAL RESOURCES
476	TRANSPORTATION DISTANCE BETWEEN KERNELS AND APPROXIMATE DYNAMIC RISK EVALUATION IN MARKOV SYSTEMS
476	WE INTRODUCE A DISTANCE BETWEEN KERNELS BASED ON THE WASSERSTEIN DISTANCES , STUDY ITS PROPERTIES , AND PROPOSE A METHOD FOR APPROXIMATING SOLUTIONS TO FORWARD BACKWARD MARKOV SYSTEMS
476	IN ADDITION , WE ESTABLISH THE METRIC PROPERTIES OF THE KERNEL DISTANCE AND RELATE IT TO VARIOUS MODES OF CONVERGENCE IN THE SPACE OF KERNELS
476	WE THEN PROPOSE A RECURSIVE APPROXIMATION SCHEME FOR THE FORWARD SYSTEM OF A MARKOV SYSTEM USING THE KERNEL DISTANCE AND ESTIMATE THE ERROR OF THE RISK EVALUATION BY THE ERRORS OF INDIVIDUAL KERNEL APPROXIMATIONS
476	WE ILLUSTRATE THE RESULTS ON STOPPING PROBLEMS AND WELL KNOWN RISK MEASURES AND WE DEVELOP A PARTICLE BASED NUMERICAL PROCEDURE WITH FINITE SUPPORT SETS
476	FINALLY , WE APPLY THE PROPOSED APPROACH TO PRICING AN AMERICAN BASKET OPTION IN A FINANCIAL PROBLEM
476	MACHINE LEARNING FOR OPTIMIZATION FINANCE OPT , INTEGER AND DISCRETE OPTIMIZATION
477	DEEP LEARNING AND MACHINE LEARNING FOR ANALYZING RISKY DRIVING BEHAVIOR
477	AGGRESSIVE DRIVING BEHAVIOR IS THE NUMBER ONE FACTOR IN ROAD CRASHES , WITH , FATAL CRASHES , OF THE TOTAL , INVOLVING ONE OR MORE AGGRESSIVE DRIVING BEHAVIORS BY DRIVERS DURING A RECENT FOUR YEAR PERIOD , ACCORDING TO THE AAA FOUNDATION FOR TRAFFIC SAFETY
477	THIS PAPER AIMS TO USE DEEP LEARNING AND MACHINE LEARNING METHODS TO ANALYZE AND UNDERSTAND RISKY DRIVING BEHAVIORS
477	OUR DATA COMES FROM COLLECTING ACCELEROMETER AND GYROSCOPE BASED SENSOR INFORMATION INSTALLED ON CELL PHONES
477	WE TRAIN THESE MODELS TO EFFECTIVELY IDENTIFY AND CLASSIFY RISKY BEHAVIORS SUCH AS AGGRESSIVE DRIVING , DISTRACTED DRIVING , AND SPEEDING
477	THE RESULTS OF THIS STUDY PROVIDE VALUABLE INSIGHTS INTO THE FACTORS THAT CONTRIBUTE TO DANGEROUS DRIVING AND ALLOW US TO DEVELOP PROACTIVE MEASURES TO ENHANCE ROAD SAFETY AND PROMOTE RESPONSIBLE DRIVING HABITS
477	MACHINE LEARNING FOR OPTIMIZATION MACHINE LEARNING IN OPERATIONS DECISION ANALYSIS SOCIETY DEVELOP PROACTIVE MEASURES TO ENHANCE ROAD SAFETY 
478	A MULTI AGENT REINFORCEMENT LEARNING BASED BRANCH AND PRICE ALGORITHM FOR RESOURCE ALLOCATION WITH TRIMMING ALLOWANCE AND BATCHING REQUIREMENTS
478	IN THIS STUDY , WE ADDRESS A RESOURCE ALLOCATION PROBLEM WITH TRIMMING ALLOWANCE AND BATCHING REQUIREMENTS
478	WE FORMULATE THE PROBLEM AS A SET COVERING MODEL , AND THEN DEVELOP A BRANCH AND PRICE ALGORITHM TO OBTAIN THE OPTIMAL SOLUTIONS
478	IN THE ALGORITHM , A LABEL CORRECTING METHOD IS DESIGNED TO OPTIMALLY SOLVE PRICING PROBLEMS , WHOSE EFFICIENCY IS GUARANTEED BY DOMINANCE RULES
478	IN ADDITION , A HYBRID RULES BRANCHING STRATEGY IS PROPOSED TO ENHANCE BRANCHING EFFICIENCY
478	FINALLY , WE PROPOSE AN ADAPTIVE CUTTING PLANE PROCEDURE BASED ON MULTI AGENT REINFORCEMENT LEARNING TO FIND CUTTING PLANES THAT CAN TIGHTEN THE MODEL
478	THE NUMERICAL EXPERIMENTS SHOW THAT OUR ALGORITHM OUTPERFORMS THE STATE OF THE ART BRANCH AND PRICE ALGORITHMS , ESPECIALLY REGARDING THE EFFECTIVENESS OF THE ADAPTIVE CUTTING PLANE PROCEDURE
478	MACHINE LEARNING FOR OPTIMIZATION MANUFACTURING AND SERVICE OPERATIONS MANAGEMENT , MSOM , 
479	SOLVING THE PAINT SHOP PROBLEM USING REINFORCEMENT LEARNING
479	IN THE PAINT SHOP PROBLEM , A SEQUENCE OF CARS HAS TO BE PAINTED WITH THE OBJECTIVE OF MINIMIZING THE NUMBER OF COLOR CHANGES
479	FOR THIS PURPOSE , MANUFACTURERS EMPLOY A MULTI LANE BUFFER SYSTEM WITH STORE AND RETRIEVAL OPERATIONS
479	PRIOR STUDIES SOLELY FOCUSED ON RETRIEVAL OPERATIONS AND SIMPLE SOLUTION HEURISTICS
479	IN THIS STUDY , WE PROPOSE AN INTEGRATED REINFORCEMENT LEARNING APPROACH THAT SIMULTANEOUSLY LEARNS TO PERFORM SMART STORAGE AND RETRIEVAL OPERATIONS
479	AFTER PROVING THAT GREEDY RETRIEVAL IS OPTIMAL , WE INCORPORATE THIS FACT INTO THE MODEL USING ACTION MASKING
479	OUR EVALUATION , BASED ON PROBLEM INSTANCES WITH BUFFER LANES AND COLORS , SHOWS THAT OUR APPROACH REDUCES COLOR CHANGES COMPARED TO EXISTING METHODS BY UP TO MACHINE LEARNING FOR OPTIMIZATION OPT , INTEGER AND DISCRETE OPTIMIZATION ARTIFICIAL INTELLIGENCE
480	TIPDAT , ML BASED OPTIMIZATION EXPLAINER
480	AMAZON S RETAIL INVENTORY IS OUTCOME OF SYSTEMS OPTIMIZING STOCHASTIC VARIABLES TO MET DEMAND AND MAXIMIZE PROFIT
480	HISTORICALLY , WE VE RELIED ON LONG MANUAL SUBJECTIVE DEEP DIVES TO INSPECT DEFECTS , AND IMPROVE OUTCOMES , WHICH HAVE PROVED TO BE UNSCALABLE AND DISCONNECTED FROM ACTUAL SUPPLY CHAIN BEHAVIOR
480	WE DEVELOPED A STAGED ALGORITHM THAT CAN CONNECT THESE INPUTS TO INVENTORY
480	STAGE OF THE ALGORITHM TRAINS A LARGE SCALE ML MODEL OVER A BILLION OBSERVATIONS TO APPROXIMATE A COMPLEX STOCHASTIC PROGRAMMING ALGORITHM USED TO MAKE BUYING DECISIONS
480	WE DEVELOPED AN ATTRIBUTION ALGORITHM THAT LEVERAGES THE CONCEPT FROM SHAPLEY VALUES WHERE ATTRIBUTION FOLLOWS EFFICIENCY , SYMMETRY , LINEARITY , AND NULL PLAYER PROPERTIES , IT ALSO JOINTLY ATTRIBUTES TO THE VARIABLES IN THE CASE WHEN VARIABLES ARE HIGHLY DEPENDENT AND INDEPENDENT ATTRIBUTION IS NOT DESIRABLE
480	MACHINE LEARNING FOR OPTIMIZATION OPT , MACHINE LEARNING MSOM , SUPPLY CHAIN
480	IT TALKS ABOUT HOW DATA FROM OR SYSTEMS CAN BE USED TO EXPLAIN THE OUTCOMES OF AN OR ALGORITHM 
481	THE COBB DOUGLAS LEARNING MACHINE
481	WE PROPOSE A NOVEL MACHINE LEARNING APPROACH BASED ON ROBUST OPTIMIZATION , EXTENDING THE MINIMUM ERROR MINIMAX PROBABILITY MACHINE MODEL
481	OUR CONTRIBUTION IS THE ADAPTATION OF THE COBB DOUGLAS FUNCTION , A WELL KNOWN STRATEGY IN PRODUCTION ECONOMICS USED TO MODEL THE RELATIONSHIP BETWEEN TWO OR MORE INPUTS AND THE QUANTITY PRODUCED BY THOSE INPUTS
481	IN PARTICULAR , OUR PROPOSAL DEFINES THE TASK OF MAXIMIZING THE TWO CLASS ACCURACIES OF A BINARY CLASSIFICATION PROBLEM AS A COBB DOUGLAS FUNCTION
481	ROBUSTNESS IS CONFERRED BY USING A PROBABILISTIC FRAMEWORK IN WHICH EACH TRAINING PATTERN IS CLASSIFIED CORRECTLY EVEN FOR THE WORST POSSIBLE CLASS CONDITIONAL DENSITY FOR A GIVEN MEAN AND COVARIANCE MATRIX
481	EXPERIMENTS PERFORMED ON SEVERAL CLASSIFICATION DATASETS CONFIRM THESE VIRTUES , LEADING TO BEST AVERAGE PERFORMANCE IN COMPARISON TO VARIOUS ALTERNATIVE CLASSIFIERS
481	MACHINE LEARNING FOR OPTIMIZATION OPT , MACHINE LEARNING OPTIMIZATION , OPT , 
482	ACCELERATING COLUMN GENERATION VIA COLUMN MANAGEMENT AND SMART GRAPH REDUCTION FOR SOLVING VEHICLE ROUTING PROBLEMS
482	COLUMN GENERATION , CG , IS A WIDELY USED AND POWERFUL ITERATIVE TECHNIQUE FOR SOLVING A WIDE RANGE OF COMBINATORIAL OPTIMIZATION PROBLEMS , SUCH AS THE VEHICLE ROUTING PROBLEM WITH TIME WINDOWS , VRPTW , 
482	TWO CRITICAL DIFFICULTIES OF CG ARE COLUMN MANAGEMENT FOR THE MASTER PROBLEM AND THE NP HARDNESS OF THE SUB PROBLEM
482	IN THIS PAPER , WE PRESENT TWO NOVEL LEARNING BASED APPROACHES TO OVERCOME THE TWO AFOREMENTIONED CHALLENGES , THUS ACCELERATING CG
482	WE FIRST PROPOSE A REINFORCEMENT LEARNING COLUMN MANAGER TO SELECT PROMISING COLUMNS FROM THE GENERATED ONES TO MAINTAIN A STRONG FORMULATION OF MASTER PROBLEM
482	WE THEN DEVELOP A GRAPH NEURAL NETWORK DRIVEN NODE SELECTION MODEL THAT ACCURATELY IDENTIFIES THE NODES THAT ARE MOST LIKELY TO BE INCLUDED IN THE OPTIMAL SOLUTION OF THE SUB PROBLEM
482	EXPERIMENTS DEMONSTRATE THAT THE PROPOSED APPROACHES BOOST THE CG SIGNIFICANTLY
482	MACHINE LEARNING FOR OPTIMIZATION OPT , MACHINE LEARNING 
483	A GRAPH NEURAL NETWORK FOR OPTIMUM COMMUNICATION SPANNING TREE FORTIFICATION PROBLEM
483	WE PRESENT A TRI LEVEL MATHEMATICAL MODEL FOR THE FORTIFICATION DECISIONS OF OPTIMUM COMMUNICATION SPANNING TREE PROBLEM , OCST , AGAINST WORST CASE DISRUPTIONS , USING A GAME THEORETIC FRAMEWORK BETWEEN THE DEFENDER AND THE INTERDICTOR
483	WE CONSIDER UNCERTAINTY IN THE NUMBER OF DISRUPTIONS SINCE THE DEFENDER MAY NOT HAVE COMPLETE INFORMATION ABOUT THE INTERDICTOR S CAPABILITIES
483	TO SOLVE THE STOCHASTIC TRI LEVEL MODEL , WE USE BACKWARD SAMPLING FRAMEWORK WHERE OCST IS SOLVED USING BRANCH AND BENDERS CUT ALGORITHM , BBC , 
483	BBC IS NOT ABLE TO SOLVE LARGE SIZE INSTANCES , THEREFORE , WE USE GRAPH NEURAL NETWORK , GNN , TO SOLVE OCST
483	THROUGH EXTENSIVE NUMERICAL EXPERIMENTS , WE COMPARE THE COMPUTATIONAL PERFORMANCE OF BBC ALGORITHM AND GNN METHOD AND DEMONSTRATE THE ADVANTAGES OF THE PROPOSED STOCHASTIC MODEL
483	MACHINE LEARNING FOR OPTIMIZATION OPT , NETWORK OPTIMIZATION OPT , OPTIMIZATION UNDER UNCERTAINTY
484	DEVELOPING A REINFORCEMENT LEARNING BASED WATER QUALITY CONTROL SYSTEM
484	MANAGING WATER QUALITY IS A COMPLEX TASK , REQUIRING THE MONITORING OF INTERDEPENDENT CONTAMINANTS AND THEIR CONTROL USING MEASURES SUCH AS FLUSHING , FILTRATION , CHEMICAL INJECTION , AND TEMPERATURE ADJUSTMENT
484	THE CHALLENGE IS AMPLIFIED BY THE STAGNATION AND LENGTHY TRANSIT TIMES DURING THE DELIVERY PROCESS , ALONG WITH THE INTRICACIES OF THE HYDRAULIC SYSTEM AND THE NONLINEARITY OF WATER QUALITY FUNCTIONS
484	THIS RESEARCH INTRODUCES A REINFORCEMENT LEARNING , RL , BASED SYSTEM , A NOVEL APPROACH TO MAINTAINING OPTIMAL WATER QUALITY IN BUILDINGS
484	THE RL BASED SYSTEM , ADAPTABLE TO VARIOUS STRUCTURES AND CAPABLE OF HANDLING STOCHASTIC DEMAND CAN REGULATE THESE CONTROL MECHANISMS EFFECTIVELY AND ENSURE CONSISTENT SAFE FOR DRINKING WATER FOR THE END USERS , PRESENTING A SIGNIFICANT ADVANCEMENT IN THE FIELD
484	MACHINE LEARNING FOR OPTIMIZATION OPT , NONLINEAR OPTIMIZATION MULTIPLE CRITERIA DECISION MAKING
485	A QUADRATIC SURFACE SUPPORT VECTOR MACHINE FOR IMBALANCED CLASSIFICATION
485	THIS PAPER STUDIES THE PROBLEM OF CONSTRUCTING A ROBUST NONLINEAR CLASSIFIER WHEN THE DATA SET IS IMBALANCED
485	UTILIZING THE HIDDEN MOMENT INFORMATION EMBEDDED IN THE DATA POINTS , A DISTRIBUTIONALLY ROBUST CHANCE CONSTRAINED KERNEL FREE QUADRATIC SURFACE SUPPORT VECTOR MACHINE MODEL IS PROPOSED
485	THE PROPOSED MODEL IS REFORMULATED AS A FRACTIONAL PROGRAMMING PROBLEM WITH SECOND ORDER CONE CONSTRAINTS
485	EXTENSIVE COMPUTATIONAL EXPERIMENTS USING SYNTHETIC AND PUBLIC BENCHMARK DATA SUPPORT THE SUPERIOR PERFORMANCE OF THE PROPOSED MODEL OVER OTHER STATE OF THE ART MODELS , PARTICULARLY FOR CLASSIFYING THE IMBALANCED DATASETS
485	THE PROPOSED MODEL ALSO HAS DOMINATING PERFORMANCE ON A REAL WORLD APPLICATION TO BATTERY FAILURE PREDICTION WITH HIGHLY IMBALANCED DATA
485	MACHINE LEARNING FOR OPTIMIZATION OPT , OPTIMIZATION UNDER UNCERTAINTY OPT , LINEAR AND CONIC OPTIMIZATION
486	PROCESS OPTIMIZATION IN CHEESE PRODUCTION TO MITIGATE BACTERIAL CONTAMINATION
486	PROCESS OPTIMIZATION IN CHEESE PRODUCTION TO REDUCE WASTAGE BR DUE TO GLOBALIZATION OF MARKETS , PERISHABLE PRODUCTS ARE MOVING THROUGHOUT THE COUNTRY AND EXPORTED
486	QUALITY MONITORING AND TRACEABILITY ALONG THE SUPPLY CHAIN IS ESSENTIAL
486	THE PURPOSE OF OUR RESEARCH IS TO DEVELOP A HOLISTIC APPROACH TO ENSURE OPTIMUM YIELD IN CHEESE SUPPLY CHAIN BY OPTIMIZING SPECIFIED SET OF PARAMETERS INVOLVED IN CHEESE PRODUCTION
486	WE DEVELOPED A REINFORCEMENT LEARNING TECHNIQUE , Q LEANING MODEL , TO FILTER RELEVANT PARAMETERS IMPACTING CHEESE QUALITY AND YIELD LIKE TEMPERATURE , RENNET AMOUNT , SALT QUANTITY ETC
486	THE Q LEARNING MODEL GIVES US THE BEST ACTION OR OPTIMIZED VALUE OF PARAMETERS AT ALL STAGES OF CHEESE PRODUCTION THUS ENSURING MINIMUM WASTAGE 
486	MACHINE LEARNING FOR OPTIMIZATION OPT , OPTIMIZATION UNDER UNCERTAINTY SUPPLY CHAIN AND LOGISTICS IN PRACTICE
487	USING MACHINE LEARNING SURROGATES TO BRIDGE DIFFERENT TIME SCALES FOR OPTIMIZATION OF PLANT SCHEDULING AND SUPPLY CHAIN UNDER DISRUPTIONS
487	OPTIMAL MANAGEMENT OF SUPPLY CHAIN AND MANUFACTURING NETWORKS UNDER DISRUPTIONS REQUIRES THE INTEGRATION OF PLANT SCHEDULING WITH THE SUPPLY CHAIN OPERATION ITSELF
487	WHILE LARGE SCALE SUPPLY CHAINS ARE USUALLY OPERATED IN TERMS OF DAYS AND WEEKS , PLANT SCHEDULING MODELS CONSIDER A FINER TIME DISCRETIZATION , I E HOURLY OR MINUTELY , 
487	EMBEDDING RIGOROUS SCHEDULING FORMULATIONS DIRECTLY INTO SUPPLY CHAIN MODELS REQUIRES THE USE OF THE SMALLER TIME SCALE USED IN PLANT DYNAMICS , WHICH MAY LEAD TO INTRACTABLE OPTIMIZATION PROBLEMS
487	HENCE , IN THIS WORK USE MACHINE LEARNING SURROGATES TO CHARACTERIZE THE FEASIBLE REGION OF RIGOROUS PLANT SCHEDULES AND WE INCORPORATE SUCH MODELS INTO REACTIVE SUPPLY CHAIN OPTIMIZATION FORMULATIONS
487	MACHINE LEARNING FOR OPTIMIZATION OPTIMIZATION , OPT , SUPPLY CHAIN AND LOGISTICS IN PRACTICE
488	UTILIZING MULTIMEDIA BIG DATA ANALYTICS TO EVALUATE TRANSPORTATION DISRUPTIONS IN NEAR REAL TIME FOLLOWING HURRICANE EVENTS
488	EMERGENCY RESPONDERS ARE DRIVEN BY LOGISTICAL ISSUES LIKE WHAT RESOURCES ARE NEEDED , WHEN AND WHERE , AND HOW THOSE RESOURCES SHOULD BE DELIVERED DURING DISASTER EVENTS
488	FOR A DISASTER RESPONSE TO BE SUCCESSFUL AND EFFECTIVE , SITUATIONAL AWARENESS OF THE STATE OF THE TRANSPORTATION INFRASTRUCTURE ALONG WHICH KEY MOVEMENTS , SUCH AS SUPPLY DISTRIBUTION AND SEARCH AND RESCUE MISSIONS MUST OCCUR , IS CRUCIAL
488	TO DO THIS , WE DEVELOP A FRAMEWORK THAT USES CUTTING EDGE DATA ANALYTICS TOOLS AND TECHNIQUES TO ROUTE IMPORTANT RESOURCES WHILE TAKING ADVANTAGE OF SOCIAL MEDIA AND OTHER DATA SOURCES FOR ESSENTIAL AND TIMELY INFORMATION
488	WE PRESENT THE WORK IN PROGRESS TOWARD IMPLEMENTING THIS FRAMEWORK USING HURRICANE HARVEY AS A TESTBED
488	MACHINE LEARNING FOR OPTIMIZATION PUBLIC SECTOR OR TRANSPORTATION SCIENCE AND LOGISTICS , TSL , 
488	IT DISCUSSES HOW SOCIAL MEDIA AND OTHER DATA SOURCE ARE HARNESSED TO EVALUATE ROAD DISRUPTIONS 
489	DISCOVERING TRUE OPTIMAL SOLUTIONS FROM RESPONSE SURFACE MODELS WITH ERRORS
489	THIS RESEARCH FOCUSES ON RESPONSE SURFACE OPTIMIZATION USING A MONOTONIC NEURAL NETWORK TO ESTIMATE THE RESPONSE SURFACE
489	BECAUSE THE RESPONSE SURFACE ESTIMATED BY TRAINING A NEURAL NETWORK FROM DATA MUST CONTAIN A PREDICTION ERROR , THE OPTIMAL SOLUTION DETERMINED FROM THIS RESPONSE SURFACE CANNOT BE CONSIDERED TRUE OPTIMAL
489	TO ADDRESS THIS , WE PROPOSE A METHOD TO IDENTIFY THE TRUE OPTIMAL SOLUTION WHEN THERE IS A MONOTONIC RELATIONSHIP BETWEEN INPUT FACTORS AND THE RESPONSE
489	BY MODIFYING THE OBJECTIVE FUNCTION BASED ON THE DIFFERENCE BETWEEN TARGET AND PREDICTED VALUES , OUR APPROACH ITERATIVELY SEARCHES FOR THE OPTIMAL SOLUTION
489	NUMERICAL EXPERIMENTS ON SYNTHETIC EXAMPLES CONFIRMED THE EFFECTIVENESS OF OUR METHOD IN FINDING TRUE OPTIMAL SOLUTIONS
489	MACHINE LEARNING FOR OPTIMIZATION QUALITY , STATISTICS AND RELIABILITY DATA MINING
489	RESPONSE SURFACE OPTIMIZATION USING NETWORKS TRAINED FROM LARGE DATA 
490	DESIGN VARIABLE SELECTION IN PERSONALIZED SYSTEM DESIGN THROUGH BAYESIAN OPTIMIZATION
490	ACHIEVING AN EFFECTIVE PERSONALIZED DESIGN POLICY THROUGH BAYESIAN OPTIMIZATION , BO , REMAINS A COMPUTATIONAL CHALLENGE WITH HIGH DIMENSIONAL DESIGN VARIABLES
490	CONSTRUCTING A RELIABLE SURROGATE MODEL INVOLVES CONDUCTING COMPUTATIONALLY INTENSIVE SIMULATIONS AND COSTLY PREDICTIONS
490	MOREOVER , POLICY PARAMETERS OPTIMIZATION IS TIME CONSUMING
490	CONVENTIONAL BO TACKLES THE FIRST TASK BY TAKING A LOWER DIMENSIONAL SUBSPACE WITH THE IMPORTANT VARIABLES
490	HOWEVER , IN PERSONALIZED SYSTEM DESIGN , THE DESIGN VARIABLE SELECTION MUST ACCOUNT NOT ONLY FOR THEIR IMPORTANCE IN SURROGATE MODEL BUT ALSO FOR THEIR VARIANCE IN DESIGN POLICY
490	WE PROPOSE A BO ALGORITHM THAT DEVELOPS A NEW IMPORTANCE SCORE TO ASSESS THE RELEVANCE OF EACH DESIGN VARIABLE IN GP AND DESIGN POLICY
490	BOTH THE RESULTS ON THE SYNTHETIC DATA AND CASE STUDY DEMONSTRATE THE EFFECTIVENESS AND ROBUSTNESS
490	MACHINE LEARNING FOR OPTIMIZATION QUALITY , STATISTICS AND RELIABILITY DIVERSITY , EQUITY , AND INCLUSION
491	MINIMIZING MAKESPAN FOR JOB SHOP SCHEDULING PROBLEM USING DEEP LEARNING MODEL EMPLOYING CRITICAL PATHS OF SCHEDULES FOR LARGE NEIGHBORHOOD SEARCH
491	WE PROPOSE A HEURISTIC FOR JOB SHOP SCHEDULING PROBLEMS , JSSP , MINIMIZING MAKESPAN BY DEVELOPING DEEP LEARNING MODELS TO IDENTIFY PARTS OF THE SCHEDULE TO RECONSTRUCT IN LARGE NEIGHBORHOOD SEARCH
491	RECENT STUDIES HAVE DEMONSTRATED THAT DEEP LEARNING CAN PERFORM WELL TO BUILD INITIAL SOLUTIONS OF JSSP OR OTHER COMBINATORIAL OPTIMIZATION PROBLEMS STEP BY STEP
491	HOWEVER , THERE HAVE BEEN FEW DISCUSSIONS ON IMPROVING SOLUTIONS AFTER TAKING RELATIONSHIP WITH MAKESPAN AND CRITICAL PATHS OF THE INCUMBENT SCHEDULE INTO ACCOUNT
491	IN THIS PRESENTATION , WE DISCUSS THE EFFECTIVENESS OF DEVELOPING DEEP LEARNING MODULES TRAINED WITH CRITICAL PATHS FOR MAKESPAN MINIMIZATION IN JSSP WHICH CAREFULLY SELECT THE PARTS OF THE SCHEDULE WHICH NEED TO BE RESCHEDULED
491	MACHINE LEARNING FOR OPTIMIZATION SCHEDULING AND PROJECT MANAGEMENT OPT , MACHINE LEARNING
492	GENERATING DIVERSE SOLUTIONS FOR VEHICLE ROUTING PROBLEMS VIA REINFORCEMENT LEARNING
492	DEEP REINFORCEMENT LEARNING METHODS HAVE SHOWN SIGNIFICANT PROMISE AT GENERATING SOLUTIONS TO VEHICLE ROUTING PROBLEMS IN A SEQUENTIAL DECISION PROCESS
492	AT TEST TIME , THESE METHODS USUALLY SAMPLE MULTIPLE SOLUTIONS PER INSTANCE FROM A TRAINED MODEL TO SEARCH FOR HIGH QUALITY SOLUTIONS
492	HOWEVER , IT HAS BEEN OBSERVED THAT TRAINED MODELS CAN SUFFER FROM OVERCONFIDENCE IN THEIR ACTIONS DURING THE SEQUENTIAL CONSTRUCTION PROCESS WHICH CAN LEAD TO LOW SOLUTION VARIETY AND HENCE AN IMPAIRED SEARCH PERFORMANCE
492	WE EVALUATE EXISTING TECHNIQUES THAT ALLOW TO INCREASE SOLUTION DIVERSITY AND THEIR IMPACT ON THE OVERALL SEARCH PERFORMANCE
492	FURTHERMORE , WE PRESENT A NOVEL APPROACH THAT SIGNIFICANTLY INCREASES THE SOLUTION DIVERSITY AND EVALUATE IT ON THE VEHICLE ROUTING PROBLEM AND THE VEHICLE ROUTING PROBLEM WITH TIME WINDOWS
492	MACHINE LEARNING FOR OPTIMIZATION TRANSPORTATION SCIENCE AND LOGISTICS , TSL , ARTIFICIAL INTELLIGENCE
492	THE APPROACH CAN LEARN CUSTOMIZED HEURISTICS FOR THE PROBLEM AT HAND BASED ON HISTORIC PROBLEM DATA 
493	AN ACCURACY SENSITIVE FEATURE SELECTION MODEL SVM WITH STEP LOSS FUNCTION
493	THIS STUDY PROPOSES A COST EFFECTIVE AND ACCURACY SENSITIVE ℓ NORM SUPPORT VECTOR MACHINE WITH STEP LOSS FUNCTION , CEAS SVM , TO HANDLE FEATURE SELECTION COST UNDER ACCURACY SENSITIVITY
493	THE OBJECTIVES OF THE PROPOSED MODEL ARE TO MINIMIZE MISCLASSIFICATION AND MAXIMIZE THE LOWER BOUNDS OF THE TRUE POSITIVE RATE AND TRUE NEGATIVE RATE
493	FROM THE EMPIRICAL TESTING RESULTS , OUR MODEL IS INSENSITIVE TO OUTLIERS
493	IN ADDITION , IT SHOWS THAT THE CEAS SVM PERFORMS HIGHER OUT OF SAMPLE ACCURACY THAN OTHER BENCHMARK MODELS WHILE CONSIDERING THE FEATURE COST
493	THE PROPOSED MODEL CAN EXTEND TO HANDLING INDIVIDUAL FEATURE AND GROUP STRUCTURE COST BASED FEATURE SELECTION EVEN UNDER FEATURE COST UNCERTAINTY , SAVING MORE MONEY
493	MACHINE LEARNING FOR OPTIMIZATION 
494	SEQUENTIAL DECISION MAKING , SDM , WITH LONG TERM REWARD ESTIMATES
494	WE STUDY OPTIMAL CONTROL PROBLEMS , WHEREIN ACTIONS TO BE TAKEN AT A TIME STEP ARE DEPENDENT ON A DYNAMICAL SYSTEM S BEHAVIOR SUCH AS REALIZED DEMAND OR PROCESS BEHAVIOR IN A PLANT
494	TRADITIONAL SDM METHODS MAY NOT ACCOUNT FOR LONG TERM EFFECTS OF DECISIONS OR CHANGING CONDITIONS
494	IN OUR FRAMEWORK , WE EXTEND OUR OBJECTIVE FUNCTION WITH TWO PARTS THE FIRST PART IS THE REWARDS WITHIN THE TIME HORIZON FOR OPTIMAL POLICY , AND WE ALSO INCLUDE A MODIFIER TO THE OBJECTIVE
494	THE MODIFIER TERM IS THE EXPECTED REMAINING REWARD AFTER THE RECOMMENDED POLICIES
494	THEREFORE , WE CAN CAPTURE THE HOLISTIC REWARD OF THE SCENARIO , ALLOWING US TO ENSURE THAT THE RECOMMENDED POLICIES BENEFIT NOT ONLY THE PERIOD OF THE RECOMMENDATION BUT ALSO THAT THE SYSTEM IS BROUGHT INTO A GOOD SYSTEM STATE FOR BETTER FUTURE REWARDS
494	WE BENCHMARK THE PERFORMANCE OF OUR MODEL ON A USE CASE FROM A PROCESSING PLANT
494	MACHINE LEARNING FOR OPTIMIZATION ML AND OPTIMIZATION APPLIED TO SENSOR DATA 
495	DIESEL ENGINE DEFECT PREDICTION FRAMEWORK USING QUANTUM MECHANICS BASED NEURAL NETWORK
495	DATA IS COLLECTED FROM SENSORS ATTACHED TO PROCESS EQUIPMENT THROUGH AUTOMATION
495	COMPANIES CAN IMPROVE ECONOMICS AND SAFETY BY PREDICTING ENGINE DEFECTS IN ADVANCE USING DIESEL ENGINE DEFECT DATA , ONE OF THE MANUFACTURING PROCESS DATA
495	DIESEL ENGINE DEFECTS CAN BE PREDICTED THROUGH NEURAL NETWORK ANALYSIS , WHICH IS A REPRESENTATIVE DATA ANALYSIS TECHNIQUE
495	HOWEVER , THE DATA COLLECTED FROM THE SENSOR AND THE WEIGHTS OF THE NEURAL NETWORK MODEL CONTAIN NOISE
495	THIS ADVERSELY AFFECTS THE ACCURACY OF NEURAL NETWORK ANALYSIS
495	THEREFORE , IN THIS STUDY , A QUANTUM MECHANICS BASED NEURAL NETWORK IS MODELED BY CONSIDERING THE UNCERTAINTY OF DATA AND THE WEIGHT OF THE NEURAL NETWORK
495	IN ADDITION , THE PROPOSED FRAMEWORK PROPOSES A NEW WEIGHT UPDATE METHODOLOGY MODELED BY STOCHASTIC DIFFERENTIAL EQUATIONS BY REFLECTING THE DRIFT OF WEIGHT AND CONSIDERING THE UNCERTAINTY
495	MACHINE LEARNING FOR OPTIMIZATION 
496	SUPERVISED AND UNSUPERVISED DEEP LEARNING FOR WORKLOAD CLASSIFICATION
496	A RECURING DECISION IN ANY DATA CENTER INVOLVES OPTIMALLY MATCHING THE COMPUTATIONAL REQUIREMENTS OF AN ARBITRARY WORKLOAD WITH THE COMPUTATIONAL CAPABILITIES OF THE AVAILABLE SERVERS AND THEIR SPECIFIC PROVISIONING
496	AS A FIRST STEP IN THIS DECISION PROCESS TO UTILIZE THE FULL POTENTIAL OF A SOFTWARE HARDWARE SYSTEM AND OBTAIN SCALABLE PERFORMANCE IMPROVEMENTS , A SET OF MEANINGFUL AND ACCURATE WORKLOAD CLASSIFIERS IS ESSENTIAL
496	THIS PAPER PROPOSES SUPERVISED AND UNSUPERVISED DEEP LEARNING WORKLOAD ANALYSIS TOOLS TO CAPTURE COMPLEX WORKLOAD DYNAMICS
496	OUR EXPERIMENTS SHOW THAT THESE TOOLS CAN PRECISELY CLASSIFY WORKLOADS BY USING LATENT FEATURE REPRESENTATIONS FROM DEEP LEARNING MODELS
496	MACHINE LEARNING IN OPERATIONS ARTIFICIAL INTELLIGENCE DATA MINING
496	OUR RESEARCH AIMS AT OPTIMIZING WORKLOAD PERFORMANCE BY EMPLOYING DATA ANALYTICS
497	METAMODELS OF A SEARCH SIMULATOR FOR MARITIME SEARCH OPERATIONS EFFICIENCY EVALUATION 
497	PLANNING AN EFFICIENT MARITIME SEARCH AND RESCUE OPERATION , MSAR , REQUIRES ESTIMATING THE QUALITY OF SEARCH PLANS
497	NOWADAYS , DECISION SUPPORT SYSTEMS , DSS , FOR MSAR PLANNING USE MONTE CARLO DRIFT SIMULATION AND SEARCH SIMULATORS
497	CARRYING MULTIPLE SIMULATIONS IS COMPUTATIONALLY INTENSIVE
497	WE PRESENT SUPERVISED LEARNING BASED METAMODELS TO REDUCE THE TIME REQUIRED TO FIND HIGH QUALITY SEARCH PLANS AND ANSWER THE FOLLOWING QUESTIONS , CAN THE PROBABILITY OF SUCCESS BE CLOSELY APPROXIMATED
497	TO WHAT EXTENT DOES OUR APPROACH IMPROVE THE CURRENT SYSTEM
497	MACHINE LEARNING IN OPERATIONS ARTIFICIAL INTELLIGENCE SIMULATION SOCIETY
497	WE USE AN AI BASED APPROACH TO CREATE METAMODELS OF A SEARCH OPERATION SIMULATOR FOR MARITIME SEARCH 
498	LEARNING TO MAKE ADHERENCE AWARE ADVICE
498	AS AI SYSTEMS CONTINUE TO CONTRIBUTE TO HUMAN DECISION MAKING , IT IS FREQUENTLY OBSERVED THAT HUMAN AGENTS SOMETIMES DISREGARD THE ADVICE PROVIDED BY AI
498	THE PROBABILITY THAT THE HUMAN AGENT FOLLOWS THE AI S ADVICE IS CALLED THE AGENT S ADHERENCE LEVEL
498	ALTHOUGH THE OPTIMAL ADVICE IS THE BEST ACTION FOR THE AGENT WHEN THE ADHERENCE LEVEL IS , WHEN THE ADHERENCE LEVEL IS LESS THAN , IT MIGHT BECOME SUBOPTIMAL FOR THE AI SYSTEM TO PROVIDE THE SAME ADVICE
498	WE PROPOSE A DECISION MAKING MODEL THAT AIMS TO PROVIDE OPTIMAL ADHERENCE AWARE ADVICE , ACCOUNTING FOR THE VARYING LEVELS OF ADHERENCE EXHIBITED BY HUMAN AGENTS ACROSS DIFFERENT STATES AND ACTIONS
498	IN ADDITION TO THE MODEL , WE INTRODUCE ACCOUNTABLE AND NEAR OPTIMAL REINFORCEMENT LEARNING ALGORITHMS SPECIFICALLY DESIGNED TO ADDRESS ADHERENCE AWARE ADVICE
498	MACHINE LEARNING IN OPERATIONS ARTIFICIAL INTELLIGENCE 
499	DISTANCE CORRELATION CAN ENHANCE UNDERSTANDING OF RECURRENT NEURAL NETWORKS FOR TIME SERIES FORECASTING
499	OUR CURRENT UNDERSTANDING OF HOW RECURRENT NEURAL NETWORKS , RNN , LEARN TIME SERIES FORECASTING IS LIMITED
499	WE ADAPT A STATISTICAL DEPENDENCY MEASURE , CALLED DISTANCE CORRELATION , TO INVESTIGATE THE NON LINEAR RELATIONSHIPS OF RNN ACTIVATION LAYERS WITH THE VARIABLES OF INTEREST SUCH AS PREDICTION TIME HORIZON AND LAG CHARACTERISTICS
499	WE CONDUCT A SERIES OF EXPERIMENTS THAT SHOW RNNS LEARN AUTO REGRESSIVE TIME SERIES WELL BUT STRUGGLE WITH DATA EXHIBITING HETEROSCEDASTICITY
499	WE ALSO GENERATE HEATMAPS TO SHOW A VISUAL REPRESENTATION OF RNN ACTIVATION LAYERS AT VARIOUS TIME EPOCHS AND FOR DIFFERENT NETWORK ARCHITECTURES
499	WE BELIEVE OUR APPROACH CAN BE USEFUL TO CHARACTERIZE THE EFFECTIVENESS OF OTHER NEURAL NETWORKS IN THE FUTURE
499	MACHINE LEARNING IN OPERATIONS ARTIFICIAL INTELLIGENCE 
500	UNRAVELING EFFECTIVE TEAMWORK STRATEGIES WITH GRAPH NEURAL NETWORKS
500	EFFECTIVE TEAMWORK IS CRUCIAL IN THE BUSINESS FIELD
500	THIS STUDY INVESTIGATES THE EFFECTIVE TEAMWORK STRATEGY USING A NOVEL DEEP LEARNING APPROACH
500	PREVIOUS LITERATURE INVESTIGATES THE APPROPRIATE WAY OF TEAMWORK MAINLY BASED ON SEPARATE INDIVIDUALS , WHICH INSUFFICIENTLY TAKES ADVANTAGE OF THE RELATIONSHIP BETWEEN AGENT TO AGENT AND AGENT TO THE WORKING ENVIRONMENT
500	WE DEVELOP A NOVEL DEEP LEARNING GRAPH NEURAL NETWORKS , GNN , FRAMEWORK TO MODEL THE INTERACTIONS BETWEEN SALES AGENTS AND PROVIDE SUGGESTIONS FOR EFFECTIVE TEAMWORK
500	THE RESULT COULD PROVIDE INSIGHTS INTO THE EFFECTIVE STRATEGIES OF TEAMWORK FOR HIGHER SALES PERFORMANCE
500	ALSO , THE FINDING INVESTIGATES WHETHER EFFECTIVE TEAMWORK CAN SERVE AS A SUBSTITUTE FOR JOB TRAINING , WHICH PROVIDES A POSSIBLE ALTERNATIVE FOR BUSINESS OPERATIONS
500	MACHINE LEARNING IN OPERATIONS DATA MINING MULTIPLE CRITERIA DECISION MAKING
500	USING THE NOVEL ML METHOD TO DATA MINING 
501	ABNORMAL DETECTION USING TWO STAGE METHOD IN COMBINED POWER PLANT
501	THE PAPER PRESENTS A TWO STAGE MODEL FOR DETECTING ABNORMAL EVENTS IN COMPLEX SYSTEMS USING TIME SERIES CLUSTERING AND THE MAHALANOBIS DISTANCE
501	STAGE ONE INVOLVES CLUSTERING SENSORS WITH SIMILAR PATTERNS USING A DTW BASED TIME SERIES CLUSTERING ALGORITHM
501	A HEALTH INDICATOR IS THEN COMPUTED FOR EACH CLUSTER USING PCA AND THE MAHALANOBIS DISTANCE
501	IN STAGE TWO , THE MAHALANOBIS DISTANCE CALCULATES AN ABNORMAL SCORE FOR EACH DATA POINT , AND POINTS EXCEEDING A PREDEFINED THRESHOLD ARE FLAGGED AS ABNORMAL
501	THE METHOD WAS EVALUATED USING REAL WORLD POWER PLANT DATA , SHOWING SUPERIOR ACCURACY AND EFFICIENCY COMPARED TO EXISTING TECHNIQUES
501	THIS APPROACH HAS THE POTENTIAL TO REDUCE COMPUTATIONAL RESOURCES NEEDED FOR ABNORMAL EVENT DETECTION , MAKING IT PROMISING FOR REAL WORLD APPLICATIONS
501	MACHINE LEARNING IN OPERATIONS DATA MINING QUALITY , STATISTICS AND RELIABILITY TWO STAGE MODEL FOR DETECTING ABNORMAL EVENTS IN COMPLEX SYSTEMS IN REAL TIME DATA STREAMS 
502	REAL TIME DECISION SUPPORT FOR HUMAN MACHINE INTERACTION IN DIGITAL RAILWAY CONTROL ROOMS
502	IN DIGITAL RAILWAY CONTROL ROOMS , TRAFFIC OPERATORS CAN ON THE SPOT CHOOSE TO USE AUTOMATION
502	AS THESE CHOICES ARE FREQUENTLY SUBOPTIMAL , WE PROPOSE A REAL TIME DECISION SUPPORT TOOL TO IMPROVE HUMAN MACHINE INTERACTION , HMI , AT INFRABEL , BELGIUM S RAILWAY INFRASTRUCTURE COMPANY
502	THE TOOL PROVIDES DESCRIPTIVE , PREDICTIVE AND PRESCRIPTIVE ANALYTICS ON BOTH EXPECTED AND DESIRABLE HMI AT THE MINUTE LEVEL FOR EACH WORKSTATION
502	WE BENCHMARK CLUSTERING BASED APPROACHES FOR THE DESCRIPTIVES , AND MACHINE AND DEEP LEARNING APPROACHES FOR THE PREDICTIONS
502	TO OBTAIN PRESCRIPTIONS , WE COMPARE THE PREDICTIONS OF HMI WITH THEIR DESIRABLE COUNTERPARTS
502	SHAPLEY VALUES ARE DEPLOYED TO FOSTER MODEL EXPLAINABILITY AND WE DOCUMENT A GENERATIONAL DIFFERENCE IN THE DISTANCE BETWEEN EXPECTED AND DESIRABLE HMI
502	MACHINE LEARNING IN OPERATIONS EMERGING TECHNOLOGIES AND APPLICATIONS ARTIFICIAL INTELLIGENCE
502	WE PROVIDE DATA DRIVEN DECISION SUPPORT FOR HMI IN A REAL WORLD OPERATIONAL SETTING 
503	OFF POLICY LEARNING OF CONTENT PROMOTIONS , OPTIMAL CURATION OF DIGITAL DISTRIBUTION CHANNELS
503	WE PRESENT AN OFF POLICY LEARNING FRAMEWORK FOR OPTIMIZING WHICH CONTENT A DIGITAL PUBLISHER SHALL PROMOTE ON ITS DISTRIBUTION CHANNELS
503	OUR FRAMEWORK COMPRISES A DECISION MODEL , AN IDENTIFICATION AND EVALUATION METHOD , AND A CAUSAL MACHINE LEARNING PROCEDURE
503	WE SHOW THEORETICALLY THAT THE OPTIMAL POLICY SELECTS THE CONTENT WITH TOP RANKED CONDITIONAL AVERAGE TREATMENT EFFECT PER TIME PERIOD , THAT THE ESTIMATION PROCEDURE IS SUFFICIENT , NECESSARY AND DOUBLY ROBUST , AND THAT OUR ESTIMATION ALGORITHM IS COMPUTATIONALLY EFFICIENT
503	WE PARTNER WITH AN INTERNATIONAL NEWSPAPER AND , USING LARGE SCALE INTERNAL DATA , DEMONSTRATE THAT THE OPTIMAL POLICY IMPROVES UPON THE STATUS QUO AND BASELINE METHODS BY PERCENT IN TERMS OF THE KEY BUSINESS METRIC
503	OUR WORK CONTRIBUTES TO PREVIOUS RESEARCH BY SUPPORTING CONTENT PUBLISHERS IN CURATING THEIR DISTRIBUTION CHANNELS
503	MACHINE LEARNING IN OPERATIONS MACHINE LEARNING FOR OPTIMIZATION INFORMATION SYSTEMS
503	OUR WORK LEVERAGES STREAMING AND LOGGING DATA REGULARLY COLLECTED BY INTERNET COMPANIES 
504	MICHAEL GEURTSEN
504	DISCOVERING THE OPTIMAL MAINTENANCE PLANNING STRATEGY CAN HAVE A MASSIVE IMPACT ON PRODUCTION EFFICIENCY , YET THIS ASPECT IS OFTEN OVERLOOKED IN FAVOR OF PRODUCTION PLANNING
504	OUR STUDY EMPHASIZES THE SIGNIFICANCE OF MAINTENANCE PLANNING IN THE DYNAMIC CONTEXT OF AN ASSEMBLY FAB CONSISTING OF MULTIPLE ASSEMBLY LINES
504	BY MAXIMIZING THE AVERAGE PRODUCTION RATE AND CONSIDERING FACTORS SUCH BUFFER CONTENTS , MACHINE PRODUCTION STATES , PLANNING WINDOWS AND SCARCE RESOURCES , WE ADDRESS A UNIQUE PROBLEM INVOLVING THE PLANNING OF MAINTENANCE ON THE FINAL MACHINE OF MULTIPLE SERIAL ASSEMBLY LINES
504	WE EMPLOY NOVEL AVERAGE REWARD DEEP REINFORCEMENT LEARNING TECHNIQUES AND COMPARE THEM TO GENERIC DISPATCHING METHODS
504	THROUGH EXPERIMENTS USING A DIGITAL TWIN WITH REAL WORLD DATA , WE DEMONSTRATE THE IMMENSE POTENTIAL OF THIS NEW DEEP REINFORCEMENT LEARNING TECHNIQUE
504	MACHINE LEARNING IN OPERATIONS MANUFACTURING AND SERVICE OPERATIONS MANAGEMENT , MSOM , ARTIFICIAL INTELLIGENCE
504	REAL WORLD DATA IS USED TO AS INPUT FOR A DIGITAL TWIN OF AN ASSEMBLY LINE , MAKING IT MORE REALISTIC 
505	MULTI PRODUCT INVENTORY CONTROL WITH CONSIDERATION OF SHIPPING COST AND DEMAND LEARNING
505	WE CONSIDER THE PROBLEM OF A FIRM THAT SELLS TWO PRODUCTS WITH UNKNOWN DEMAND AND AIMS TO MINIMIZE THE TOTAL INVENTORY AND SHIPPING COST
505	EXTRA SHIPPING COST IS INCURRED IF ANY ITEM IN A CUSTOMER ORDER STOCKS OUT AND NEEDS TO BE SHIPPED LATER SEPARATELY
505	WE FIRST ANALYZE THE FIRM S PROBLEM WITH KNOWN DEMAND INFORMATION AND THEN STUDY THE PROBLEM WHERE THE DEMAND INFORMATION IS UNKNOWN AND THE FIRM NEEDS TO LEARN IT
505	MACHINE LEARNING IN OPERATIONS MSOM , SUPPLY CHAIN 
506	FROM LOCAL TO GLOBAL LEARNING FOR DATA DRIVEN DYNAMIC INVENTORY CONTROL , A PRACTICAL APPLICATION OF PRESCRIPTIVE ANALYTICS
506	BUILDING ON WEIGHTED SAMPLE AVERAGE APPROXIMATION , WE DEVELOP A PRACTICAL PRESCRIPTIVE ANALYTICS APPROACH FOR THE REAL WORLD DYNAMIC INVENTORY CONTROL PROBLEM OF A LARGE NETWORK OF PHARMACIES WITH MANY HETEROGENEOUS PRODUCTS
506	USING CONTEXTUAL FEATURE INFORMATION , WE PROPOSE A GLOBAL LEARNING MODEL THAT IS TRAINED SIMULTANEOUSLY ACROSS ALL PRODUCTS TO SPECIFY CONDITIONAL SAMPLE WEIGHTS
506	THE RESULTS OF OUR NUMERICAL EXPERIMENTS SUGGEST A SIGNIFICANT IMPROVEMENT OVER MODELS THAT ARE TRAINED SEPARATELY FOR EACH PRODUCT
506	MACHINE LEARNING IN OPERATIONS OPT , OPTIMIZATION UNDER UNCERTAINTY OPT , MACHINE LEARNING
506	MY TALK PROPOSES A GLOBAL LEARNING APPROACH TO MAKE BEST USE OF RICH DATA SOURCES IN OPTIMISATION 
507	IMBALANCE AWARE LSTM FOR DIGITAL TWIN BASED CONTROL CHART PATTERN RECOGNITION
507	DIGITAL TWINS , DT , BASED PREDICTIVE MODELS FIND THEIR ROOTS IN SMART MANUFACTURING , HOWEVER , LIMITED RESEARCH EXISTS ON APPLICATIONS OF DT BASED MODELS TO THE CONTROL CHART PATTERN RECOGNITION , CCPR , ALGORITHMS , WHICH LIE AT THE HEART OF ADVANCED FAULT DETECTION SYSTEMS
507	A KEY OBSERVATION IN CCPR PREDICTIVE MODELS IS THE PRESENCE OF A HIGH DEGREE OF IMBALANCE BETWEEN THE CLASSES , WHICH DETERIORATES THE PERFORMANCE OF THE ALGORITHM IF LEFT UNTREATED
507	IN THIS WORK , WE PROPOSE A LONG SHORT TERM MEMORY , LSTM , BASED NEURAL NETWORK MODEL WITH A COST SENSITIVE LOSS FUNCTION TO ADDRESS THE SEVERE IMBALANCE BETWEEN CLASSES
507	WE PARTICULARLY FIT OUR MODEL TO DATASETS OBTAINED FROM A DATA SIMULATION SCHEME THAT CAN PRODUCE ABNORMAL PATTERNS IN REAL TIME
507	OUR RESULTS INDICATE THAT OUR LSTM ALGORITHM OUTPERFORMS EXISTING METHODS
507	MACHINE LEARNING IN OPERATIONS SIMULATION SOCIETY QUALITY , STATISTICS AND RELIABILITY
507	ENHANCING CONTROL CHART RECOGNITION WITH DATA DRIVEN LSTM MODELS FOR IMPROVED DECISION MAKING 
508	A MACHINE LEARNING ENHANCED MULTI ROBOT PATH PLANNING PROTOCOL FOR AMR INTRALOGISTICS
508	MULTI ROBOT PATH PLANNING , MRPP , PLAYS A CRITICAL ROLE IN THE FLEET MANAGEMENT OF AUTONOMOUS MOBILE ROBOTS , AMR , INTRALOGISTICS , INFLUENCING CONFLICT INCIDENCE AND INFORMING TASK ALLOCATION THROUGH TRAVEL TIME PREDICTIONS
508	HOWEVER , TRADITIONAL METHODS USE DETERMINISTIC MULTIAGENT PATHFINDING , MAPF , ALGORITHMS OR ASSUME ARBITRARY DELAY PROBABILITIES IN STATIC PLANNING SCENARIOS , FAILING TO ADDRESS REAL WORLD UNCERTAINTIES
508	WE PROPOSE A REAL TIME , RESERVATION BASED MRPP PROTOCOL COUPLED WITH A MACHINE LEARNING BASED TIME ESTIMATOR
508	THIS INNOVATIVE APPROACH REDUCES REPLANNING AND TIMEOUTS , ENHANCING TASK SCHEDULING ACCURACY AND ENSURING THAT AMRS EXECUTE TASKS AS PLANNED
508	MACHINE LEARNING IN OPERATIONS SIMULATION SOCIETY SUPPLY CHAIN AND LOGISTICS IN PRACTICE
509	PROBABILISTIC INVENTORY ESTIMATION IN GROCERY WITH INACCURATE RECORDS
509	INVENTORY MANAGEMENT IS IMPORTANT IN INDUSTRIES SUCH AS GROCERY AND RETAIL , BUT TAKING INVENTORY CAN BE TEDIOUS AND TIME CONSUMING
509	PERPETUAL INVENTORY METHODS ARE OFTEN USED TO ESTIMATE INVENTORY , BUT THESE METHODS ARE SENSITIVE TO INVENTORY RECORD INACCURACY , IRI , AND PERISHABILITY
509	TO IMPROVE INVENTORY ESTIMATE ACCURACY , WE PRESENT A PROBABILISTIC GENERATIVE MODEL , INVHMM , THAT EXPLICITLY MODELS IRI AND PERISHABILITY
509	WE USE A PARTICLE FILTER TO INFER THE POSTERIOR INVENTORY , AS WELL AS A NOVEL PARTICLE SMOOTHING ALGORITHM TO ESTIMATE PAST INVENTORY RETROSPECTIVELY
509	ON A DATASET FROM A MAJOR US GROCERY CHAIN , INVHMM IMPROVES INVENTORY ESTIMATE ACCURACY OVER A SIMPLY PERPETUAL INVENTORY BY AND GIVES WELL CALIBRATED CONFIDENCE BOUNDS
509	MACHINE LEARNING IN OPERATIONS SUPPLY CHAIN AND LOGISTICS IN PRACTICE APPLIED PROBABILITY 
509	USING DATA TO MODEL PERISHABILITY INVENTORY TAKING BEHAVIOR TO BETTER ESTIMATE CONTROL INVENTORY 
510	INTEGRATED GA ML SOLUTION METHOD FOR LOCATION INVENTORY ROUTING PROBLEM
510	WE PRESENT AN INTEGRATED METHOD FOR THE LOCATION INVENTORY ROUTING PROBLEM
510	THE METHOD COMBINES GA WITH MACHINE LEARNING
510	THE NUMERICAL RESULTS ARE PRESENTED
510	WE ALSO APPLIED THE METHOD TO A REAL WORLD HEALTHCARE PROBLEM
510	MACHINE LEARNING IN OPERATIONS SUPPLY CHAIN AND LOGISTICS IN PRACTICE OPT , INTEGER AND DISCRETE OPTIMIZATION
510	WE ADDRESS A REAL WORLD PROBLEM WITH MACHINE LEARNING 
511	MAINTENANCE OPTIMIZATION OF INLAND WATERWAY TRANSPORTATION SYSTEM VIA SIMULATION AND MACHINE LEARNING
511	MAINTENANCE OPTIMIZATION IS CRITICAL IN MINIMIZING THE NEGATIVE IMPACT OF NATURAL AND MAN MADE DISRUPTIONS ON INLAND WATERWAY TRANSPORTATION SYSTEMS
511	THIS RESEARCH TAKES ADVANTAGE OF AGENT BASED SIMULATION AND MACHINE LEARNING TO ENABLE EFFICIENT MAINTENANCE FOR THE CONTINUED OPERATION OF INLAND WATERWAY TRANSPORTATION SYSTEMS
511	MACHINE LEARNING IN OPERATIONS 
512	DATA DRIVEN PREDICTIVE MAINTENANCE IN COUNTER PRESSURE CASTING PROCESS 
512	COUNTER PRESSURE CASTING , CPC , IS A PROCESS TECHNOLOGY USED TO MANUFACTURE ALUMINUM AUTOMOTIVE PARTS , WHERE THE MOLD IS FILLED BY HAVING A SLIGHT PRESSURE DIFFERENTIAL
512	PREDICTIVE MAINTENANCE OF CPC EQUIPMENT IS CRUCIAL TO AVOID QUALITY DEGRADATIONS SUCH AS AIR ENTRAPMENT AND POROSITY INSIDE THE PARTS
512	THE OPERATING CONDITIONS CHARACTERIZED BY HIGH TEMPERATURE AND PRESSURE , COUPLED WITH THE INACCESSIBILITY OF INTERNAL COMPONENTS HINDER THE ADAPTATION OF PRE EMPTIVE MANAGEMENT
512	THIS STUDY PROPOSES AN AUTOENCODER BASED OPERATIONAL ANOMALY DETECTION METHOD FOR THE DATA DRIVEN CPC EQUIPMENT MAINTENANCE TO ADDRESS THIS CHALLENGE
512	THE RESULT LOOKS PROMISING , EXPECTING THAT THE MANUFACTURERS MAY ACHIEVE THE REDUCTION OF MAINTENANCE COSTS AND IMPROVED QUALITY OF THE PARTS BY ADAPTING THE PREDICTIVE MAINTENANCE METHODS
512	MACHINE LEARNING IN OPERATIONS 
513	A BAYESIAN FRAMEWORK FOR FORECASTING SPARE PART FAILURES
513	THIS STUDY FOCUSES ON DEVELOPING AN EFFICIENT FRAMEWORK TO FORECAST SPARE PART FAILURES FOR A GLOBAL COMPUTER MANUFACTURER
513	OUR RESULTS SHOW THAT IN ADDITION TO THE NUMBER OF COMPUTERS IN USE , AGE , WARRANTY EXPIRATION , SEASON , AND LOCATION SPECIFIC FACTORS , LIKE MONSOON SEASON IN COASTAL INDIA , IMPACT THE NUMBER OF FAILURES
513	FURTHERMORE , USING A BAYESIAN APPROACH , WE FIND THAT TRANSFERRING STATISTICAL INFORMATION FROM AN OLDER PRODUCT SIGNIFICANTLY IMPROVES FORECAST ACCURACY
513	THE BENEFIT IS MOST PRONOUNCED DURING THE INITIAL MONTH PERIOD OF THE PRODUCT S LIFE CYCLE
513	LASTLY , WE DISCUSS THE IMPLICATIONS OF THIS FORECASTING METHODOLOGY ON THE SUPPLY CHAIN AND INVENTORY MANAGEMENT
513	MACHINE LEARNING IN OPERATIONS 
514	A MACHINE LEARNING FRAMEWORK FOR PREDICTION OF HURRICANE EVACUATION DECISIONS OF HOUSEHOLDS , THE CASE OF HURRICANE IRMA
514	THE EFFECTIVENESS OF EVACUATION MANAGEMENT DURING NATURAL DISASTERS HEAVILY RELIES ON HOUSEHOLDS COMPLIANCE WITH EVACUATION ORDERS
514	THUS , COMPREHENDING THE FACTORS THAT INFLUENCE HOUSEHOLD BEHAVIOR DURING AN EVACUATION IS CRUCIAL FOR EVACUATION PLANNING
514	DESPITE ADVANCEMENTS IN IDENTIFYING FACTORS THAT INFLUENCE HOUSEHOLD EVACUATION BEHAVIOR , PREDICTING SUCH BEHAVIOR REMAINS CHALLENGING AS THESE FACTORS ARE INTERTWINED
514	ARTIFICIAL INTELLIGENCE , AI , CAN AID POLICYMAKERS IN SYNTHESIZING DATA FROM VARIOUS FACTORS AND IDENTIFYING HOUSEHOLDS WITH DIFFERENT PROBABILITIES OF EVACUATION
514	IN THIS PAPER , WE APPLY MACHINE LEARNING , ML , ALGORITHMS TO A UNIQUE SURVEY DATASET OF HOUSEHOLDS THAT EVACUATED DURING HURRICANE IRMA IN , CONTRIBUTING TO THE FIELD OF DISASTER MANAGEMENT
514	MACHINE LEARNING IN OPERATIONS THE STUDY AIMS TO CONTRIBUTE TO THE FIELD OF DISASTER MANAGEMENT BY UTILIZING ML METHODS
515	HARNESSING DATA FOR BETTER CUSTOMER SERVICE
515	DATA WAVES ARE HERE TO STAY AND IN FACT COMES LIKE TSUNAMI
515	HOW WE CAN LEVERAGE DATA IN THE FORM OF PHONE CALLS , EMAILS AND SOCIAL MEDIA CHATS TO ARRIVE AT SENTIMENT SCORES OF CUSTOMERS AND CAN HELP ORGANIZATIONS LEVERAGE THE SENTIMENTS , IMPROVE ON PROBLEM AREAS TO PROVIDE BETTER SERVICE AND EXPERIENCES TO CUSTOMERS WILL BE DISCUSSED
515	MACHINE LEARNING IN OPERATIONS DATA USAGE FOR BETTER CUSTOMER SERVICE 
516	CONVENIENCE , PERSONALIZATION , AND ENGAGEMENT IN AN AGRICULTURAL ADVISORY SERVICE
516	AUTOMATED SYSTEMS HAVE BEEN USED TO DELIVER INFORMATION IN AREAS SUCH AS PUBLIC HEALTH , EDUCATION , AND AGRICULTURE
516	AUTOMATED DELIVERY ENABLES USERS TO CONSUME INFORMATION AT A CONVENIENT TIME AND PLACE
516	WE EXAMINE WHETHER PERSONALIZING TIMING OF INFORMATION DELIVERY IN AN AGRICULTURAL ADVISORY SERVICE CAN LEAD TO HIGHER USER ENGAGEMENT
516	WE DEVELOP , IMPLEMENT , AND EVALUATE A PERSONALIZED RECOMMENDATION SYSTEM THAT CUSTOMIZES CONTACT TIMES TO USER CHARACTERISTICS
516	WE FIND SCOPE FOR SIGNIFICANT GAINS FROM PERSONALIZED RECOMMENDATION IN TERMS OF FARMERS PROPENSITY TO PICK UP CALLS , ESTIMATING AN INCREASE OVER THE BASELINE PICK UP
516	WE ADDRESS SEVERAL CHALLENGES TO IMPLEMENTING CUSTOMIZED POLICIES IN DEVELOPING COUNTRY SETTINGS , SUCH AS BANDWIDTH CONSTRAINTS , EQUITY EFFICIENCY CONCERNS AND HOW TECHNOLOGY OR PREFERENCE SHOCKS AFFECT PERFORMANCE OF POLICIES
516	MACHINE LEARNING IN OPERATIONS IN MY TALK I WILL DESCRIBE HOW MACHINE LEARNING AND EXPERIMENTS CAN BE USED IN DEVELOPING COUNTRIES 
517	MACHINE LEARNING BASED VISION FOR ADDITIVE MANUFACTURING PROCESS
517	MANUFACTURING SYSTEMS ARE INCREASINGLY FACED WITH INTRUSIONS NOT ONLY BY TRADITIONAL MALICIOUS ACTORS SUCH AS HACKERS AND CYBER CRIMINALS BUT ALSO BY SOME COMPETITORS AND NATIONS ENGAGED IN CORPORATE ESPIONAGE
517	ARTIFICIAL INTELLIGENCE , AI , IS ONE OF THE NOVEL APPROACHES THAT HAS EMERGED TO OVERCOME THE INCREASING COMPLEXITY AND SOPHISTICATION OF CYBERSECURITY INTRUSIONS IN MANUFACTURING
517	THESE DEFENSIVE AND CONTROL BASED AI METHOD IMPLEMENTS VARIOUS MACHINE LEARNING ALGORITHMS FOR DIVERSE TYPES OF CONTROLS , SUCH AS INTRUSION DETECTION AND MALWARE DETECTION
517	IN THIS PAPER , THE AUTHORS PROPOSE AN ACTION FOR AI BASED INTRUSION AND ANOMALY CONTROLS IN RESEARCH AND PRACTICE FOR ADDITIVE MANUFACTURING
517	THIS PAPER PROPOSES A DEEP CONVOLUTIONAL NEURAL NETWORK THAT IS THE MOST COMMON TYPE OF NEURAL NETWORK THAT USE TO RECOGNIZE PATTERNS IN AM IMAGES THROUGH D PRINTING
517	MANUFACTURING AND SERVICE OPERATIONS MANAGEMENT , MSOM , ARTIFICIAL INTELLIGENCE DATA DRIVEN INNOVATIONS IN OR EDUCATION
518	CHALLENGES OF THE MANUFACTURING SECTOR IN SELECTED CITIES IN NIGERIA 
518	THE PAPER DISCUSSED CHALLENGES OF THE MANUFACTURING SECTOR IN SELECTED CITIES IN NIGERIA
518	THE RESEARCH QUESTIONS ADDRESSED THE EXTENT TO WHICH EPILEPTIC POWER SUPPLY , ABSENCE RAW MATERIALS , IMPORTATION OF FOREIGN PRODUCTS , HIGH RATE OF FOREIGN EXCHANGE AND HIGH RATE OF TAXATION CONSTITUTE A CHALLENGE TO THE MANUFACTURING SECTOR IN SELECTED CITIES IN NIGERIA
518	THE CORE ASPECT OF THE STUDY IS THE USE OF CROSS SECTIONAL RESEARCH SURVEY IN GENERATING THE PRIMARY DATA USED FOR ANALYSIS
518	THE RESEARCH IS BASED ON THREE CITIES , LAGOS , PORT HARCOURT AND IBADAN WHERE MAJOR MANUFACTURING ACTIVITIES TAKE PLACE IN NIGERIA
518	A SAMPLE SIZE OF WAS SELECTED FROM A POPULATION MILLION INDUSTRIAL WORKERS IN THE THREE CITIES
518	MANUFACTURING AND SERVICE OPERATIONS MANAGEMENT , MSOM , BEHAVIORAL OPERATIONS MANAGEMENT ENRE , ENVIRONMENT AND SUSTAINABILITY YES 
519	SUB SCHEDULING AND SEQUENCING OF TASKS BASED ON A HEURISTICS BASED APPROACH SUB 
519	HEURISTIC STUDY OF SCHEDULING AND SEQUENCING MANUFACTURING EQUIPMENT HAS BEEN DONE EXTENSIVELY
519	THE STUDY WILL SUGGEST CURRENT TRENDS
519	THE STUDY WILL CLASSIFY EACH SCHEDULING AND SEQUENCING PROBLEM INTO SINGLE MACHINE SCHEDULING , FLOW SHOP SCHEDULING , JOB SHOP SCHEDULING , AND OPENSHOPSCHEDULING AND EXAMINE THE DIFFERENCES AND THE BEST SITUATION TO EMPLOY BASED ON THE DATA
519	THIS IDEA WOULD IMPROVE DELIVERY PERFORMANCE , PRODUCTION TIME , AND COST , BENEFITING THE READING COMMUNITY
519	DAILY DECISION MAKERS ALSO WANT TO FIND THE BEST WAY TO EFFICIENTLY CONTROL RESOURCES TO MANUFACTURE PRODUCTS FOR MANUFACTURING AND SERVICE INDUSTRIES
519	IT WOULD ALSO NOTIFY THE COMMUNITY THAT HEURISTIC MODELS CAN HANDLE SECTOR SPECIFIC SCHEDULING AND SEQUENCING ISSUES
519	MANUFACTURING AND SERVICE OPERATIONS MANAGEMENT , MSOM , DATA MINING BEHAVIORAL OPERATIONS MANAGEMENT
520	TEXT MINING IN MANUFACTURING , A SYSTEMATIC LITERATURE REVIEW
520	WITH THE EMERGENCE OF CYBER PHYSICAL MANUFACTURING SYSTEMS , THE MANUFACTURING INDUSTRY HAS GENERATED ONE OF THE LARGEST SHARES OF DATA IN RECENT YEARS AND IS PROJECTED TO GROW SIGNIFICANTLY IN THE UPCOMING YEARS , ACCORDING TO IDC
520	STRUCTURED DATA MAKES UP A SMALL PORTION OF THE TOTAL , WHILE THE MAJORITY CONSISTS OF SEMI STRUCTURED AND UNSTRUCTURED DATA LIKE TEXT DOCUMENTS
520	TEXT MINING , TM , CAN BE USED TO EXTRACT INFORMATION FROM MANUFACTURING UNSTRUCTURED DATA , HOWEVER , COMPREHENSIVE REVIEWS OF TM APPLICATIONS IN MANUFACTURING ARE LIMITED
520	THIS STUDY SYSTEMATICALLY REVIEWS ARTICLES PUBLISHED ON TM APPLICATIONS IN MANUFACTURING , ANALYZING PRIME APPLICATION FIELDS , IDENTIFYING KEY CHALLENGES , AND PROPOSING FUTURE RESEARCH DIRECTIONS
520	THE FINDINGS INFORM THE RESEARCH COMMUNITY ABOUT THE NOVEL TM APPLICATIONS IN MANUFACTURING AND RESEARCH OPPORTUNITIES
520	MANUFACTURING AND SERVICE OPERATIONS MANAGEMENT , MSOM , DATA MINING EMERGING TECHNOLOGIES AND APPLICATIONS 
520	IT STUDIES HOW TEXT MINING CAN BE USED TO EXTRACT KNOWLEDGE FROM MANUFACTURING UNSTRUCTURED DATA 
521	EVALUATION OF MANUAL ASSEMBLY LINE BALANCING PROBLEM IN FLEXIBLE MANUFACTURING AND UNCERTAIN OPERATOR PERFORMANCE
521	UNCERTAINTY IN MANUAL ASSEMBLY OPERATIONS CAN SIGNIFICANTLY IMPACT MANUFACTURING PROCESSES , RESULTING IN LATE DELIVERIES AND POTENTIAL LOSS OF REVENUE
521	THIS RESEARCH ADDRESSES THE CHALLENGE OF OPTIMIZING UNCERTAIN TASK DURATIONS OF A MANUAL ASSEMBLY LINE IN FLEXIBLE MANUFACTURING TO MINIMIZE LATENESS AND MAXIMIZE REVENUE
521	WE PROPOSE AN APPROACH TO ASSIGNING OPERATORS TO ASSEMBLY TASKS , WITHOUT PRIOR KNOWLEDGE OF THEIR PERFORMANCE , WHICH IS PERIODICALLY REEVALUATED TO ENSURE OPTIMAL ASSIGNMENT AND BALANCE OF THE ASSEMBLY LINE
521	OUR APPROACH CONSIDERS THE UNCERTAIN AND VARIABLE NATURE OF MANUAL ASSEMBLY OPERATIONS , AND LEVERAGES THE ASSEMBLY LINE BALANCING PROBLEM FRAMEWORK TO ACHIEVE OPTIMAL EFFICIENCY
521	WE DEMONSTRATE THE EFFECTIVENESS OF OUR APPROACH THROUGH NUMERICAL SIMULATIONS AND PROVIDE RECOMMENDATIONS FOR IMPLEMENTATION IN MANUFACTURING PROCESSES
521	MANUFACTURING AND SERVICE OPERATIONS MANAGEMENT , MSOM , DECISION ANALYSIS SOCIETY OPTIMIZATION , OPT , 
522	FLEXIBILITY AND AUTOMATION AS ANTIDOTES FOR EMPLOYEE OVERLOADED
522	AN EMPIRICAL ANALYSIS IN DIGITAL CONTROL ROOMS
522	WORKLOAD AND AUTOMATION RECEIVE INCREASING ATTENTION IN LIGHT OF INDUSTRY WE EXAMINE HOW OPERATORS , OVER , WORKLOAD IS INFLUENCED BY THEIR OWN AND THEIR PEERS FLEXIBILITY , AND THEIR USE OF AUTOMATION
522	OUR EMPIRICAL ANALYSIS BUILDS UPON A PURPOSEFULLY CONSTRUCTED OPERATIONAL DATA SET IN A DIGITAL CONTROL ROOM SETTING
522	MANUFACTURING AND SERVICE OPERATIONS MANAGEMENT , MSOM , FAIRNESS IN OPERATIONS SOCIAL OPERATIONS MANAGEMENT
523	THE OPTIMAL POLICY FOR PERIODIC STOCKING AND BUNDLING
523	WE INVESTIGATE THE OPTIMAL POLICY FOR JOINT INVENTORY REPLENISHMENT AND BUNDLING DECISIONS , WHERE A SELLER PERIODICALLY REPLENISHES INDIVIDUAL PRODUCTS AS WELL AS BUNDLES THEM TO ANOTHER SELLING ITEM
523	THE SELLER BACKLOGS UNMET DEMANDS AND CARRIES OVER UNSOLD ITEMS AIMING TO MINIMIZE THE TOTAL DISCOUNTED COST OVER A FINITE HORIZON
523	WE REVEAL THAT THERE EXISTS AN ECONOMIC RELATIONSHIP SUCH THAT EACH COUPLE OF THE BUNDLE AND AN INDIVIDUAL PRODUCT SHOULD BE REGARDED AS SUBSTITUTES WHILE INDIVIDUAL ONES AS COMPLEMENTS FOR EACH OTHER
523	WE CHARACTERIZE THE OPTIMAL POLICY AND PROPOSE EFFICIENT ALGORITHMS TO COMPUTE THE POLICY AS WELL AS PROVIDE A MYOPIC POLICY THAT MAY BE OPTIMAL UNDER CERTAIN REGULARITIES
523	MANUFACTURING AND SERVICE OPERATIONS MANAGEMENT , MSOM , INFORMATION SYSTEMS 
524	JUDICIAL CENTRALIZATION AND FIRMS IN HOUSE PRODUCTION , QUASI EXPERIMENTAL EVIDENCE FROM CHINA
524	FIRM DECISONS REGARDING IN HOUSE PRODUCTION OR OUTSOURCING IS A KEY SOURCE OF ECONOMIC GROWTH BUT INVOLVE SIGNIFICANT RISK OF HOLD UP AND IMPERFECT ENFORCEMENT OF CONTRACTS , WHICH MAKES A SOUND JUDICIAL SYSTEM HIGHLY IMPORTANT
524	USING A STAGGERED DIFFERENCE IN DIFFERENCES DESIGN , WE FIND THE INTRODUCTION OF THE CIRCUIT TRIBUNALS IN CHINA , WHICH ALLEVIATES LOCAL INTERVENTION ON THE JUDICIAL SYSTEM , REDUCES FIRMS IN HOUSE PRODUCTION SHARPLY
524	JUDICIAL CENTRALIZATION HAS MUCH STRONGER EFFECTS ON SMALL FIRMS , PRIVATE FIRMS , AND HIGH GROWTH FIRMS
524	FINALLY , WE FIND THAT JUDICIAL CENTRALIZATION INDEED INCREASES FIRMS CONFIDENCE IN THE JUDICIAL SYSTEM AS SEEN IN AN INCREASE IN BOTH THE NUMBER OF FIRM INITIATED LAWSUITS AND THE CLAIMED AMOUNT OF FUNDS IN THE TREATED AREAS
524	MANUFACTURING AND SERVICE OPERATIONS MANAGEMENT , MSOM , LOCATION ANALYSIS SUPPLY CHAIN AND LOGISTICS IN PRACTICE
524	WE USE NOVEL DATA ON LEGAL CASES 
525	VERTICAL PRODUCT LOCATION EFFECT ON SALES , A FIELD EXPERIMENT IN CONVENIENCE STORES
525	MOST RETAILERS USE THE EYE LEVEL LOCATION TO ENHANCE DEMAND
525	YET , LITTLE IS KNOW ABOUT WHAT HAPPENS TO PRODUCTS AT OTHER SHELVES WHEN A PRODUCT IS MOVED TO THE EYE LEVEL
525	WE STUDY HOW CHANGING VERTICAL LOCATIONS OF PRODUCTS IN A SHELVING UNIT IMPACTS PRODUCT SALES AND OVERALL SALES , AND WHETHER THIS EFFECT VARIES ACROSS PRODUCTS
525	WE CONDUCTED A WEEK FIELD EXPERIMENT AT C STORES
525	OUR RESULTS SHOW THAT THE EYE LEVEL GENERATES AN ADDITIONAL AND MORE DEMAND COMPARED TO THE STOOP LEVEL AND THE STRETCH LEVEL
525	YET , THIS INCREASE COMES AT AN EXPENSE OF DEMAND LOSS AT OTHER SHELVES , LEADING TO PURE SUBSTITUTION AMONG PRODUCTS
525	WE ALSO FIND THAT THE VERTICAL LOCATION EFFECT VARIES ACROSS PRODUCTS
525	INCORPORATING THIS HETEROGENEITY INTO PLANOGRAM OPTIMIZATION CAN INCREASE PROFIT BY AT THE FOCAL RETAILER , A SIGNIFICANT IMPROVEMENT OVER USING HOMOGENEOUS EFFECTS
525	MANUFACTURING AND SERVICE OPERATIONS MANAGEMENT , MSOM , MSOM , SERVICE OPERATIONS IT IS AN A B EXPERIMENT SHOWING THAT HOW DATA CAN HELP RETAILERS TO MAKE DECISION 
526	A DIGITAL TWIN FRAMEWORK FOR PRODUCTION PLANNING OPTIMIZATION
526	WE DEVELOP A DIGITAL TWIN FRAMEWORK THAT ALLOWS FOR PRACTICAL TESTING , EVALUATION , AND IMPLEMENTATION OF NEW PRODUCTION OPTIMIZATION APPROACHES
526	THE ULTIMATE GOAL IS TO FACILITATE INDUSTRY ADOPTION OF THESE TECHNIQUES BY BRIDGING THEORY AND PRACTICE
526	TO ILLUSTRATE THE APPROACH IN COLLABORATION WITH A SOFTWARE AND DATA ANALYTICS FIRM SUPPORTING MANUFACTURERS IN THE AEROSPACE SUPPLY CHAIN , WE BUILD , A FACTORY GENERATOR ACCURATELY REPRESENTING LARGE SCALE PRODUCTION FACILITIES , , A MULTI LEVEL CAPACITATED LOT SIZING PROBLEM , MLCLSP , APPROACH TO GENERATE A PRODUCTION PLAN FOR AN EXTENDED PLANNING HORIZON WITH FULL TRACEABILITY OF CUSTOMER SALES ORDERS , , HEURISTICS CAPABLE OF TRANSLATING PRODUCTION PLANS INTO EXECUTABLE SCHEDULES , AND , ADVANCED ANALYTICS AND VISUALIZATIONS FOR EVALUATING THE RESULTING SCENARIOS AND SCHEDULES
526	MANUFACTURING AND SERVICE OPERATIONS MANAGEMENT , MSOM , MSOM , SUPPLY CHAIN OPT , INTEGER AND DISCRETE OPTIMIZATION
526	THE RESEARCH PROMOTES THE USE OF OR TECHNIQUES IN INDUSTRY WITH THE SUPPORT OF DIGITAL TWINS 
527	MANAGING PERISHABLE INVENTORY WHEN STRATEGIC CUSTOMERS FORM A REFERENCE ON PRODUCT AVAILABILITY
527	CONSIDER A RETAILER SELLING A PERISHABLE PRODUCT IN THE PRESENCE OF STRATEGIC CUSTOMERS WHO USE THEIR REFERENCE ON PRODUCT AVAILABILITY TO TIME THEIR PURCHASES
527	EACH SHORT PERIOD , THE RETAILER DETERMINES A STOCKING QUANTITY BEFORE RANDOM DEMAND IS REALIZED AND STRATEGIC CUSTOMERS LEARN FROM THE RETAILER S STOCKING QUANTITY TO UPDATE THEIR REFERENCE
527	WE CHARACTERIZE THE STRUCTURAL PROPERTIES OF SINGLE PERIOD , TWO PERIOD , AND INFINITE HORIZON PROBLEMS , AND CONDUCT NUMERICAL STUDIES ON AN INFINITE HORIZON TO COMPARE AN OPTIMAL DYNAMIC POLICY AND THE CORRESPONDING OPTIMAL STATIC POLICY WHICH SETS A FIXED STOCKING QUANTITY OVER TIME
527	A NEAR OPTIMAL PERFORMANCE OF OPTIMAL STATIC POLICY WITH AN AVERAGE PROFIT GAP OF LESS THAN IS REMARKABLE AND CONTRASTS WITH THAT IN THE TWO PERIOD MODEL WHICH MAY BE FAR WORSE
527	MANUFACTURING AND SERVICE OPERATIONS MANAGEMENT , MSOM , MSOM , SUPPLY CHAIN OPT , OPTIMIZATION UNDER UNCERTAINTY
527	OUR FRAMEWORK IS USEFUL FOR DATA DRIVEN DECISIONS OVER TIME FOR A FIRM LEARNING FROM THE CUSTOMERS 
528	CAPACITY INVESTMENT AND PRICING STRATEGIES ACROSS INTERNATIONAL MARKETS UNDER CURRENCY EXCHANGE RATE AND TARIFF UNCERTAINTY
528	THIS PAPER ANALYZES CAPACITY INVESTMENT AND PRICING STRATEGIES FOR A MULTINATIONAL MANUFACTURER TO HEDGE AGAINST EXCHANGE RATE AND TARIFF UNCERTAINTIES IN THE COMPETITIVE GLOBAL MARKET
528	BECAUSE OF LONG LEAD TIMES , THE CAPACITY INVESTMENT MUST BE DONE BEFORE THE SELLING SEASON BEGINS WHEN THE EXCHANGE RATE BETWEEN THE TWO COUNTRIES IS UNCERTAIN
528	WE CONSIDER A DUOPOLY COMPETITION IN THE FOREIGN COUNTRY
528	WE MODEL THE EXCHANGE RATE AS A RANDOM VARIABLE
528	AN ANALYTIC MODEL IS BUILT TO STUDY THE DUOPOLY COMPETITION IN A FOREIGN MARKET WITH BOTH CURRENCY EXCHANGE RATE AND TARIFF RATE AS EXOGENOUS VARIABLES
528	WE FIND THE OPTIMAL CAPACITY INVESTMENT AND PRICING STRATEGY GIVEN VARIOUS EXCHANGE RATE AND DIFFERENT TARIFF POLICY STATUSES
528	SOME PENETRATING MANAGERIAL INSIGHTS ARE GENERATED
528	CASE DISCUSSION AND NUMERICAL TESTS CONFIRM OUR FINDINGS
528	MANUFACTURING AND SERVICE OPERATIONS MANAGEMENT , MSOM , MSOM , SUPPLY CHAIN OPT , OPTIMIZATION UNDER UNCERTAINTY
529	A COMPARISON OF STOCK OUT SCENARIOS CONSIDERING THE RISK ATTITUDE OF THE RETAILER
529	WE EVALUATE TWO PRACTICALLY COMMON APPROACHES FOR HANDLING EXCESS DEMAND THROUGH THE LENS OF A RETAILER , NEWSVENDOR , WHOSE RISK ATTITUDE , RISK NEUTRAL VS RISK AVERSE , IS MODELED , EXPLICITLY
529	THE DIFFERING STOCK OUT POLICIES ARE INVESTIGATED FOR BOTH TYPES OF RISK ATTITUDES UTILIZING THE CORRESPONDING EXPECTED PROFIT BASED AND CONDITIONAL VALUE AT RISK BASED METHODOLOGIES
529	DEPENDING ON THE RISK ATTITUDE AND PARTICULAR COST PARAMETER RELATIONSHIPS , WE EXPLORE SETTINGS THAT REVEAL THE SUPERIOR WAY FOR HANDLING STOCK OUT SCENARIOS AND PRESENT PRACTICAL INSIGHTS REGARDING THE PROFITABILITY OF EACH SCENARIO
529	MANUFACTURING AND SERVICE OPERATIONS MANAGEMENT , MSOM , MSOM , SUPPLY CHAIN OPT , OPTIMIZATION UNDER UNCERTAINTY
530	SUPPLY CHAIN MODEL FOR THREE ECHELON SUPPLY CHAIN FOR DETERIORATING ITEMS
530	THIS PAPER PROPOSED THREE ECHELON SUPPLY CHAIN MODELS
530	IN THIS STUDY , WE HAVE CONSIDERED THAT AFTER PRODUCTION , THE MANUFACTURER SUPPLIES THE PERISHABLE ITEMS TO THE SUPPLIER
530	THEN THE RETAILER RECEIVES THE PRODUCT FROM THE SUPPLIER FOR SALE TO THE CUSTOMERS
530	THE RETAILER ASSUMES THE CUSTOMER S SEASONAL DEMAND AND THE SUPPLIER S UNCERTAIN LEAD TIME
530	IN THIS MODEL , THE PRODUCT EXPIRATION DATE IS ALSO CONSIDERED
530	THE MODEL HELPS THE COMPLETE SUPPLY STAKEHOLDERS TO OPTIMIZE THEIR PROFITS BY MANAGING OPTIMAL INVENTORY
530	THE CONVEXITY OF THE MODEL HAS BEEN CHECKED , AND NUMERICAL ILLUSTRATIONS HAVE AIDED THE MODEL S SUITABILITY
530	MANUFACTURING AND SERVICE OPERATIONS MANAGEMENT , MSOM , MSOM , SUPPLY CHAIN OPTIMIZATION , OPT , 
531	CROP PRODUCTION IN EMERGING ECONOMIES , THE VALUE OF PRICING MECHANISMS
531	THIS PAPER EXAMINES AN AGRICULTURAL SUPPLY CHAIN FOR A PARTICULAR CROP , WHERE FARMERS CAN CHOOSE TO SELL THEIR PRODUCT IN A SIDE MARKET OR TO A PROCESSING PLANT
531	IN ADDITION , THE GOVERNMENT OFFERS A MINIMUM PRICE GUARANTEE FOR THE CROP
531	WE EXPLORE VARIOUS PRICING STRATEGIES THAT THE PROCESSING PLANT CAN USE TO ENGAGE WITH FARMERS REGARDING LAND AND HARVEST ALLOCATION DECISIONS
531	WE DEVELOP TWO STAGE STOCHASTIC PROGRAM MODELS TO ANALYZE THESE ALLOCATION AND PRICING DECISIONS AT AN AGGREGATE FARMING LEVEL
531	MANUFACTURING AND SERVICE OPERATIONS MANAGEMENT , MSOM , MSOM , SUPPLY CHAIN PUBLIC SECTOR OR 
532	FORECAST DRIVEN DUAL SOURCING INVENTORY MANAGEMENT USING SIMULATION OPTIMIZATION
532	DYNAMIC SUPPLIER MANAGEMENT IS AN EFFECTIVE STRATEGY FOR A SUPPLY CHAIN OPERATING IN A VOLATILE AND DISRUPTIVE ENVIRONMENT
532	WE STUDY A DUAL MODE FORECAST DRIVEN INVENTORY MANAGEMENT PROBLEM FOR A REAL WORLD FURNITURE MANUFACTURER
532	THE MANUFACTURER FACES A NON STATIONARY STOCHASTIC DEMAND AND ENFORCES A CHANCE STOCK OUT CONSTRAINT FOR CONSISTENT PRODUCT AVAILABILITY
532	WE CONSIDER TWO SUPPLIERS , REGULAR WHO HAS STOCHASTIC LEAD TIME , AND AN EMERGENCY SUPPLIER WITH A CONSTANT LEAD TIME BUT HIGHLY VULNERABLE TO DISRUPTIONS
532	WITH DAILY UPDATE OF DEMAND FORECASTS , WE EMPLOY A SIMULATION OPTIMIZATION APPROACH TO ESTIMATE INVENTORY POLICY PARAMETERS
532	WE COMPARE THE PERFORMANCE OF THREE RELEVANT POLICIES NAMELY SINGLE INDEX , DUAL INDEX AND TAILORED BASE SURGE , AND INVESTIGATE THE SENSITIVITY OF THE POLICY PARAMETERS TO SUPPLIER CHARACTERISTICS AND CONSTRAINTS
532	MANUFACTURING AND SERVICE OPERATIONS MANAGEMENT , MSOM , MSOM , SUPPLY CHAIN SUPPLY CHAIN AND LOGISTICS IN PRACTICE
532	OUR DYNAMIC APPROACH ENABLES SUPPLY CHAINS TO BENEFIT FROM THEIR VALUABLE YET UNDERUTILIZED DATA 
533	RELATIVE VS
533	ABSOLUTE VOLUME BASED EXPORT RESTRICTIONS , CHOICE , DESIGN , AND EFFECTIVENESS
533	MANUFACTURERS IN DEVELOPING ECONOMIES ARE OFTEN SUBJECT TO EXPORT RESTRICTIONS BY REGULATORS
533	IN THIS PAPER , WE EXAMINE THE IMPACT OF A REGULATOR S CHOICE OF EXPORT BASED RESTRICTIONS , RELATIVE AND ABSOLUTE VOLUME BASED , ON A MANUFACTURER AND ON THE SOCIETY
533	MANUFACTURING AND SERVICE OPERATIONS MANAGEMENT , MSOM , MSOM , SUPPLY CHAIN 
534	VERIFICATION AND VALIDATION , BUILDING TRUST IN DIGITAL TWINS
534	DIGITAL TWIN , DT , INVOLVES THE INTEGRATION OF INTERNET OF THINGS , IOT , , MACHINE LEARNING , ML , , ARTIFICIAL INTELLIGENCE , AI , , CLOUD COMPUTING , AND OTHER INNOVATIVE TECHNOLOGIES TO PREDICT THE OUTCOMES OF ITS PHYSICAL COUNTERPART , AS WELL AS TO GENERATE WHAT IF SCENARIOS AND TO SUPPORT DECISION MAKING
534	ALTHOUGH THE DEFINITION OF DT VARIES AMONG EXPERTS , DTS ARE MODELS , AND AS WITH ANY MODEL , A DT NEEDS TO BE VERIFIED AND VALIDATED IN ORDER TO BE TRUSTED AND USED IN REAL WORLD ENVIRONMENTS
534	OUR RESEARCH INVESTIGATED THE STATUS OF DT VERIFICATION AND VALIDATION , V V , 
534	WE FOUND THAT VERY FEW STUDIES REPORTED V V PROCEDURES AND THAT THERE IS DISAGREEMENT OVER WHAT VERIFICATION AND VALIDATION IN THE CONTEXT OF DTS REPRESENT
534	TO ADDRESS THIS GAP , WE DEVELOPED A METHODOLOGY AND DEMONSTRATED IT IN A CASE STUDY
534	MANUFACTURING AND SERVICE OPERATIONS MANAGEMENT , MSOM , MSOM , TECHNOLOGY , INNOVATION AND ENTREPRENEURSHIP EMERGING TECHNOLOGIES AND APPLICATIONS 
534	DIGITAL TWIN INTEGRATES BIG DATA , CLOUD COMPUTING , ML AI , ETC TO SUPPORT DECISIONS IN MANY SCENARIOS 
535	MANUFACTURING RESCHEDULING AFTER CRISIS OR DISASTER CAUSED SUPPLY CHAIN DISRUPTION
535	IN THIS PAPER , WE ADDRESS THE RESCHEDULING CHALLENGES FACED BY A REPAIR SHOP FOLLOWING MAJOR SUPPLY DISRUPTIONS
535	THESE DISRUPTIONS CAUSE DELAYS IN PRODUCTION AND ORDER DELIVERY , NECESSITATING THE RESCHEDULING OF UNFINISHED PARTS
535	OUR STUDY CONSIDERS THE HOLDING COSTS ASSOCIATED WITH FINISHED AND UNFINISHED PARTS , AS WELL AS SETUP COSTS WHEN SWITCHING BETWEEN PART TYPES
535	WE FORMULATE THE RESCHEDULING PROBLEM AS AN INTEGER PROGRAM , AIMING TO MINIMIZE TOTAL TARDINESS , SETUP COST , AND HOLDING COST
535	THEN , WE PROPOSE A TWO STAGE GENETIC ALGORITHM THAT INCORPORATES AN ESTIMATION OF DISTRIBUTION ALGORITHM FOR ENHANCED SEARCH
535	WE EVALUATE THE ALGORITHM USING DATA FROM A HEAVY MACHINERY MAINTENANCE PROVIDER
535	RESULTS SHOW THAT OUR APPROACH OUTPERFORMS THE INITIAL SCHEDULE AND OTHER BENCHMARK ALGORITHMS WITHOUT SACRIFICING COMPUTATIONAL TIME
535	MANUFACTURING AND SERVICE OPERATIONS MANAGEMENT , MSOM , OPT , INTEGER AND DISCRETE OPTIMIZATION SCHEDULING AND PROJECT MANAGEMENT
535	WE DESIGN A TWO STAGE GENETIC ALGORITHM TO SEARCH FOR THE OPTIMAL SOLUTION 
536	CHALLENGES OF IMPLEMENTING ADVANCED ANALYTICS IN OIL GAS INDUSTRY
536	THE OIL AND GAS INDUSTRY IS A DATA RICH SECTOR WHERE ADVANCED ANALYTICS CAN UNLOCK SIGNIFICANT VALUE BY IMPROVING OPERATIONAL EFFICIENCY , REDUCING COSTS , AND OPTIMIZING PRODUCTION
536	HOWEVER , IMPLEMENTING ADVANCED ANALYTICS PROJECTS IN THIS INDUSTRY COMES WITH UNIQUE CHALLENGES THAT CAN HINDER THEIR SUCCESS
536	THE PRESENTER WILL DISCUSS MAJOR ISSUES IN SUCH DEPLOYMENTS WITH SUGGESTED SOLUTIONS TO OVERCOME THEM OR REDUCE THEIR IMPACT
536	MANUFACTURING AND SERVICE OPERATIONS MANAGEMENT , MSOM , OPT , MACHINE LEARNING EMERGING TECHNOLOGIES AND APPLICATIONS 
536	THIS IS AN EXPERIENCE FROM APPLYING OR ON PRODUCTION ASSET DATA 
537	COORDINATED GROUND AND AERIAL RESTORATION SCHEDULING FOR POST DISASTER WIRELESS NETWORK
537	DRONE IS AN EMERGING TECHNIQUE PROVIDING EMERGENCY SERVICES TO POST DISASTER WIRELESS NETWORKS
537	IN THIS RESEARCH , WE CONDUCT THE COORDINATED GROUND AND AERIAL RESTORATION SCHEDULING FOR THE POST DISASTER NETWORK , WHICH AIMS TO IDENTIFY THE OPTIMAL DRONE PLACEMENT AND RESTORATION CREW SCHEDULE TO MINIMIZE THE DEPRIVATION COST
537	WE PROPOSE A NEW FORMULATION TO CHARACTERIZE THE SELECTIVE TIME DEPENDENT TRAVELING SALESMAN PROBLEM , AND DEVELOP A STOCHASTIC RESTORATION SCHEDULING OPTIMIZATION PROBLEM BY BUILDING A DECISION DEPENDENT DEMAND PREDICTION MODEL BASED ON THE AVAILABLE COVARIATES IN A DATA DRIVEN SETTING
537	WE CHARACTERIZE THE STRUCTURE OF OPTIMAL DECISION BY STUDYING THE IMPLICATIONS OF CROSS COVERAGE EFFECT AND GROUND AND AERIAL COORDINATION
537	THE EMPIRICAL RESULT ON A REAL WORLD POST DISASTER CASE DEMONSTRATES THE EFFECTIVENESS OF OUR MODEL
537	MANUFACTURING AND SERVICE OPERATIONS MANAGEMENT , MSOM , OPT , OPTIMIZATION UNDER UNCERTAINTY TELECOMMUNICATIONS AND NETWORK ANALYTICS
537	WE BUILD A DECISION DEPENDENT DEMAND PREDICTION MODEL BASED IN A DATA DRIVEN SETTING 
538	DESIGN OF VIRTUAL MANUFACTURING CELLS , AN APPROACH BASED ON ACO AND NEGOTIATION BASED MAS
538	CUSTOMER PROFILES HAVE RAPIDLY CHANGED TOWARD HIGH MIX , LOW VOLUME , HIGH COMPLEXITY PRODUCTS
538	THIS RESEARCH THEREFORE PRESENTS A LEARNING BASED APPROACH TO DESIGN VIRTUAL MANUFACTURING CELLS FOR RECONFIGURABLE MANUFACTURING SYSTEMS
538	DATA FROM THE SHOP FLOOR IS USED TO DYNAMICALLY RE ALLOCATE MACHINES , TOOLS AND FIXTURES AMONG THE CELLS , ACCORDING TO THE CURRENT STATE OF THE SHOP FLOOR
538	MANUFACTURING AND SERVICE OPERATIONS MANAGEMENT , MSOM , OPTIMIZATION , OPT , ARTIFICIAL INTELLIGENCE
538	WE PROPOSE TO USE DATA COLLECTED ON THE SHOP FLOOR TO HAVE AGENT LEARN FROM THEIR ENVIRONMENT 
539	ORDER ROUTING AND PACKING IN COBOT ASSISTED WAREHOUSE OPERATIONS
539	ORDER PICKING IS THE MOST TIME CONSUMING AND COSTLY OPERATION IN THE WAREHOUSE
539	TO IMPROVE PICKING EFFICIENCY WHILE REDUCING INVESTMENT COSTS , COLLABORATIVE ROBOT ASSISTED , ALSO KNOWN AS COBOT , PICKING IS A GOOD CHOICE
539	IN THE COBOT ASSISTED PICKING WAREHOUSES , WE DEVELOPED AN INTEGRATED D BPP , THREE DIMENSIONAL BIN PACKING PROBLEM , AND ROUTING MODEL TO MINIMIZE THE TRAVEL DISTANCE OF THE COBOT
539	TO SOLVE THIS COMPLICATED NP HARD PROBLEM IN POLYNOMIAL TIME , A HYBRID ALGORITHM IS DESIGNED BY EMBEDDING MAXRECTS AND DYNAMIC PROGRAMMING
539	BASED ON THE REAL ORDER DATASET , SOME INSTANCES ARE GENERATED TO CHECK THE EFFECTIVENESS OF THE ALGORITHM
539	THE RESULTS SHOW THAT THE DESIGNED ALGORITHM PERFORMS WELL
539	MANUFACTURING AND SERVICE OPERATIONS MANAGEMENT , MSOM , OPTIMIZATION , OPT , OPT , INTEGER AND DISCRETE OPTIMIZATION
540	AN EFFICIENT MIXED INTEGER LINEAR PROGRAMMING MODEL OF BATCH SIZE AND PRODUCTION FREQUENCY CONSTRAINTS IN MASTER PRODUCTION SCHEDULING
540	MANUFACTURING FIRMS CONSIDER THE BATCH SIZE AND PRODUCTION FREQUENCY IN THE MASTER PRODUCTION SCHEDULING IN ORDER TO AGGREGATE PRODUCTION ORDERS AND AVERAGE RESOURCE LOADING AND WIP LEVELS
540	IN THIS STUDY , WE FORMULATE VARIOUS BATCH SIZE CONSTRAINTS FROM REAL WORLD APPLICATIONS
540	ALSO , WE APPLY COMPACT FORMULATIONS TO REDUCE THE MODEL SIZE OF THE MIXED INTEGER LINEAR PROGRAMMING
540	COMPUTATIONAL EXPERIMENTS USE ACTUAL PROBLEM INSTANCES TO EVALUATE THE EFFECTIVENESS OF PROPOSED MODELS
540	RESULTS SHOW THAT ADDING THE COMPACT BATCH SIZE CONSTRAINTS CAN FULFILL DECISION MAKER REQUIREMENTS AND OBTAIN WELL COMPUTATIONAL PERFORMANCE
540	MANUFACTURING AND SERVICE OPERATIONS MANAGEMENT , MSOM , OPTIMIZATION , OPT , SCHEDULING AND PROJECT MANAGEMENT
541	NONPARAMETRIC ADAPTIVE AGE REPLACEMENT WITH CENSORED DATA
541	WE CONSIDER THE DISTRIBUTION FREE AGE REPLACEMENT PROBLEM WITH CENSORED LIFETIMES
541	WE FIRST DEVELOP A NONPARAMETRIC ADAPTIVE ALGORITHM THAT IS A VARIANT OF THE STOCHASTIC GRADIENT DESCENT METHOD TO MINIMIZE THE EXPECTED NET COST PER MACHINE
541	THEN WE COMBINE THIS ALGORITHM WITH THE KAPLAN MEIER ESTIMATOR TO MINIMIZE THE LONG RUN EXPECTED COST PER UNIT OF TIME
541	MANUFACTURING AND SERVICE OPERATIONS MANAGEMENT , MSOM , QUALITY , STATISTICS AND RELIABILITY MACHINE LEARNING IN OPERATIONS
542	MULTI OBJECTIVE STAFF SCHEDULING FOR RETAIL OPERATIONS
542	STAFF HAPPINESS IS ONE OF THE KEY ISSUES FOR SERVICE QUALITY IN RETAIL SYSTEMS
542	IN CASE OF EXISTENCE OF UNHAPPY STAFF IN A RETAIL STORE , IT WOULD DEFINITELY AFFECT THEIR CUSTOMERS
542	FOR THIS REASON , GENERATION OF SCHEDULES BY CONSIDERING STAFF PREFERENCES IS CRITICAL TO ENSURE STAFF HAPPINESS WITH A BALANCED WORKLOAD
542	THE MAIN AIM OF THIS PAPER IS TO PROPOSE A MULTI OBJECTIVE MIXED INTEGER PROGRAMMING MODEL FOR STAFF SCHEDULING IN RETAIL OPERATIONS
542	THE PROPOSED MODEL TAKES STAFF PREFERENCES AND COMPANY TARGETS INTO ACCOUNT
542	A CASE STUDY FOR A GROSS MARKET IN ANKARA IS PRESENTED TO DEMONSTRATE THE APPLICABILITY OF THE PROPOSED MODEL
542	MANUFACTURING AND SERVICE OPERATIONS MANAGEMENT , MSOM , SERVICE SCIENCE OPT , INTEGER AND DISCRETE OPTIMIZATION
543	CUSTOMER TO MANUFACTURER , SHOULD THE PLATFORM COOPERATE WITH MORE MANUFACTURERS
543	THE CUSTOMER TO MANUFACTURER , C M , MODEL UTILIZES THE E PLATFORM TO TACKLE DISADVANTAGES OF TRADITIONAL PRODUCT MANUFACTURING MODELS IN A LOW COST AND LOW FAILURE MANNER
543	THIS PAPER DEVELOPS AN ANALYTICAL MODEL TO INVESTIGATE THE PLATFORM S COOPERATION STRATEGY AND MANUFACTURERS STRUCTURE PREFERENCES IN A COMPETITIVE ONLINE MARKETPLACE WHERE THE C M OPTIONS ARE OFFERED
543	THIS PAPER FOCUSES ON THE ROLE OF INFORMATION TO UNDERSTAND HOW IT AFFECTS MANUFACTURERS R D EFFORTS AND PROFITS
543	OUR ANALYSIS SHOWS THAT THE MANUFACTURER S EFFORT LEVEL AND EXPECTED PROFIT ARE NOT NECESSARILY MONOTONOUS IN TERMS OF THE AMOUNT OF INFORMATION
543	AND SHARING INFORMATION WITH MULTIPLE MANUFACTURERS IS NOT ALWAYS THE OPTIMAL STRATEGY FOR THE PLATFORM
543	THE KEY POINT BEHIND THIS FACT IS HOW THE PLATFORM BALANCES ITS FUNCTION OF FACILITATING TRANSACTIONS AND THE ROLE OF CONSULTING
543	MANUFACTURING AND SERVICE OPERATIONS MANAGEMENT , MSOM , SHARING ECONOMY , INNOVATIVE MARKETPLACES , AND DATA NEW PRODUCT DEVELOPMENT
543	CONSUMER BIG DATA IS THE ENGINE OF C M 
544	SIMULATION MANUFACTURING OPERATIONS AND CONDITION BASED MAINTENANCE POLICIES TO SUPPORT CONDITION MONITORING TOOL ADOPTION
544	CONDITION MONITORING SYSTEMS , CMSS , CAN IMPROVE MANUFACTURING PERFORMANCE BY HELPING MAINTENANCE DETECT AND DIAGNOSE PRODUCT FAULTS AND MACHINE FAILURES
544	HOWEVER , MEASURING CMS IMPACT ON MANUFACTURING CAN BE DIFFICULT
544	THOUGH CMS ABILITIES CAN BE ASSESSED USING DETECTION OR DIAGNOSIS METRICS AND COMPARED TO MANUFACTURING PERFORMANCE INDICATORS , MANUFACTURING PERFORMANCE ALSO DEPENDS ON THE CONFIGURATION OF MACHINERY AND THE IMPLEMENTED MAINTENANCE POLICY
544	WE DEVELOPED A SIMULATOR TO ANALYZE MANUFACTURING SCENARIOS ACROSS VARIOUS MACHINERY CONFIGURATIONS AND MAINTENANCE POLICIES , EMPHASIZING CMS ENABLED POLICIES
544	WE OBSERVE CMS IMPACT ON MANUFACTURING PERFORMANCE AND CONSIDER HOW MACHINERY CONFIGURATION AND MAINTENANCE POLICY LIMITS OR FACILITATES CMS IMPACT
544	WE ALSO DISCUSS ALIGNING CMS LEVEL METRICS AND MANUFACTURING PERFORMANCE INDICATORS
544	MANUFACTURING AND SERVICE OPERATIONS MANAGEMENT , MSOM , SIMULATION SOCIETY MACHINE LEARNING IN OPERATIONS
544	THE TALK IS ABOUT SIMULATING MANUFACTURING OPERATIONS AND ML TOOLS THAT MONITOR CONDITION DATA 
545	COORDINATION BETWEEN THE Q COMMERCE COMPANY AND DELIVERY RIDERS , A GAME THEORETIC APPROACH
545	Q COMMERCE IS AN EMERGING BUSINESS THAT GREATLY IMPACTS CUSTOMERS BUYING BEHAVIOUR AS THEIR ORDERS ARE DELIVERED IN MINUTES
545	IN THIS STUDY , WE DISCUSS THE CHALLENGES AND ISSUES FACED BY DELIVERY RIDERS AND Q COMMERCE COMPANIES AS FAR AS THE ORDER FULFILMENT OF CUSTOMERS ARE CONCERNED
545	WE DEVELOP A TWO PLAYERS GAME THEORETIC MODEL TO STUDY THE INTERACTION BETWEEN I THE DELIVERY FEES PAID TO THE RIDERS BY THE Q COMMERCE COMPANY I , AND I THE EFFORTS PUT BY BOTH THE PLAYERS THE DELIVERY RIDERS AS WELL AS THE Q COMMERCE COMPANY TOWARDS A SUCCESSFUL DELIVERY I UNDER TWO DIFFERENT SETUPS , I WITH VERSUS WITHOUT PENALTY I 
545	IT DETERMINES THE OPTIMUM DELIVERY FEE AND EFFORTS SO THAT PAYOFFS OF BOTH THE PLAYERS ARE MAXIMIZED
545	THE RESULTS OF THE GAME THEORETIC MODEL PROVIDE VARIOUS MANAGERIAL INSIGHTS THAT MAY LEAD TO BETTER PERFORMANCE FOR BOTH Q COMMERCE COMPANY AND DELIVERY RIDERS
545	MANUFACTURING AND SERVICE OPERATIONS MANAGEMENT , MSOM , SUPPLY CHAIN AND LOGISTICS IN PRACTICE MSOM , SUPPLY CHAIN
545	WE HAVE USED OR TOOL , I E , GAME THEORY , TO STUDY A MS PROBLEM RELATED TO Q COMMERCE BUSINESS 
546	MANAGING INVENTORY IN THE PRESENCE OF LEAD TIME AND DEMAND CORRELATION
546	NUMEROUS STUDIES COMMONLY ASSUME THAT LEAD TIME AND DAILY DEMAND ARE INDEPENDENT
546	IN THIS STUDY , WE RELAX THE ASSUMPTION OF INDEPENDENCE BETWEEN LEAD TIME AND DEMAND IN A CONTINUOUS REVIEW INVENTORY SYSTEM
546	BY ANALYZING THE OPTIMAL ORDERING POLICY , WE COMPARE THE UNCORRELATED AND CORRELATED CASES
546	OUR FINDINGS DEMONSTRATE THAT CONSIDERING THE CORRELATION BETWEEN DEMAND AND LEAD TIME ADDS COMPLEXITY , BUT IT ALSO LEADS TO MORE GENERALIZED AND ROBUST RECOMMENDATIONS
546	MANUFACTURING AND SERVICE OPERATIONS MANAGEMENT , MSOM , SUPPLY CHAIN AND LOGISTICS IN PRACTICE MSOM , SUPPLY CHAIN
547	OPERATION ORIENTED GENERATIVE MODEL OF E COMMERCE ORDERS FOR STOWAGE DECISIONS IN MOBILE FULFILLMENT SYSTEMS
547	THE ROBOTIC MOBILE FULFILLMENT SYSTEM , MFS , PROVIDES OPERATIONAL FLEXIBILITY FOR THE STORAGE OF ENORMOUS AND VOLATILE E COMMERCE ORDERS
547	INSPIRED BY THE TOPIC MODELING IN NATURAL LANGUAGE PROCESSING , WE TREAT INVENTORY PODS CARRYING SKUS AS TOPICS COMPOSED OF WORDS AND INCOMING ORDERS REQUESTING PODS AS DOCUMENTS COMPOSED OF TOPICS
547	WE INTRODUCE POD CAPACITY CONSTRAINTS TO THE GENERATIVE MODEL OF E COMMERCE ORDERS AND SHOW THE RELATIONSHIP BETWEEN THE POD VISIT MINIMIZATION PROBLEM AND THE NEWLY PROPOSED OPERATION ORIENTED GENERATIVE MODEL
547	FURTHERMORE , WE DESIGN AN ONLINE ALGORITHM TO CAPTURE THE DYNAMICS IN ORDER PATTERNS AND VALIDATE OUR MODEL USING A TYPICAL MFS SETTING WITH REAL E COMMERCE ORDERS
547	MANUFACTURING AND SERVICE OPERATIONS MANAGEMENT , MSOM , SUPPLY CHAIN AND LOGISTICS IN PRACTICE OPTIMIZATION , OPT , 
548	GIG WORKERS FOR RELAY NETWORK MODEL , FACTORS TO CONSIDER
548	A RELAY POINT IS A PHYSICAL LOCATION IN THE TRANSPORTATION NETWORK WHERE SHIPMENTS CAN BE RELAYED
548	WE STUDY THE OPTIMAL RELAY NETWORK DESIGN PROBLEM ROBUST TO LABOR , DRIVERS SUPPLY , SHOCKS UNDER A QUEUING FRAMEWORK
548	WE DISCUSS MANAGERIAL INSIGHTS AND FACTORS TO CONSIDER WHILE DESIGNING RELAY NETWORKS WITH SUCH DAILY LEVEL SUPPLY UNCERTAINTIES
548	MANUFACTURING AND SERVICE OPERATIONS MANAGEMENT , MSOM , TRANSPORTATION SCIENCE AND LOGISTICS , TSL , SOCIAL OPERATIONS MANAGEMENT
549	REMOTE WORK ARRANGEMENT AND GENDER INEQUALITY
549	COVID PROMPTED WIDESPREAD ADOPTION OF REMOTE WORK ARRANGEMENTS , RWAS , , NOW CONTINUED BY MANY COMPANIES THIS STUDY INVESTIGATES THE IMPACT OF RWAS ON WORKPLACE GENDER INEQUALITY AND EXPLORES THE MODERATING EFFECTS OF GOVERNMENT WAGE SUBSIDIES AND FEMALE EXECUTIVES
549	BY ANALYZING DETAILED FIRM LEVEL DATA FROM , COMPANIES ACROSS COUNTRIES , OUR STUDY REVEALS THAT RWAS EXACERBATE GENDER INEQUALITY , LEADING TO A SIGNIFICANT DECLINE IN THE PROPORTION OF FEMALE EMPLOYEES AND CONSEQUENT REDUCTION IN FIRM PERFORMANCE
549	HOWEVER , WE FIND THAT GOVERNMENT WAGE SUBSIDIES DURING THE PANDEMIC AND THE PRESENCE OF FEMALE EXECUTIVES MITIGATE THE IMPACT ON GENDER INEQUALITY
549	OUR RESEARCH HIGHLIGHTS THE CASCADING CONSEQUENCES OF THIS OPERATIONAL DECISION FOR COMPANIES , WHILE PROVIDING INSIGHTS FOR BUSINESSES AND POLICYMAKERS ON MITIGATING THESE NEGATIVE IMPACTS
549	MANUFACTURING AND SERVICE OPERATIONS MANAGEMENT , MSOM , WOMEN IN O R MS , WORMS , MSOM , SUSTAINABLE OPERATIONS
550	MANAGING INVENTORIES AND SUPPLIERS IN ASSEMBLY SYSTEMS WITH RANDOM DEMAND AND SUPPLY CAPACITY
550	WE CONSIDER STOCK POSITIONING IN A PURE ASSEMBLY SYSTEM CONTROLLED USING INSTALLATION BASE STOCK POLICIES
550	WHEN COMPONENT SUPPLIERS HAVE RANDOM CAPACITY AND END PRODUCT DEMAND IS UNCERTAIN , WE CHARACTERIZE THE SYSTEM S INVENTORY DYNAMICS
550	WE SHOW THAT COMPONENTS AND THE END PRODUCT PLAY CONVEX COMPLEMENTARY ROLES IN PROVIDING CUSTOMER SERVICE
550	WE PROPOSE A DECOMPOSITION APPROACH THAT USES AN INTERNAL SERVICE LEVEL TO INDEPENDENTLY DETERMINE NEAR OPTIMAL STOCK LEVELS FOR EACH COMPONENT
550	COMPARED WITH THE OPTIMAL , THE AVERAGE ERROR OF THE DECOMPOSITION APPROACH IS ACROSS THE TESTED INSTANCES
550	COMPARED WITH CURRENT PRACTICE , THIS APPROACH HAS THE POTENTIAL TO REDUCE THE SAFETY STOCK COST BY FINALLY , WE ANALYTICALLY SHOW HOW A MULTI ECHELON PURE ASSEMBLY SYSTEM MAY BE CONVERTED INTO AN EQUIVALENT TWO ECHELON ASSEMBLY SYSTEM TO WHICH ALL OUR RESULTS APPLY
550	MANUFACTURING AND SERVICE OPERATIONS MANAGEMENT , MSOM , 
551	OPTIMIZING TOOL PATH DISTANCE IN DRILLING OPERATIONS
551	IN THIS PAPER , WE PRESENT THE USE OF A GENETIC ALGORITHM TO MINIMIZE TOOL PATH DISTANCE IN MULTI TOOL DRILLING NP HARD PROBLEM OPERATIONS
551	MOST OF THE RESEARCH ON HOLE DRILLING PATH OPTIMIZATION FOCUSES ON DRILLING HOLES OF THE SAME DIAMETER , PRIMARILY ADDRESSING SINGLE TOOL PATH PLANNING
551	HOWEVER , OPTIMIZING DRILLING PATHS FOR MULTIPLE HOLE SIZES IN A WORKPIECE INVOLVING MULTI TOOL PATH PLANNING HAS RECEIVED RELATIVELY LESS ATTENTION
551	THIS PAPER PRESENTS AN IMPROVED APPROACH FOR MINIMIZING THE LENGTH OF TOOL PATHS IN MULTI TOOL DRILLING USING A GENETIC ALGORITHM
551	MANUFACTURING AND SERVICE OPERATIONS MANAGEMENT , MSOM , 
552	HOW EMPLOYEE TRAINING DRIVES FIRM PRODUCTION REPURPOSING IN COVID PANDEMIC
552	IN THE COVID PANDEMIC , WE FOUND SOME FIRMS SUCCESSFULLY REPURPOSE PRODUCTION , I E , ADJUSTING FIRM PRODUCTION SERVICES PARTIALLY FULLY , TO ADAPT TO THE PANDEMIC , WHICH MOTIVATES US TO STUDY WHAT FACTORS DRIVES FIRM PRODUCTION REPURPOSING IN COVID PANDEMIC
552	DRAWING UPON THE ABILITY , MOTIVATION AND OPPORTUNITY , AMO , FRAMEWORK , WE STUDY HOW TO LEVERAGE HUMAN CAPITAL , BY EMPLOYEE TRAINING , TO ENHANCE FIRM ADAPTATION , I E , PRODUCTION REPURPOSING , IN THE PANDEMIC
552	THE RESULTS INDICATE THAT EMPLOYEE TRAINING PRIOR TO THE PANDEMIC DEVELOPS HUMAN CAPITAL AND FIRM CAPABILITY TO INITIATE PRODUCTION REPURPOSING DURING THE PANDEMIC
552	GOVERNMENT WAGE SUBSIDY AND LESS LABOR SHORTAGE WILL ENHANCE FIRM MOTIVATION AND OPPORTUNITY RESPECTIVELY IN PRODUCTION REPURPOSING , THUS AMPLIFYING THE POSITIVE IMPACT OF EMPLOYEE TRAINING PRIOR TO THE PANDEMIC
552	MANUFACTURING AND SERVICE OPERATIONS MANAGEMENT , MSOM , 
553	A LARGE SCALE LINEAR PROGRAMMING MODEL TO OPTIMIZE OPERATIONAL EFFICIENCY OF A SEMICONDUCTOR FABRICATION PLANT WITH MULTIPLE LINES
553	DUE TO THE IMMENSE SIZE AND RE ENTRANT FLOW SHOP CHARACTERISTICS OF A SEMICONDUCTOR FABRICATION PLANT , FAB , , IMPROVING EFFICIENCY AND OPTIMIZING PRODUCTIVITY OF A FAB ARE BECOMING EVER MORE IMPORTANT
553	IN THIS PAPER , A MATHEMATICAL MODEL IS PRESENTED TO OPTIMIZE THE OPERATIONAL EFFICIENCY OF A FAB
553	LINEAR PROGRAMMING IS USED TO MODEL A FAB , AND THE PRODUCTION LEVEL IS MAXIMIZED WHILE ACCOUNTING FOR REALISTIC CONSTRAINTS SUCH AS EQUIPMENT ARRANGE AND WORK IN PROCESS
553	THE ROLLING HORIZON METHOD IS UTILIZED TO REDUCE THE COMPUTATION TIME FOR SUCH A LARGE SCALE PROBLEM
553	FOUR EXPERIMENTS ARE CONDUCTED TO TEST THE VALIDITY AND PRACTICALITY OF THE MODEL , AND THE RESULTS OF THE EXPERIMENTS ARE COMPARED TO THE ACTUAL FAB DATA
553	THE ANALYSIS RESULT ALSO SHOWED THAT THE MODEL CAN BE USED FOR DETECTING BOTTLENECKS , WHICH IS AN ADDITIONAL POINT OF IMPROVEMENT FROM A MANAGERIAL PERSPECTIVE
553	MANUFACTURING AND SERVICE OPERATIONS MANAGEMENT , MSOM , 
554	MANAGING SUPPLY CHAINS FACING EXTREME WEATHER
554	RECENTLY , THE RELATIONSHIP BETWEEN A SUPPLIER AND A BUYER HAS BEEN INFLUENCED BY EXTREME WEATHER AND CLIMATE RISKS
554	TO MITIGATE THESE RISKS AND ENSURE CONTINUOUS SUPPLY CHAIN ACTIVITIES , COMPANIES INVEST IN CLIMATE SPECIFIC ASSETS SUCH AS CLIMATE ANALYTICS , TEMPORARY RENTING OF WAREHOUSES AND GENERATORS , ETC
554	THESE FACTORS AND CONVENTIONAL CONTRACT ELEMENTS , SUCH AS COSTS AND RESERVATION PROFITS , INFLUENCE A SUPPLIER S PRICING AND A BUYER S ORDERING DECISIONS
554	WE DEVELOP A DYNAMIC GAME MODEL TO ESTABLISH THE NATURE OF SUPPLIER BUYER INTERACTION AND THE IMPACT OF THE SUPPLIER S NATURE ON THIS INTERACTION DURING AN EXTREME WEATHER EVENT
554	SUBSEQUENTLY , THROUGH EXTENDED ANALYSIS WE DEMONSTRATE THAT WITH A HIGHER POSSIBILITY OF EXTREME WEATHER EVENT , A PROACTIVE SUPPLIER CHARGES HIGHER PER UNIT PRICE TO THE BUYER
554	MANUFACTURING AND SERVICE OPERATIONS MANAGEMENT , MSOM , 
555	EVALUATION OF COMPUTER VISION TECHNIQUES FOR UNMANNED AERIAL VEHICLES , UAVS , 
555	THE UNITED STATES MILITARY HAS UTILIZED UAVS TO PERFORM SURVEILLANCE , SUPPORT , AND OFFENSIVE MISSIONS FOR DECADES
555	ADVANCES IN ARTIFICIAL INTELLIGENCE , AI , HAVE INCREASED THE CAPABILITY OF THESE SYSTEMS TO AUTONOMOUSLY REACT TO CHANGES IN THE ENVIRONMENT
555	HOWEVER , ACCORDING TO A FEBRUARY GOVERNMENT ACCOUNTABILITY OFFICE REPORT , DOD HAS STATED THAT AI SYSTEMS ARE SUSCEPTIBLE TO TRADITIONAL AND NEW METHODS OF CYBERATTACK
555	IN PARTICULAR , THE REPORT NOTED THAT IMAGERY DATA COULD BE ALTERED VIA CYBERATTACKS THAT COULD RENDER THE SYSTEM INEFFECTIVE
555	HENCE , IT IS CRITICAL FOR AUTONOMOUS UAVS TO DISTINGUISH IF AN IMAGE IS DISTORTED BEFORE UTILIZING THAT IMAGE TO REACT
555	THIS PRESENTATION WILL SHOWCASE THE COMPARISON CONVOLUTIONAL NEURAL NETWORKS AND VISUAL TRANSFORMERS IN THEIR ABILITY TO CLASSIFYING IMAGES FROM UAVS AS DISTORTED OR UNDISTORTED
555	MILITARY AND SECURITY ARTIFICIAL INTELLIGENCE AVIATION APPLICATIONS
556	EFFICIENT DYNAMIC THREAT AVOIDANCE ROUTING FOR COMBAT AIRCRAFT IN ADVANCED FRAMEWORK FOR SIMULATION , INTEGRATION , AND MODELING , AFSIM , 
556	SIMULATING PRE PLANNED ROUTES AND DYNAMIC THREAT AVOIDANCE ROUTING REPRESENTS A SIGNIFICANT PROBLEM FOR OPERATIONS ANALYSTS
556	WITHOUT AUTOMATED METHODS TO CREATE OPERATIONALLY VALID ROUTES , THE ANALYST IS FACED WITH HARD CODING INDIVIDUAL ROUTES FOR AIRCRAFT OVER THE ENTIRETY OF THE MISSION SET
556	THIS RESEARCH IMPLEMENTED THREAT AVOIDANCE ROUTING BASED ON DIJKSTRA S ALGORITHM FOR AIRCRAFT ATTEMPTING TO OPERATE IN AN ANTI ACCESS AREA DENIAL ENVIRONMENT CAPABLE OF DYNAMICALLY UPDATING THE MISSION ROUTE AS NEW THREAT INFORMATION IS LEARNED
556	A DESIGNED EXPERIMENT DETERMINED THE IMPACT OF GRID PARAMETERS ON OPERATIONAL EFFECTIVENESS AND COMPUTATIONAL COSTS
556	RESULTS SHOW THAT THE ALGORITHM PRODUCED THE BEST OPERATIONAL PERFORMANCE WITH GRID SPACING SET TO OF THE SMALLEST SURFACE TO AIR MISSILE THREAT RADIUS WITHOUT INCURRING PROHIBITIVE COMPUTATIONAL COSTS
556	MILITARY AND SECURITY AVIATION APPLICATIONS SIMULATION SOCIETY
557	USING INTERPRETABLE AI METHODS TO IDENTIFY RECENT CYBER VULNERABILITIES WITH EXPLOITS
557	WE DESCRIBE THE IMPORTANCE OF FINDING SUPER CRITICAL VULNERABILITIES RELATING TO THE RACE BETWEEN HACKERS AND DEFENDERS
557	ALSO , THE FEATURES THAT PREDICT THE EXISTENCE OF EXPLOITS AND ALTERNATIVE APPROACH ARE DESCRIBED
557	THEN , WE SHOW HOW OPTIMAL CLASSIFICATION TREES BASED ON A SAMPLING SCHEME SUPPORT INSIGHTS AND BOUNDING ON A LARGE DATASET
557	MILITARY AND SECURITY INFORMATION SYSTEMS COMPUTING SOCIETY
558	DEVELOPING AN UNDERGRADUATE PROGRAM IN NAVY ENGINEERING ANALYTICS
558	THANKS TO FUNDING FROM THE OFFICE OF NAVAL RESEARCH , IOWA STATE UNIVERSITY , ISU , IS LAUNCHING A NAVY ENGINEERING ANALYTICS PROGRAM , NEAP , FOR UNDERGRADUATE STUDENTS
558	THE OBJECTIVE OF NEAP IS TO DEVELOP AN INNOVATIVE EDUCATION AND TRAINING PROGRAM THAT TEACHES ANALYTICAL SKILLS TO SOLVE NAVY AND DEFENSE PROBLEMS
558	THE GOAL OF NEAP IS TO PROVIDE UNDERGRADUATE ENGINEERING STUDENTS WITH THE NECESSARY ANALYTICAL SKILLS SO THAT THEY CAN ENTER INTO EXCITING PROFESSIONS IN THE NAVY AND THE BROADER DEFENSE COMMUNITY
558	NEAP IS CURRENTLY COMPOSED OF FOUR COURSES , , I , CRISIS DECISION MAKING AND RISK MANAGEMENT , , II , DESIGN AND EVALUATION OF HUMAN COMPUTER INTERACTION , , III , PROBLEM SOLVING USING R , AND , IV , A PROJECT BASED COURSE IN WHICH STUDENTS WORK ON DEFENSE SPONSORED PROJECTS
558	NEAP HAS AWARDED STUDENTS WITH SCHOLARSHIPS FOR MILITARY AND SECURITY INFORMS COMMITTEE ON TEACHING AND LEARNING AND EDUCATION OUTREACH 
558	SOME OF THE COURSES TEACH STUDENTS HOW TO USE DATA TO SOLVE NAVY AND DEFENSE PROBLEMS 
559	A STOCHASTIC GAME FRAMEWORK FOR PATROLLING A BORDER
559	WE CONSIDER A STOCHASTIC GAME FOR MODELLING THE INTERACTIONS BETWEEN SMUGGLERS AND A PATROLLER ALONG A BORDER
559	THE PROBLEM WE EXAMINE IS A GROUP OF COOPERATING SMUGGLERS MAKING REGULAR ATTEMPTS AT BRINGING SMALL AMOUNTS OF ILLICIT GOODS ACROSS A BORDER
559	A SINGLE PATROLLER HAS THE GOAL OF PREVENTING THE SMUGGLERS FROM DOING SO , BUT MUST PAY A COST TO TRAVEL FROM LOCATION TO LOCATION
559	WE HAVE PROVEN A NUMBER OF PROPERTIES OF THE NASH EQUILIBRIA IN THE GAME THAT LEAD TOWARDS NEW METHODS OF CALCULATING THEM
559	THE METHODS WE HAVE DEVELOPED ARE THEN SIGNIFICANTLY MORE COMPUTATIONALLY EFFICIENT THAN EXISTING GENERAL WAYS TO FIND NASH EQUILIBRIA IN OUR MODEL
559	WE EXPLORE HOW PARAMETERS SUCH AS THE PENALTIES APPLIED TO THE SMUGGLERS BY THE PATROLLER AND TOPOLOGY OF THE BORDER CAN AFFECT THE PATROLLER S STRATEGY
559	MILITARY AND SECURITY 
560	EFFECTS OF LAWSUIT ON SUPPLY CHAIN STRUCTURE 
560	THE PURPOSE OF THIS STUDY IS TO EMPIRICALLY ANALYZE WHETHER A CLASS ACTION LAWSUIT CAN HAVE AN IMPACT ON THE SUPPLY CHAIN STRUCTURE
560	CLASS ACTION LAWSUITS INVOLVE A GROUP OF INDIVIDUALS WITH A COMMON INTEREST HOLDING A COMPANY LEGALLY ACCOUNTABLE
560	WHEN A COMPANY FACES A LAWSUIT , IT INCURS HIGH COSTS , WHICH CAN INDIRECTLY AFFECT OTHER COMPANIES IN THE SUPPLY CHAIN
560	SPECIFICALLY , IF A SUPPLIER IS SUED , IT IS LIKELY TO CAUSE CHANGES IN THE SALES STRUCTURE OF BOTH THE SUPPLIER AND THE CUSTOMER COMPANIES WITHIN THE SUPPLY CHAIN
560	FURTHERMORE , IT IS ANTICIPATED THAT LAWSUITS AGAINST A SUPPLIER CAN INDIRECTLY IMPACT THE SUPPLY CHAIN STRUCTURE OF OTHER SUPPLIERS WHO SHARE THE SAME CUSTOMERS
560	THIS STUDY AIMS TO PROVIDE SIGNIFICANT INSIGHTS INTO THE EXISTING LITERATURE THROUGH THE EXAMINATION OF THE INFLUENCE OF LAWSUITS ON THE SUPPLY CHAIN STRUCTURE
560	MINORITY ISSUES FORUM FINANCE MSOM , SUPPLY CHAIN
561	CONTROLING APPOINTMENT SCHEDULES , HOW AND WHEN TO INTERVENE
561	TRADITIONALLY , APPOINTMENT SCHEDULES HAVE BEEN DETERMINED BY MINIMIZING A SPECIFIC COST FUNCTION CONSISTING OF CLIENTS WAITING TIMES AND SERVER IDLING
561	THESE SCHEDULES ARE OFTEN STUDIED IN A STATIC SENSE , ONCE ANNOUNCED NO FURTHER UPDATES WILL FOLLOW
561	HOWEVER , ADVANCEMENTS IN TECHNOLOGY HAVE OPENED UP THE POSSIBILITY OF COMMUNICATING WITH UPCOMING CLIENTS , WHICH CAN LOWER COSTS
561	YET , EXCESSIVE UPDATES MAY CAUSE CONFUSION AND FRUSTRATION AMONG CLIENTS
561	IN THIS STUDY , WE CONSIDER HOW MANY UPDATES ONE SHOULD SEND AND WHAT ARE THE IDEAL MOMENTS TO SEND THESE UPDATES
561	ON THE OPERATIONAL LEVEL , THE FINDINGS HAVE BROAD APPLICATIONS IN THE MANAGEMENT OF APPOINTMENT SCHEDULING
561	MSOM , HEALTHCARE APPLIED PROBABILITY OPT , OPTIMIZATION UNDER UNCERTAINTY
562	A PRECISE NURSING TRAINING SYSTEM INTEGRATING CONVERSATIONAL ARTIFICIAL INTELLIGENCE AND MIXED REALITY
562	USING MIXED REALITY TECHNOLOGY , WE HAVE DEVELOPED A NURSING TRAINING SYSTEM THAT CREATES SCENARIOS WITH DIFFERENT DIGITAL PATIENTS AND SYMPTOMS , ALLOWING NURSES TO PRACTICE INTERACTIONS WITH DIGITAL PATIENTS IN A SAFE , CONTROLLED , AND REALISTIC ENVIRONMENT
562	IN ADDITION , THE SYSTEM IS AUGMENTED WITH A CONVERSATIONAL ARTIFICIAL INTELLIGENCE , AI , MODEL THAT ALLOWS THE NURSE TO HAVE REGULAR CONVERSATIONS WITH A DIGITAL PATIENT TO PRACTICE COMMUNICATION AND EMPATHIC SKILLS , AS WELL AS TO LEARN HOW TO PROVIDE APPROPRIATE CARE AND TREATMENT
562	IN THIS WORK , WE DELVE DEEPER INTO OUR CONVERSATIONAL AI MODEL AND THE NATURAL LANGUAGE PROCESSING METHODS TO IMPROVE LANGUAGE COMPREHENSION , INCLUDING TEXT CLASSIFICATION USING FEED FORWARD AND CONVOLUTIONAL NETWORKS , PART OF SPEECH TAGGING USING MAXIMUM ENTROPY MARKOV MODELS , AND LOCAL AND GLOBAL MODELS FOR DEPENDENCY PARSING
562	MSOM , HEALTHCARE ARTIFICIAL INTELLIGENCE MACHINE LEARNING IN OPERATIONS
563	SOCIAL MEDIA ADDICTION , ITS EFFECTS ON ADDICTS , AND ITS RELEVANCE TO BUSINESSES , A LITERATURE REVIEW
563	WE TRY TO UNDERSTAND HOW INDIVIDUALS SOCIAL MEDIA ADDICTION RELATES TO BUSINESS STRATEGIES
563	WE ANALYZE SCHOLARLY JOURNAL ARTICLES TO CLASSIFY THE VICTIMS OF THIS ADDICTION BASED ON DIMENSIONS SUCH AS DEMOGRAPHICS , SEXUAL ORIENTATION , TECHNOSTRESS , AND SOCIAL CAPITAL
563	WE IDENTIFY THE EFFECTS OF THIS ADDICTION ON ONE S CONTENTMENT , JOB PERFORMANCE , ACHIEVEMENTS , COMMUNITY ENGAGEMENT , SENSE OF BELONGING , HABITS , FATIGUE , ANXIETY , DEPRESSION , EMOTIONS , AND WELLBEING
563	WE IDENTIFY BUSINESSES THAT ARE BENEFICIARIES OF INDIVIDUALS ADDICTIVE USE OF SOCIAL MEDIA AND GENERATE RELEVANT HYPOTHESES
563	MSOM , HEALTHCARE BEHAVIORAL OPERATIONS MANAGEMENT HEALTH APPLICATIONS SOCIETY EFFECTS OF DATA REVOLUTION ON PUBLIC HEALTH PROBLEMS SUCH AS ADDICTION 
564	REINVENTING WEIGHT LOSS STRATEGIES , UNLEASHING THE POTENTIAL OF SMART DINNER TIMING 
564	MEDICAL RESEARCH HAS SHOWN THE POSITIVE EFFECTS OF LONGER FASTING PERIODS ON WEIGHT LOSS , AS IT EXHAUSTS SUGAR STORES IN HUMAN BODY AND STARTS BURNING FAT
564	CONSEQUENTLY , MANY INDIVIDUALS ADOPT THE PRACTICE OF HAVING AN EARLY DINNER TO RESTRICT THEIR EATING WINDOW
564	CHALLENGING THIS CONVENTIONAL BELIEF , THE AUTHOR REVEALS THAT WHEN HAVING LUNCH AFTER NOON , DELAYING DINNER TIME CAN REDUCE DAILY CALORIE INTAKE EFFECTIVELY
564	OUR ANALYSIS REVOLVES AROUND A COMPREHENSIVE DATA SET OF OFFICE WORKERS PURCHASING BEHAVIORS AT THE CAFETERIA
564	FOCUSING ON EMPLOYEES WHO HAVE LUNCH AFTER P M , WE FIND THAT AS THE INTERVAL BETWEEN DINNER AND LUNCH INCREASES , DAILY CALORIE INTAKE DECLINES , WHICH IMPLIES THE IMPORTANCE OF MANAGING DINNER TIME SMARTLY RATHER THAN SIMPLY EATING DINNER EARLY
564	ULTIMATELY , THESE RESULTS OFFER INSIGHTS FOR ACHIEVING WEIGHT LOSS AND PROMOTING HEALTH
564	MSOM , HEALTHCARE HEALTH APPLICATIONS SOCIETY BEHAVIORAL OPERATIONS MANAGEMENT
565	THE EFFECT OF PANEL COMPOSITION ON THE PERFORMANCE OF HEALTHCARE APPOINTMENT SYSTEMS
565	THE PAPER STUDIES HOW PANEL DESIGN STRATEGIES AFFECT OPERATION PERFORMANCE UNDER DIFFERENT APPOINTMENT POLICIES
565	SPECIFICALLY , WE EXAMINE APPOINTMENT SYSTEMS COMMONLY STUDIED IN THE LITERATURE UNDER DIFFERENT PATIENT PANEL SETTINGS
565	THE STUDY AIMS TO HIGHLIGHT THE POTENTIAL OPPORTUNITIES FOR BETTER OUTCOMES WHEN LONG TERM STRATEGIC AND SHORT TERM OPERATIONS DECISIONS ARE SIMULTANEOUSLY CONSIDERED
565	MSOM , HEALTHCARE HEALTH APPLICATIONS SOCIETY MSOM , SERVICE OPERATIONS
566	PERSONALIZED STATIN TREATMENT PLAN USING COUNTERFACTUAL PREDICTION AND OPTIMIZATION
566	STATINS ARE A CLASS OF DRUGS THAT LOWER CHOLESTEROL LEVELS IN THE BLOOD
566	HIGH CHOLESTEROL LEVELS CAN CAUSE ATHEROSCLEROTIC CARDIOVASCULAR DISEASE , ASCVD , 
566	STATINS CAN REDUCE THE RISK OF ASCVD EVENTS WHILE THEY MIGHT BE ASSOCIATED WITH SYMPTOMS SUCH AS MUSCLE PAIN , ETC
566	THIS LEADS TO A STRONG REASON TO DISCONTINUE STATIN THERAPY , WHICH INCREASE THE RISK OF CARDIOVASCULAR EVENTS AND MORTALITY
566	TO SOLVE THIS PROBLEM , WE PROPOSED A FRAMEWORK TO PRODUCE A PROACTIVE STRATEGY , CALLED A PERSONALIZED STATIN TREATMENT PLAN , PSTP , USING OVERLAP WEIGHTING COUNTERFACTUAL PREDICTION , TO MINIMIZE THE RISKS OF STATIN ASSOCIATIVE SYMPTOMS , SAS , AND RISK OF DISCONTINUATION , AND MAXIMIZING LDL C REDUCTION I I 
566	MSOM , HEALTHCARE HEALTH APPLICATIONS SOCIETY OPTIMIZATION , OPT , 
567	MANAGING CAPACITY RESERVATION FOR LOW PRIORITY STRATEGIC PATIENTS
567	WE STUDY A HEALTHCARE SYSTEM THAT OPERATES TWO PARALLEL TRACKS , I E , A SHARED TRACK AND A DEDICATED TRACK , TO SERVE TWO PRIORITY CLASSES OF PATIENTS
567	HIGH PRIORITY PATIENTS ARE ASSIGNED TO THE DEDICATED TRACK FOR PROMPT SERVICE FOLLOWING A FCFS PRINCIPLE
567	WHEN THE DEDICATED TRACK IS RELATIVELY BUSY , HIGH PRIORITY PATIENTS ARE DIVERTED TO THE SHARED TRACK WITH A NON PREEMPTIVE PRIORITY OVER LOW PRIORITY PATIENTS
567	LOW PRIORITY PATIENTS ARE STRATEGIC , AND THEY CHOOSE TO JOIN THE WAITING QUEUE ON THE SHARED TRACK , OR TO BALK FROM THE SYSTEM
567	THEIR JOIN OR BALK DECISION IS MADE BASED ON THE UTILITY OF JOINING AFTER OBTAINING DELAY INFORMATION
567	IN OUR STUDY , WE CONSIDER TWO TYPES OF EXPECTED WAITING TIME INFORMATION TO BE REVEALED TO LOW PRIORITY PATIENTS , LONG TERM EXPECTED WAITING TIME , AND REAL TIME EXPECTED WAITING TIME
567	MSOM , HEALTHCARE HEALTH APPLICATIONS SOCIETY 
568	PATIENT APPOINTMENT SCHEDULING AT HEMODIALYSIS CENTERS , AN EXACT BRANCH AND PRICE APPROACH
568	SCHEDULING PATIENT APPOINTMENTS AT A HEMODIALYSIS CENTER IS A UNIQUE CHALLENGE , UNLIKE OTHER HEALTHCARE APPOINTMENT SCHEDULING PROBLEMS
568	PATIENTS REQUIRE A SERIES OF DIALYSIS TREATMENT SESSIONS RATHER THAN A SINGLE APPOINTMENT
568	WE FORMULATE THIS MULTIPLE APPOINTMENT SYSTEM AS A SET PARTITIONING MODEL AND SOLVE IT USING A BRANCH AND PRICE ALGORITHM
568	SINCE DYNAMIC PROGRAMMING DOESN T PERFORM VERY WELL FOR SOLVING THE PRICING SUBPROBLEM , WE FURTHER DECOMPOSE IT AND SOLVE IT USING A NOVEL COLUM GENERATION BASED APPROACH
568	ADDITIONALLY , WE DESIGN A GREEDY HEURISTIC TO IMPROVE THE COMPUTATIONAL EFFICIENCY OF THE ALGORITHM
568	MSOM , HEALTHCARE HEALTH APPLICATIONS SOCIETY 
569	PHARMACEUTICAL COMPETITION WITH RISK SHARING , A GAME THEORETIC PERSPECTIVE
569	WE STUDY THE USE OF RISK SHARING AGREEMENTS BY PHARMACEUTICAL COMPANIES TO ESTABLISH MARKET SHARE IN AN OLIGOPOLISTIC MARKET
569	WE ANALYZE THE COMPETITION BETWEEN AN INCUMBENT DRUG MANUFACTURER AND A MARKET ENTRANT THAT MAY ENCROACH THE MARKET USING RISK SHARING AGREEMENTS TO INCREASE ITS MARKET COVERAGE
569	IN RESPONSE TO THE ENTRY OF THE NEW DRUG , THE INCUMBENT MAY ALSO ADJUST ITS PRICE OR INTRODUCE RISK SHARING AGREEMENTS
569	WE FIND THAT PRICE REDUCTION BY THE INCUMBENT CAN BE A BETTER RESPONSE BY THE INCUMBENT WHEN THERE IS A COST ASSOCIATED WITH THE IMPLEMENTATION OF A RISK SHARING AGREEMENT
569	MSOM , HEALTHCARE MANUFACTURING AND SERVICE OPERATIONS MANAGEMENT , MSOM , 
570	POOLING AND ASSORTMENT IN HEALTHCARE SYSTEM WITH TELEMEDICINE
570	TELEMEDICINE SERVICES ENABLE THE REMOTE DELIVERY OF HEALTHCARE AND INFORMATION VIA TELECOMMUNICATIONS TECHNOLOGY , WHICH HAS THE POTENTIAL TO INCREASE ACCESS TO AND THE QUALITY OF HEALTHCARE SERVICES IN RURAL COMMUNITIES
570	IN MANY HEALTHCARE SYSTEMS , CENTRAL HOSPITALS ALLOCATE A PORTION OF THEIR MEDICAL STAFF TO PROVIDE TELEMEDICINE CARE FOR CRITICALLY ILL PATIENTS IN REMOTE REGIONS
570	THIS PAPER EXAMINES HOW THE INTEGRATION OF TELEMEDICINE MAY AFFECT HEALTHCARE ACCESS FOR PATIENTS IN BOTH URBAN AND RURAL AREAS AND HOW CENTRAL HOSPITALS CAN MAKE EFFECTIVE DECISIONS REGARDING THE ALLOCATION OF MEDICAL RESOURCES BETWEEN ONLINE AND OFFLINE CARE
570	THE AIM OF THIS STUDY IS TO ASSESS THE POTENTIAL BENEFITS OF TELEMEDICINE AND PROVIDE VALUABLE INSIGHTS FOR HEALTHCARE POLICYMAKERS AND PRACTITIONERS
570	MSOM , HEALTHCARE MSOM , SERVICE OPERATIONS EMERGING TECHNOLOGIES AND APPLICATIONS 
570	TELEMEDICINE RELIES HEAVILY ON THE USE OF DATA AND TECHNOLOGY
571	MANAGING PATIENT SAFETY CULTURE FOR HEALTHCARE ORGANIZATIONS , AN EXPLORATORY STUDY WITH CORRESPONDENCE ANALYSIS AT CHENG CHING GENERAL HOSPITAL
571	WE INVESTIGATE THE RELATIONSHIPS THAT THE VARIOUS SAFETY CHARACTERISTICS HAVE WITH GENDER , AGE , AND WORKPLACE OF MEDICAL STAFF IN RELATION TO PATIENT SAFETY CULTURE
571	AN EXPLORATORY STUDY WAS PERFORMED BY USING THE CORRESPONDENCE ANALYSIS WITH NINE PATIENT SAFETY CHARACTERISTICS FROM THE CHINESE VERSION OF SAQ , SAFETY ATTITUDE QUESTIONNAIRE , 
571	THE RESULTS SHOWED HOSPITAL MANAGEMENT SUPPORT FOR PATIENT SAFETY , TEAMWORK ACROSS HOSPITAL UNITS , AND HOSPITAL HANDOFFS AND TRANSITIONS SHOWED SIGNIFICANT RELATIONSHIPS WITH THE GENDER AND AGE OF EMPLOYEES , WHILE SAFETY CLIMATE , STRESS RECOGNITION , HOSPITAL MANAGEMENT SUPPORT FOR PATIENT SAFETY , AND TEAMWORK ACROSS HOSPITAL UNITS RESULTED IN SIGNIFICANT RELATIONSHIPS WITH THE WORKPLACE AND AGE OF EMPLOYEES
571	WE PROVIDE SOME IMPLICATIONS TO IMPROVE THE PATIENT SAFETY CULTURE OF AN ORGANIZATION
571	MSOM , HEALTHCARE MSOM , SERVICE OPERATIONS HEALTH APPLICATIONS SOCIETY
571	USING HEALTHCARE DATA TO IMPROVE SAFETY CULTURE 
572	THE EFFECT OF THE CLINICAL AND NON CLINICAL PRACTICES ON MORTALITY RATE
572	AN ECONOMETRIC ANALYSIS
572	PHYSICIANS BELIEVE IN LINKING RESULTS TO ONLY THE CLINICAL TREATMENT WITH LITTLE TO NO TENDENCY TO BELIEVE IN ANYTHING OTHER THAN THE CLINICAL TREATMENT , TONELLI , , OUR STUDY INVESTIGATES THE EFFECT OF THE CLINICAL AND NON CLINICAL CARE ON MORTALITY RATE USING LONGITUDINAL DATA FROM ALL US ACUTE CARE HOSPITALS
572	MSOM , HEALTHCARE MSOM , SERVICE OPERATIONS SERVICE SCIENCE 
573	A STUDY ON POLICY DECISIONS TO EMBED FLEXIBILITY IN THE PLANNING AND SCHEDULING IN OPERATING ROOMSCONSIDERING MULTIPLE RESOURCE STAGES IN THE OPERATING ROOM
573	THE ENDEAVOR FOR OPERATIONAL EXCELLENCE IN THE OPERATING ROOM , OR , DEPARTMENT IS HAMPERED BY UNCERTAINTY UNDERLYING PATIENT DEMAND FOR HEALTHCARE RESOURCES
573	INCORPORATING THIS UNCERTAINTY IS COMPLICATED SINCE PLANNING AND SCHEDULING DECISIONS ARE ORGANIZED ACCORDING TO A HIERARCHICAL DECISION STRUCTURE IN DIFFERENT PHASES
573	IN THIS STUDY , WE LINK THE STRATEGIC , TACTICAL , AND OPERATIONAL DECISION MAKING IN THE OR DEPARTMENT AND STUDY THE IMPACT OF POLICY DECISIONS EMBEDDING FLEXIBILITY IN THE OR PLANNING AND SCHEDULING PROCESSES TO IMPROVE THE OPERATIONAL OUTCOME , MAKING THE TRADE OFF BETWEEN EFFICIENCY AND CONSISTENCY
573	WE CONSIDER A SEQUENTIAL BUT INTERRELATED PROACTIVE REACTIVE DECISION FRAMEWORK THAT IS GUIDED BY BOTH GENERIC ASSUMPTIONS FROM LITERATURE AND REAL LIFE
573	ANALYSIS IS PERFORMED VIA COMPUTATIONAL EXPERIMENTATION ON A REAL LIFE DATASET
573	MSOM , HEALTHCARE OPT , INTEGER AND DISCRETE OPTIMIZATION OPT , COMPUTATIONAL OPTIMIZATION AND SOFTWARE
574	PREDICTION OF CARDIOVASCULAR MORTALITY IN NASH LIVER TRANSPLANT RECIPIENTS USING MACHINE LEARNING
574	CARDIOVASCULAR DISEASE , CVD , IS THE LEADING CAUSE OF MORTALITY AMONG NON ALCOHOLIC STEATOHEPATITIS , NASH , PATIENTS WHO UNDERWENT LIVER TRANSPLANTS
574	THEREFORE , EARLY IDENTIFICATION OF CVD PATIENTS IS CRUCIAL FOR TIMELY INTERVENTION AND PREVENTION OF ADVERSE OUTCOMES
574	IN THIS STUDY , A MACHINE LEARNING , ML , MODEL WAS DEVELOPED TO PREDICT THE RISK OF CARDIOVASCULAR DEATH AMONG , NASH PATIENTS BETWEEN AND LOGISTIC REGRESSION , LR , , RANDOM FOREST , RF , , DECISION TREE , DT , , AND XGBOOST , XGB , AS ESTIMATORS FOR RFE AND SFM WERE ALL APPLIED IN THE STUDY
574	ADDITIONALLY , PREDICTION MODELS WERE DEVELOPED USING SUPPORT VECTOR MACHINE , SVM , , RF , AND XGB
574	RESULTS SHOWED THAT THE BEST PREDICTION MODEL WAS XGB WITH APPLYING SFM DT FEATURES
574	MSOM , HEALTHCARE OPT , MACHINE LEARNING 
575	INTEGER PROGRAMMING FOR SURGERY SCHEDULING UNDER UNCERTAINTY
575	FLEXIBLE OPERATING ROOMS CAN BE USED FOR SCHEDULED ELECTIVE SURGERIES AND RANDOMLY ARRIVING EMERGENCY SURGERIES , BOTH WITH UNCERTAIN DURATIONS
575	THE SCHEDULING PROBLEM WE DEAL WITH CONSISTS OF ASSIGNING GIVEN ELECTIVE SURGERIES TO OPERATING ROOMS AND DETERMINING THEIR START TIMES TO MINIMIZE THE SUM OF THE ROOM ASSIGNMENT COST AND THE EXPECTED COST ASSOCIATED WITH DELAYS OR CANCELLATIONS OF SURGERIES AND WITH IDLE OR OVERTIME
575	WE FORMULATE THIS PROBLEM AS A TWO STAGE MIXED INTEGER LINEAR PROGRAM , TO TACKLE INSTANCES OF REALISTIC SIZE AND COMPLEXITY , WE PROPOSE A CORRESPONDING MATHEURISTIC
575	MSOM , HEALTHCARE OPT , OPTIMIZATION UNDER UNCERTAINTY SCHEDULING AND PROJECT MANAGEMENT
576	CAPACITY PLANNING FOR EMERGENCY TELEMEDICINE
576	THIS RESEARCH FOCUSES ON THE CAPACITY MANAGEMENT PLANNING FOR A TELEMEDICINE ORGANIZATION THAT PROVIDES SERVICES FOR STROKE PATIENTS , WITH OPERATING SYSTEM WHERE PHYSICIANS REMOTELY ATTEND TO PATIENTS LOCATED IN THE HOSPITAL EMERGENCY WARD
576	A NOVEL LINEARIZED INTEGER PROGRAMMING MODEL IS PROPOSED WHICH CONSIDERS THE HIRING , LICENSING AND HOSPITAL CREDENTIALING OF PHYSICIANS , WITH THE AIMS TO MINIMIZING TOTAL COSTS ASSOCIATED WITH THE CAPACITY
576	MSOM , HEALTHCARE OPTIMIZATION , OPT , SUPPLY CHAIN AND LOGISTICS IN PRACTICE
577	SURVIVAL OPTIMIZATION MODELS FOR CARDIAC ARRESTS
577	OUT OF HOSPITAL CARDIAC ARREST , OHCA , IS A SIGNIFICANT PUBLIC HEALTH ISSUE AND A LEADING CAUSE OF DEATH AMONG ADULTS IN THE UNITED STATES
577	THIS STUDY PROPOSES NEW SURVIVAL OPTIMIZATION MODELS IN WHICH THE OBJECTIVE FUNCTION IS THE MAXIMIZATION OF THE PROBABILITY OF SURVIVAL TO AN OHCA
577	MSOM , HEALTHCARE OPTIMIZATION , OPT , 
578	PARAMETER ESTIMATION OF COVID DYNAMICS CONSIDERING PUBLIC POLICIES , EPIDEMIC MODELING AND NONLINEAR OPTIMIZATION
578	THE GOAL OF THIS STUDY IS TO MODEL THE COVID OUTBREAK WITH EPIDEMIC MODELING , CONSIDERING THE NON PHARMACEUTICAL EFFECTS
578	TO ACHIEVE THIS GOAL , THIS STUDY DEVELOPS A NONLINEAR OPTIMIZATION PROBLEM TO DETERMINE THE PARAMETERS FOR A SUSCEPTIBLE EXPOSED INFECTED RECOVERED DECEASED MODEL
578	PARTICULARLY , THE STUDY INCORPORATES A DYNAMIC VARIABLE IN ESTIMATING THE TRANSMISSION RATE AND DETERMINES THE OPTIMAL PARAMETERS USING GRID SEARCH TO MINIMIZE THE LEAST SQUARED ERRORS IN FITTING EMPIRICAL DATA COLLECTED BY THE CENTERS FOR DISEASE CONTROL AND PREVENTION
578	THE ANALYTICAL FINDINGS HAVE THE POTENTIAL TO AID HEALTHCARE POLICYMAKERS BY PROVIDING INSIGHTS INTO THE CORONAVIRUS DYNAMICS AND OFFERING A QUANTIFIED EVALUATION OF PUBLIC POLICIES
578	MSOM , HEALTHCARE PANDEMIC MANAGEMENT MSOM , SUSTAINABLE OPERATIONS
578	IT INCORPORATES A DYNAMIC VARIABLE TO REFLECT DATA REVOLUTION 
579	INVENTORY RATIONING DURING A PANDEMIC , MODEL AND APPLICATIONS
579	THE AVAILABILITY OF REAL TIME DATA SHOWING DYNAMIC REGIONAL HEALTHCARE NEEDS SKYROCKETED DURING THE PANDEMIC , WITH SEVERAL LARGE ORGANIZATIONS PROVIDING THE DATA FOR FREE AND IN MANY FORMS
579	AS SUCH , BETTER INFORMED INVENTORY RATIONING DECISIONS BECAME POSSIBLE AT A HIGHER LEVEL THAN EVER BEFORE
579	DURING THE COVID PANDEMIC , SEVERAL INSTANCES OF RATIONING OCCURRED IN THE US HEALTHCARE SYSTEM
579	WE PRESENT A MODEL THAT TAKES INTO ACCOUNT MULTIPLE RATIONING CLASSES IN A HEALTHCARE ENVIRONMENT USING SIMULATION OPTIMIZATION , WHERE PARAMETERS CAN BE DERIVED FROM NEAR REAL TIME , OPENLY AVAILABLE HEALTHCARE DATA
579	WE ALSO PROVIDE A SIMPLIFIED MODEL THAT PERFORMS WELL IN REAL WORLD SETTINGS AND ALLOWS FOR APPLIED CUSTOMIZATION UNDER DIFFERENT GOVERNING POLICIES
579	MSOM , HEALTHCARE PANDEMIC MANAGEMENT OPT , OPTIMIZATION UNDER UNCERTAINTY
579	WE PRESENT A RATIONING MODEL THAT RELIES ON WIDELY AVAILABLE HEALTH DATA PREVALENT DURING COVID 
580	OPTIMIZING A TWO STAGE GENETIC MANUFACTURINGSYSTEM WITH MARKOV DECISION PROCESS
580	SYNTHETIC BIOLOGY AND GENETIC ENGINEERING ARE CRUCIAL IN BIOTECHNOLOGY
580	GENETIC MANUFACTURING SYSTEMS , GMS , STREAMLINE GENETIC CONSTRUCT PRODUCTION
580	INSPECTIONS ENSURE HIGH QUALITY OUTPUTS
580	THIS STUDY MODELS GMS USING A MARKOV DECISION PROCESS , ADDRESSING MULTISTAGE INSPECTION ALLOCATION
580	IT EXAMINES HOW GMS CHARACTERISTICS AFFECT OPTIMAL INSPECTION STRATEGIES
580	THE MATHEMATICAL MODEL AIDS IN DESIGNING OPTIMAL INSPECTION STRATEGIES FOR GMS
580	THESE FINDINGS OPTIMIZE HIGH QUALITY GENETIC CONSTRUCT PRODUCTION , BENEFITING PROFESSIONALS IN SYNTHETIC BIOLOGY
580	MSOM , HEALTHCARE QUALITY , STATISTICS AND RELIABILITY OPTIMIZATION , OPT , 
581	MINIMIZING UNDERSTAFFING COSTS FOR CHIEF RESIDENTS IN MEDICAL RESIDENCY UNDER UNCERTAIN ATTRITION
581	IN THIS PAPER WE PRESENT STOCHASTIC OPTIMIZATION MODELS FOR PROGRAM DIRECTORS , PDS , OF MEDICAL RESIDENCY PROGRAMS TO ANNUALLY DECIDE ON ALLOCATION OF RESIDENTS BETWEEN SENIOR LEVEL CLINICAL STAGES AND RESEARCH TRACK TO CONSIDER ATTRITION UNCERTAINTY ANALYTICALLY
581	OUR MODEL MINIMIZES UNDERSTAFFING COSTS DUE TO DEFICIENCY FROM THE TARGETED NUMBER OF GRADUATES AND THE AFFINITY OF THE RESIDENTS TOWARDS RESEARCH
581	MSOM , HEALTHCARE SERVICE SCIENCE APPLIED PROBABILITY 
582	IMPACTS OF STAFF COLLABORATIONS ON THE SERVICE TIME FOR INPATIENT STAYS , AN ANALYSIS USING EHR AUDIT LOGS AND DYNAMIC GRAPHS
582	IN THIS STUDY , WE INVESTIGATE THE IMPACTS OF COLLABORATION BETWEEN TEAMS OF CARE PROVIDERS IN HEALTHCARE ORGANIZATIONS ON THE SERVICE TIME FOR INPATIENT STAYS
582	USING DATA FROM EHR AUDIT LOGS , WE FIRST DEVELOP A TEMPORAL DATA MINING ALGORITHM TO OBTAIN A DYNAMIC GRAPH REPRESENTING THE STRENGTHS OF COLLABORATION BETWEEN CARE PROVIDERS , WHICH IS USED WITH ECONOMETRIC MODELS TO FIND THE IMPACT OF COLLABORATION BETWEEN CARE PROVIDERS ON THE SERVICE TIME
582	WE FIND A CURVILINEAR IMPACT , INVERTED U , OF STAFF COLLABORATIONS ON SERVICE TIME OF INPATIENT STAYS
582	IT SUGGESTS A LEARNING CURVE , WHEN CARE PROVIDERS WITH LITTLE TO NO EXPERIENCE IN WORKING TOGETHER COLLABORATE , THEY INITIALLY HAVE A NEGATIVE IMPACT ON SERVICE TIME FOR INPATIENT STAYS
582	HOWEVER , AS THE COLLABORATIONS STRENGTHEN OVER TIME , THEY START TO MAKE A POSITIVE IMPACT BY DECREASING THE SERVICE TIME FOR INPATIENT STAYS
582	MSOM , HEALTHCARE SERVICE SCIENCE 
583	EMPOWERING ATTENDED HOME HEALTHCARE SERVICE , A ROBUST STRATEGY TO MITIGATE CASCADING DELAYS AND ENSURE PUNCTUAL CARE DELIVERY
583	WE CONSIDER AN ATTENDED HOME HEALTHCARE PROBLEM WITH UNCERTAIN TRAVEL AND SERVICES TIMES , WHICH IS FORMULATED AS A ROBUST HETEROGENEOUS SITE DEPENDENT CAPACITATED VEHICLE ROUTING PROBLEM WITH TIME WINDOWS
583	WE DISCOVER A CASCADING DELAY EFFECT CAUSED BY THE CONVOLUTIONAL UNCERTAINTIES IN TRAVEL AND SERVICE TIMES
583	WE PROPOSE A DISTRIBUTIONALLY ROBUST MODEL TO JOINTLY HANDLE UNCERTAINTIES AND CAPTURE THEIR CHARACTERISTICS , AND INTEGRATE PROBABILITY AND MAGNITUDE ASSESSMENT OF SCHEDULE RESILIENCY BY ANALYZING THE WORST CASE COMPOUND SET RELIABILITY INDEX , CSRI , REGARDING DELAYS
583	TO SOLVE THE PROBLEM FOR PRACTICAL PURPOSES , AN EXACT BRANCH PRICE AND CUT FRAMEWORK AND A VARIABLE NEIGHBORHOOD SEARCH META HEURISTIC ARE DEVELOPED TO OBTAIN FAST EFFECTIVE SOLUTIONS
583	MSOM , HEALTHCARE TSL , URBAN TRANSPORTATION PLANNING AND MODELING 
584	THE IMPACT OF THE PAYMENT BY RESULT , PBR , ON HOSPITALS OPERATIONAL EFFICIENCY
584	THE NATIONAL HEALTH SERVICE , NHS , IN ENGLAND CHANGES PAYMENT SCHEMES OVER TIME TO ENTICE HOSPITALS TO REDUCE COSTS , IMPROVE THE QUALITY OF CARE , AND INCREASE , OPERATIONAL , EFFICIENCY
584	IN , THE NHS INTRODUCED A NEW PAYMENT SYSTEM CALLED I PAYMENT BY RESULTS , PBR , I UNDER WHICH HOSPITALS ARE PAID A FIXED AMOUNT FOR EACH PATIENT BASED ON THEIR DIAGNOSIS GROUP AND THE TYPE OF TREATMENT THEY RECEIVE
584	THE PBR IS INTRODUCED TO IMPROVE OPERATIONAL EFFICIENCY AND TO REDUCE HIGH COSTS
584	THE IMPACT OF THIS REFORM MIGHT VARY IN DIFFERENT HOSPITALS BASED ON THEIR CHARACTERISTICS SUCH AS STATUS , E G , FOUNDATION TRUST , , SIZE , AND THE LEVEL OF UNAVOIDABLE EXPENSES
584	WE RELY ON EMPIRICAL ANALYSIS TO INVESTIGATE HOW HOSPITAL CHARACTERISTICS AFFECT THEIR RESPONSES TO THE USE OF PBR
584	MSOM , HEALTHCARE 
585	LEGISLATION DRIVEN INTERORGANIZATIONAL KNOWLEDGE SPILLOVERS
585	IN THIS STUDY WE LOOK AT THE EFFICACY OF LEGISLATIVE ACTIONS IN DRIVING BROADER CHANGES BEYOND TARGETED ORGANIZATIONS THROUGH SHARED PERSONNEL ENABLED INTERORGANIZATIONAL SPILLOVERS OF RELATED KNOWLEDGE , WHICH COVERS A WIDE SPECTRUM OF KNOWLEDGE THAT IS NOT DIRECTLY ASSOCIATED WITH AN INDIVIDUAL S EXPERTISE AREA
585	USING THE CONTEXT OF THE QUALITY PAYMENT PROGRAM , WE EMPLOYED A DIFFERENCE IN DIFFERENCES ANALYSIS TO ANSWER OUR RESEARCH QUESTIONS
585	OUR RESULTS DEMONSTRATE THE EXISTENCE OF INTERORGANIZATIONAL SPILLOVER EFFECTS FOR RELATED KNOWLEDGE DRIVEN BY THE LEGISLATION
585	WE ALSO FIND TIMING HETEROGENEITY OF KNOWLEDGE SPILLOVERS
585	FURTHER , WE FIND SPILLOVER EFFECTS ON BOTH QUALITY AND COST OF CARE RELATED KNOWLEDGE ARE STRONGER FOR HOSPITALS WITH A BETTER LEARNING ENVIRONMENT
585	MSOM , HEALTHCARE 
586	ICU NETWORKS DESIGN WITH STEP DOWN UNITS
586	INTENSIVE CARE UNITS , ICU , CARE FOR SOME OF THE MOST CRITICALLY ILL PATIENTS WITHIN HOSPITALS
586	ONCE ICU PATIENTS ARE STABLE ENOUGH , THEY CAN BE MOVED TO DOWNSTREAM UNITS , MAKING SPACE FOR INCOMING CRITICAL PATIENTS
586	TYPES OF DOWNSTREAM UNITS VARY BASED ON STAFF TRAINING AND LEVEL OF CARE
586	WHILE THE MOST GENERAL TYPE OF DOWNSTREAM UNITS ARE WARDS , CARING FOR STABLE PATIENTS BEFORE DISCHARGE , SOME HOSPITALS UTILIZE INTERMEDIATE , OR STEP DOWN , UNITS THAT ARE ABLE TO CARE FOR SEMI CRITICAL PATIENTS
586	WE EXPLORE NETWORK DESIGN CONSIDERATIONS BASED ON UTILITY MAXIMIZING OPTIMIZATION MODELS
586	WE TEST AND VALIDATE OUR PROPOSED NETWORK TOPOLOGIES USING LARGE SCALE MULTI PERIOD SIMULATION STUDIES CONSIDERING PATIENT HEALTH EVOLUTION AND TRANSFER POLICIES BETWEEN VARIOUS LEVEL OF CARE UNITS
586	MSOM , HEALTHCARE 
587	COMPETE OR COOPERATE , ANALYSIS OF FINANCING AND PRIVATE LABEL DECISIONS IN ONLINE RETAILING
587	ONLINE THIRD PARTY , P , RETAILERS FACE A SHORTAGE OF WORKING CAPITAL AND MAINLY DEPEND ON BANK FINANCING , BF , FOR LOANS
587	ONLINE PLATFORMS SUCH AS AMAZON AND ALIBABA HAVE RECENTLY STARTED COOPERATING WITH RETAILERS BY FUNDING THEM THROUGH PLATFORM FINANCING , PF , 
587	AT THE SAME TIME , THEY DIRECTLY COMPETE WITH THE SELLERS BY INTRODUCING A COMPETING PRIVATE LABEL , PB , 
587	THIS STUDY FOCUSES ON THIS FASCINATING COOPETITION SCENARIO AND JOINTLY ANALYSES THE PLAYERS FINANCING AND OPERATIONAL DECISIONS
587	WE FIND THAT THE RETAILER SHOULD NOT ALWAYS CHOOSE BF , EVEN IN THE PRESENCE OF PB PRODUCTS , E G , LOW REFERRAL FEE PRODUCTS , 
587	THE PLATFORM SHOULD NOT INTRODUCE PB IF THE PRODUCT QUALITY IS PERCEIVED AS LOW
587	FURTHERMORE , WE SHOW WITH AN INCREASE IN RISK , THE RETAILER PREFERS PF MORE , AND THE PLATFORM CAN INTRODUCE LOWER QUALITY PB
587	WE ALSO DEVELOP A PRODUCT BASED EQUILIBRIUM STRATEGY
587	MSOM , IFORM EBUSINESS OPTIMIZATION , OPT , 
588	ON THE EMPIRICAL PERFORMANCE OF REOPTIMIZATION AND MACHINE LEARNING HEURISTICS FOR MERCHANT COMMODITY STORAGE
588	COMMODITY MERCHANTS USE STORAGE ASSETS FOR MAXIMIZING PROFITS AND MANAGING THE RISK ASSOCIATED WITH VOLATILE PRICES
588	THE REOPTIMIZATION HEURISTIC , RH , IS A POPULAR APPROACH FOR MANAGING STORAGE
588	WHEN USED FOR PURE SPOT TRADING , RH HAS BEEN RECENTLY SHOWN TO RESULT IN LOWER PROFITS ON A REAL DATA BACKTEST COMPARED TO A MACHINE LEARNING METHODOLOGY THAT TRAINS A STRUCTURED POLICY
588	HOWEVER , THESE RESULTS DO NOT ACCOUNT FOR TRADING IN THE FORWARD MARKET THAT MERCHANTS LEVERAGE TO MANAGE RISK WHEN THIS MARKET IS LIQUID
588	IN THIS WORK , WE REVISIT THE EMPIRICAL COMPARISON OF RH AND MACHINE LEARNING POLICIES FOR COMMODITIES WITH LIQUID FORWARD MARKETS , ALLOWING FOR FORWARD TRADING , AND ASSESS THE PERFORMANCE OF THESE METHODS IN TERMS OF BOTH PROFIT AND RISK
588	MSOM , IFORM ENRE , ENERGY MANUFACTURING AND SERVICE OPERATIONS MANAGEMENT , MSOM , 
589	A COVERAGE PROCUREMENT APPROACH DOES NOT PAY , EMPIRICAL EVIDENCE OF THE COST OF FLEXIBILITY
589	MARKET UNCERTAINTY CAN DRIVE PROCUREMENT DECISIONS THAT FAVOR FLEXIBILITY AND DELAYED DECISION MAKING TO MITIGATE FINANCIAL RISK
589	HOWEVER , WE EMPIRICALLY DEMONSTRATE THAT DOING SO CAN LEAD TO HIGHER COSTS AND LOWER SUPPLIER PERFORMANCE
589	IN THE FULL TRUCKLOAD TRANSPORTATION SERVICES INDUSTRY , BUYING FIRMS , SHIPPERS , ESTABLISH NON BINDING CONTRACTS WITH TRUCKING COMPANIES , CARRIERS , THAT FUNCTION AS OPTIONS TO AVOID PRICE ESCALATIONS AND VOLATILITY IN A SPOT MARKET
589	WE BUILD A SET OF EMPIRICAL MODELS OF SHIPPERS AND CARRIERS STRATEGIC AND OPERATIONAL BEHAVIORS TO TEST THE EFFECTS OF SHIPPERS CHOICES TO ESTABLISH CONTRACTS BUT ULTIMATELY NOT EXERCISE THEM
589	DESPITE FIRMS INTENTIONS TO REDUCE COSTS AND MITIGATE RISKS , WE FIND THAT THE STRATEGY HAS TANGIBLE COSTS
589	WE ADD TO THE BY EXPLORING A CONTEXT IN WHICH THESE TACTICS ARE UNFAVORABLE AND QUANTIFY THE COSTS
589	MSOM , IFORM MSOM , SERVICE OPERATIONS TSL , FREIGHT TRANSPORTATION
589	THIS EMPIRICAL WORK SHOWS HOW FIRMS CAN UTILIZE HISTORICAL DATA TO IMPROVE STRATEGIC DECISIONS 
590	OPTIMAL INVENTORY POLICIES WHEN THE PURCHASE SELLING PRICE AND DEMAND ARE STOCHASTIC AND GOODS CAN BE SOLD BACK ON THE OPEN MARKET
590	THIS WORK EXTENDS ON THE WORK BY BERLING AND VICTOR MARTÍNEZ DE ALBÉNIZ , , BY ALLOWING PURCHASED GOODS TO BE SOLD BACK AT THE MARKET PRICE
590	THE CONDITIONS UNDER WHICH A PRICE DEPENDENT ECHELON BASE STOCK POLICY IS OPTIMAL IS PROVEN AND A METHOD FOR DETERMINING THESE BASE STOCK LEVELS USING THE UNIT TRACKING APPROACH IS DERIVED
590	NUMERICAL TESTS SHOW THAT IGNORING THE POSSIBILITY OF BEING ABLE TO SELL THE UNITS BACK LEADS TO SUBSTANTIAL DEVIATION FROM THE OPTIMAL POLICY AND A SIGNIFICANT INCREASE IN COST
590	MSOM , IFORM 
591	VALUATION PREMIUM EFFECTOF TARGETS OPERATIONS CAPABILITY IN M AS
591	VALUATION OF TARGET FIRMS IN MERGERS AND ACQUISITIONS , M AS , HAS FAR REACHING IMPLICATIONS FOR SHAREHOLDER WEALTH
591	THIS STUDY INVESTIGATES THE EFFECT OF A TARGET S OPERATIONS CAPABILITY ON THE VALUATION PREMIUMS , ABOVE ITS MARKET VALUE , THAT IT RECEIVES FROM THE ACQUIRING FIRM
591	WE FIND THAT TARGET FIRMS OPERATIONS CAPABILITY HAS A POSITIVE AND ECONOMICALLY SIGNIFICANT EFFECT ON THEIR M A VALUATION PREMIUMS
591	HOWEVER , THIS EFFECT BECOMES WEAKER WITH INCREASING MARKET OVERLAP BETWEEN THE TARGET AND ACQUIRING FIRMS
591	THESE FINDINGS OFFER CORPORATE EXECUTIVES A COMPREHENSIVE PERSPECTIVE ON THE ROLE OF OPERATIONS CAPABILITY IN ENHANCING SHAREHOLDER WEALTH BEYOND ITS EFFECT ON STOCK MARKET VALUE IN THE CONTEXT OF A MAJOR STRATEGIC DECISION , CORPORATE M AS
591	MSOM , IFORM 
592	COINS , CARDS , OR APPS , IMPACT OF PAYMENT METHODS ON STREET PARKING OCCUPANCY AND WAIT TIMES
592	THIS STUDY EXAMINES HOW DIFFERENT PAYMENT METHODS AFFECT DRIVERS PAYMENT BEHAVIOR , STREET PARKING OCCUPANCY AND INCURRED WAIT
592	WE DEVELOP AN ANALYTICAL MODEL FOR THE OPTIMAL PAYMENT AMOUNT AND ANALYZE PAYMENT PATTERNS
592	THE EMPIRICAL FINDINGS INDICATE THAT DRIVERS TEND TO PAY LESS WHEN THEY PAY WITH CASH OR VIA MOBILE APPLICATIONS THAN WITH CREDIT CARDS
592	TO PROVIDE FURTHER GUIDANCE TO MUNICIPALITIES , WE SIMULATE THE STREET PARKING SITUATION TO VERIFY THE EFFECTS OF EACH PAYMENT METHOD AND PRICING ON THE PARKING OCCUPANCY AND WAIT
592	THE RESULTS SHOW THAT USING MOBILE PAYMENT APPS LEADS TO SHORTER WAITING TIMES AND LOWER PARKING OCCUPANCY
592	SIMULATIONS ALSO REVEAL THE ASYMMETRICAL EFFECTS OF PRICE CHANGES ON OCCUPANCY AND WAIT TIMES
592	THESE FINDINGS HIGHLIGHT THE POTENTIAL BENEFITS OF MOBILE PAYMENTS AND PRICE ADJUSTMENTS FOR IMPROVING STREET PARKING EXPERIENCES
592	MSOM , SERVICE OPERATIONS BEHAVIORAL OPERATIONS MANAGEMENT TRANSPORTATION SCIENCE AND LOGISTICS , TSL , 
593	RELATIONSHIP BETWEEN PACKAGE DELIVERY SPEED AND PRODUCT RETURNS REVISITED , ENDOGENEITY , NONLINEARITY , AND HETEROGENEITY
593	AS CUSTOMERS INCREASINGLY DEMAND FAST DELIVERY WHEN SHOPPING ONLINE , AN UNDERSTANDING OF HOW LOGISTICS TIME AFFECTS THEIR PRODUCT RETURN TENDENCY BECOMES CRITICAL
593	RAO ET AL , , REVEALED THAT THERE EXISTS A LINEARLY POSITIVE RELATIONSHIP BETWEEN PACKAGE DELIVERY SPEED AND PRODUCT RETURNS
593	BUILDING ON THEIR SEMINAL FINDINGS , OUR RESEARCH EXAMINES THIS UNDERSTUDIED EFFECT IN A MORE GRANULAR MANNER , BOTH THEORETICALLY AND EMPIRICALLY , BY LEVERAGING A TRANSACTION LEVEL DATASET THAT IS MORE UP TO DATE AND LARGER IN SIZE
593	WE FIND THAT CUSTOMERS TENDENCY TO RETURN AN ORDER CONCAVELY INCREASES WITH THE ACTUAL DELIVERY TIME , WHICH CAN BE EXPLAINED BY CUSTOMER S SUBJECTIVE TIME PERCEPTION THAT PSYCHOPHYSICALLY DIFFERS FROM OBJECTIVE TIME
593	OUR FINDINGS HIGHLIGHT THE INCREMENTALLY INCREASING BENEFITS OF SHORTENING DELIVERY TIME ON ORDER RETURNS FOR ONLINE RETAILERS
593	MSOM , SERVICE OPERATIONS EBUSINESS SUPPLY CHAIN AND LOGISTICS IN PRACTICE
594	OPTIMAL CONTROL OF JOB COMPLETION DECISION IN FORK JOIN QUEUEING NETWORK
594	FORK JOIN , FJ , QUEUEING NETWORKS CAN CAPTURE THE TRADE OFF BETWEEN SPEED AND ACCURACY THAT COMMONLY ARISES IN KNOWLEDGE BASED SERVICE SYSTEMS WITH REDUNDANCY , SUCH AS FACT CHECKING FOR SOCIAL MEDIA PLATFORMS , HOSPITAL DIAGNOSIS OPERATIONS AND LEGAL SYSTEMS
594	IN FJ QUEUEING SYSTEMS , EACH INCOMING JOB TO THE SYSTEM IS COPIED AT THE FORK NODE TO ALL THE KNOWLEDGE SERVERS , AND THE JOB S COMPLETION IS DYNAMICALLY DECIDED AT THE JOIN NODE WHEN ALL OR SOME OF THE JOB COPIES ARE COMPLETED BY THE SERVERS
594	WE CHARACTERIZE THE STRUCTURE OF THE OPTIMAL POLICY AT THE JOIN NODE IN ORDER TO MINIMIZE THE TOTAL EXPECTED HOLDING COST AND ERROR IN DECISION MAKING
594	DUE TO THE CURSE OF DIMENSIONALITY , WE PROPOSE AN INTUITIVE AND EASY TO COMPUTE LINE HEURISTIC POLICY THAT USES A SIMPLER QUEUEING MODEL AND PERFORMS WITHIN A OPTIMALITY GAP
594	MSOM , SERVICE OPERATIONS MANUFACTURING AND SERVICE OPERATIONS MANAGEMENT , MSOM , OPT , OPTIMIZATION UNDER UNCERTAINTY
595	THE DRIVERS OF CONSUMER PURCHASE QUANTITY AND TRAFFIC IN RETAIL STORES
595	LIKE BUSINESSES , CONSUMERS HOLD INVENTORIES OF GOODS LIKE FOOD AND GASOLINE , SEPARATING CONSUMPTION FROM THE AMOUNT THE CONSUMER PURCHASES FROM A RETAILER PER TRANSACTION
595	SUCH DECOUPLING GIVES THE CONSUMER FLEXIBILITY IN DECIDING HOW MUCH TO PURCHASE IN EACH TRANSACTION , AN AMOUNT WE REFER TO AS THE CONSUMER PURCHASE QUANTITY , CPQ , , AND HOW OFTEN TO VISIT THE RETAILER
595	HENCE , VARIATION IN CPQ DRIVES TRAFFIC , SALES , AND FINANCIAL PERFORMANCE AT THE RETAILER
595	WE STUDY THE DRIVERS OF CPQ AND THE IMPLICATIONS OF CPQ FOR RETAILERS USING TRANSACTION DATA FROM A GASOLINE RETAILER
595	GASOLINE CPQ , MEASURED IN GALLONS , VARIES WITH PRICES AND CONSUMERS FINANCIAL CONDITIONS
595	WE SHOW HOW VARIATION IN GASOLINE CPQ AFFECTS THE RETAILER S GASOLINE PUMP TRAFFIC
595	WE FIND THAT INCREASES IN GASOLINE TRANSACTIONS CAUSE INCREASES IN NON GAS TRANSACTIONS E G , PURCHASES OF FOOD ITEMS
595	MSOM , SERVICE OPERATIONS MANUFACTURING AND SERVICE OPERATIONS MANAGEMENT , MSOM , PRACTICE 
595	THE RESEARCH EMPLOYS DATA TO UNDERSTAND CONSUMERS DECISIONS AND THEIR IMPLICATIONS FOR RETAILERS 
596	A NOVEL MOBILE BASED OUTPATIENT HEALTHCARE SERVICE DELIVERY MODEL , INVESTIGATING ACCEPTANCE AND ITS IMPACT ON PHYSICIANS PERFORMANCE
596	CHINA S TERTIARY HOSPITALS ARE OVERCROWDED DESPITE INCREASED EMERGENCY DEPARTMENT CAPACITY , WHILE PRIMARY HEALTHCARE CENTERS ARE WELL EQUIPPED TO TREAT OUTPATIENTS BUT UNDERUTILIZED AND COULD HELP ADDRESS THE ISSUE
596	THEREFORE , WE FIRST SUGGEST A MOBILE BASED HEALTHCARE SERVICE DELIVERY MODEL TO STREAMLINE OUTPATIENT FLOW AND OPTIMIZE RESOURCE UTILIZATION BETWEEN EMERGENCY DEPARTMENTS OF TERTIARY HOSPITALS AND PRIMARY HEALTHCARE CENTERS
596	SECONDLY , THE TECHNOLOGY AND PUBLIC PRIVATE SHARING ECONOMY BASED NATURE OF THE SUGGESTED HEALTHCARE SERVICE DELIVERY MODEL PROVOKED US TO EMPLOY TASK TECHNOLOGY FIT AND CHANNEL EXPANSION THEORIES IN THIS STUDY TO INVESTIGATE ITS ACCEPTANCE AND IMPACT ON PHYSICIANS PERFORMANCE
596	THIS STUDY HAS IMPLICATIONS FOR RESEARCHERS , GOVERNMENT HEALTHCARE AUTHORITIES , POLICYMAKERS , AND ONLINE HEALTHCARE SERVICE COMPANIES
596	MSOM , SERVICE OPERATIONS MSOM , HEALTHCARE MSOM , TECHNOLOGY , INNOVATION AND ENTREPRENEURSHIP
597	ANALYSIS OF THE SATISFACTION AND IMPORTANCE OF DELIVERY APPLICATIONS
597	THE DELIVERY APP MARKET IN SOUTH KOREA CONTINUES TO GROW WHILE COMPETITION AMONG COMPANIES INTENSIFIES
597	THIS STUDY EXPLORES THE ATTRIBUTES THAT A COMPETITIVE DELIVERY APP SHOULD HAVE BY UTILIZING IPA ANALYSIS ON VARIOUS ATTRIBUTES OF DELIVERY APPS IN KOREA
597	BY EXPLORING ATTRIBUTES THAT ARE EXPECTED TO FURTHER INCREASE CUSTOMER SATISFACTION , NEW DIRECTIONS FOR SERVICE DEVELOPMENT IN RELATED INDUSTRIES ARE PRESENTED
597	MSOM , SERVICE OPERATIONS MSOM , SUSTAINABLE OPERATIONS SUPPLY CHAIN AND LOGISTICS IN PRACTICE
598	FAST FOOD STORES WITH A DRIVE THROUGH OPTION RECOVERED FROM COVID , STORES WITHOUT DID NOT
598	COMPARING THE FOOT TRAFFIC DATA FOR POPULAR FAST FOOD CUSTOMERS BEFORE AND AFTER THE COVID PANDEMIC , WE EMPIRICALLY SHOW THAT CUSTOMER PREFERENCE SHIFTED FROM STORES WITHOUT A DRIVE THROUGH OPTION TO STORES WITH ONE
598	IN PARTICULAR , WE SHOW THAT THIS SHIFT IN PREFERENCE FOR A DRIVE THROUGH IS CONSISTENT ACROSS THE US
598	MOREOVER , WE FIND EVIDENCE OF SIGNS OF PERSISTENCE IN THIS SHIFT IN THE FUTURE
598	MSOM , SERVICE OPERATIONS MSOM , TECHNOLOGY , INNOVATION AND ENTREPRENEURSHIP TECHNOLOGY , INNOVATION MANAGEMENT AND ENTREPRENEURSHIP
599	LARGE SCALE SERVICE SYSTEMS PROVISIONING AN UNCERTAIN MARKET OF RATIONAL , DELAY SENSITIVE CUSTOMERS
599	IN THIS TALK , WE CONSIDER A LARGE SCALE SERVICE PROVIDER THAT CATERS TO A MARKET OF RATIONAL , DELAY SENSITIVE INDIVIDUALS , IN WHICH THE TOTAL MARKET SIZE FLUCTUATES STOCHASTICALLY OVER TIME
599	WITHIN THIS UNCERTAIN MARKET ENVIRONMENT , THE FIRM STRIVES TO ESTABLISH ITS PRICING POLICY AND DETERMINE THE APPROPRIATE SERVICE CAPACITY TO ACQUIRE , ALL WITH THE END GOAL OF MAXIMIZING ITS PROFITS
599	A CRUCIAL ASPECT OF OUR ANALYSIS REVOLVES AROUND THE TWO CONTROL PARAMETERS THAT THE FIRM CAN MANIPULATE TO ADAPT TO STOCHASTIC FLUCTUATIONS , THE PRICE OF THE SERVICE AND THE TOTAL CAPACITY
599	WE DEVELOP AN APPROACH THAT AIMS TO STRIKE THE OPTIMAL BALANCE BETWEEN THESE TWO CONTROL PARAMETERS , ENABLING THE FIRM TO MAXIMIZE ITS PROFIT WHILE CONSIDERING THE INHERENT UNCERTAINTY OF THE MARKET ENVIRONMENT
599	MSOM , SERVICE OPERATIONS REVENUE MANAGEMENT AND PRICING 
600	AN INVESTIGATION OF GIFT TYPES IN RELATIONSHIP ENHANCEMENT , THE GIFT RECIPIENT S PERSPECTIVE
600	RESEARCHERS HAVE QUESTIONED THE GENERALITY OF THE EXPERIENTIAL ADVANTAGES , THAT IS , CONSUMERS SHOULD BUY MORE EXPERIENTIAL , VS MATERIAL , PRODUCTS , AND EMPHASIZED THE IMPORTANCE OF EXPLORING POTENTIAL MODERATORS FOR THESE EXPERIENTIAL ADVANTAGES
600	THIS STUDY DRAWS ON THE LITERATURE ON THE MATERIAL EXPERIENTIAL PRODUCTS AND THE CONCEPT OF MENTAL IMAGERY TO INVESTIGATE THE EFFECT OF DIFFERENT GIFT TYPES ON GIFT RECIPIENT RESPONSES
600	THE RESULTS SHOW THAT , I , MATERIAL , VS LIFE EXPERIENCE , GIFTS RESULT IN BETTER GIFT RECIPIENT RESPONSES , , II , THESE MATERIAL ADVANTAGES HOLD REGARDLESS OF THE FOCUSES OF IMAGERY , AND , III , MENTAL REPRESENTATION MEDIATES THE RELATIONSHIP BETWEEN GIFT TYPES AND GIFT RECIPIENT RESPONSES
600	THIS STUDY PROVIDES THEORETICAL AND PRACTICAL IMPLICATIONS FOR COMPANIES TO MANAGE THEIR CONSUMERS PRODUCT PREFERENCES EFFECTIVELY
600	MSOM , SERVICE OPERATIONS SERVICE SCIENCE EBUSINESS
601	OPTIMAL WORLD DESIGN IN VIDEO GAMES
601	SPENDING TIME IN VIRTUAL SPACES IS A GROWING PART OF THE HUMAN EXPERIENCE
601	WE STUDY THE DESIGN OF VIRTUAL SPACES IN A VIDEO GAME CONTEXT , WITH AN EMPHASIS ON UNDERSTANDING HOW PEOPLE SPEND MORE OR LESS TIME ENJOYING THESE SPACES
601	WHEN DECIDING HOW TO CHART A MEANINGFUL PATH THROUGH A VIRTUAL WORLD , GAME PLAYERS CONFRONT A SERIES OF CHOICES
601	AN EFFECTIVE DESIGN OF A VIRTUAL WORLD MUST BALANCE TWO THINGS
601	FIRST , THE WORLD SHOULD BE FLEXIBLE TO DIFFERING TIME BUDGETS OF PLAYERS
601	SECOND , COMPLEX DESIGNS CAN OVERWHELM PLAYERS WITH DECISIONS
601	WE MODEL VIRTUAL WORLD DESIGN AS A GRAPH DESIGN PROBLEM
601	THE ASSOCIATED GRAPH DESIGN PROBLEM IS NP HARD
601	WE FIND POLYNOMIAL TIME ALGORITHMS WHEN DECISION FATIGUE DEPENDS ONLY ON THE NUMBER OF NODES AND PATHS
601	THE ALGORITHM USES AN ELEGANT OPTIMALITY CONDITION
601	IN THIS SETTING , OPTIMAL WORLD MAPS HAVE A SIDE QUEST TREE STRUCTURE
601	MSOM , SERVICE OPERATIONS SERVICE SCIENCE MANUFACTURING AND SERVICE OPERATIONS MANAGEMENT , MSOM , 
602	TO LAUNCH ONLINE COMMUNITY GROUP BUYING OR NOT , THE CHANNEL CHOICE OF E COMMERCE PLATFORM
602	IN ADDITION TO THE EXISTING SAME DAY DELIVERY , MANY E COMMERCE PLATFORMS , E G , MEITUAN AND FRESHHEMA , HAVE LAUNCHED ONLINE COMMUNITY GROUP BUYING WHICH REDUCES LAST MILE DELIVERY
602	THE PLATFORM ORDERS PRODUCTS FROM SUPPLIERS AND ASSIGNS A LEADER OF THE GROUP TO PROMOTE PRODUCTS IN A COMMUNITY
602	THIS PRE ORDER STRATEGY MAY BRING UP CONFLICT TO THE CURRENT CHANNEL WITH SAME DAY DELIVERY
602	THIS STUDY AIMS TO EXPLORE HOW CUSTOMER ACCEPTANCE OF THE GROUP BUYING , THE COMMISSION RATE FOR THE LEADER , AND THE OPERATIONAL COST DIFFERENCE ACROSS TWO CHANNELS AFFECT THE PLATFORM S CHANNEL CHOICE AND THE GROUP LEADER S EFFORT
602	MSOM , SERVICE OPERATIONS SOCIALLY RESPONSIBLE AND SUSTAINABLE OPERATIONS MSOM , SUPPLY CHAIN
603	DYNAMIC RESOURCE SHARING IN PRIVATE G NETWORKS WITH SLICING
603	WE PROPOSE A MARKOV DECISION PROCESS MODEL TO STUDY THE DECISION PROBLEM FACED BY THE OPERATOR OF A PRIVATE G NETWORK , KNOWN AS A PRIVATE CELL , WHO MUST ALLOCATE AVAILABLE CAPACITY TO MEET THE RESOURCE NEEDS OF THE PRIMARY USER OF THE NETWORK , BUT WHO MAY ALSO LEASE EXCESS CAPACITY TO EXTERNAL SECONDARY USERS TO GENERATE ADDITIONAL REVENUE
603	PRIVATE CELLS ARE PRIVATELY OWNED , LOCAL WIRELESS NETWORKS INDEPENDENT OF COMMERCIAL OR PUBLIC G NETWORKS
603	SUCH NETWORKS HAVE RECENTLY BEEN IMPLEMENTED IN FACTORIES , WAREHOUSES , HOSPITALS , PORTS , AND CAMPUSES
603	NETWORK SLICE INSTANCES ARE UNITS OF DEMAND FROM THE PRIMARY USER , REQUIRING SPECIFIC RESOURCE COMBINATIONS , SUCH AS SPECTRUM , COMPUTATION , OR STORAGE
603	WE USE THE MODEL TO CHARACTERIZE THE OPTIMAL REAL TIME ADMISSION DECISIONS FOR THE SLICE INSTANCES , AND LEASING AND CANCELLATION DECISIONS FOR THE SECONDARY USER DEMANDS
603	MSOM , SERVICE OPERATIONS TELECOMMUNICATIONS AND NETWORK ANALYTICS OPT , OPTIMIZATION UNDER UNCERTAINTY
604	MOBILE ADDITIVE MANUFACTURING SYSTEM DEVELOPMENT CONSIDERING TRUCK DRONE BIMODAL DELIVERY
604	ONE OF THE LOADING TECHNOLOGIES OF THE LATEST PHASE OF INDUSTRY REVOLUTION , INDUSTRY , IS ADDITIVE MANUFACTURING TECHNOLOGY
604	TRUCK DRONE BIMODAL DELIVERY SYSTEM WAS INVESTIGATED AND EMPLOYED FOR SUCH A LONG TIME
604	THIS STUDY AIMS TO INCORPORATE TRUCK DRONE DELIVERY SYSTEM WITH MOBILE ADDITIVE MANUFACTURING WHEREAS ALSO CONSIDERING THE CUSTOMERS PREFERRED DELIVERY TIME WINDOW AND THE OPTIMAL PRINTING SEQUENCE
604	A MIXED INTEGER LINEAR PROGRAMMING MODEL IS RECOMMENDED TO ESTABLISH THIS INNOVATIVE MECHANISM
604	THE RESULTS AFFIRM THE APPLICABILITY AND EFFECTIVENESS OF THE SUGGESTED MODEL
604	THE OUTCOMES ALSO ILLUSTRATE THAT THE MAXIMUM DRONE FLIGHT RANGE AND THE PRINTING JOB COMPLEXITY HAVE THE SUBSTANTIAL INFLUENCES ON THE TOTAL COST PERFORMANCE AND SATISFYING THE CUSTOMERS ON TIME DELIVERY NECESSITIES
604	MSOM , SERVICE OPERATIONS TRANSPORTATION SCIENCE AND LOGISTICS , TSL , OPT , INTEGER AND DISCRETE OPTIMIZATION
605	SERVICE RECOVERY ASSESSMENT AFTER POST COMPLAINT RESPONSE , A MODERATED MEDIATION APPROACH
605	ABSTRACT BR CONSUMER SENTIMENTS SIGNIFICANTLY IMPACT THE MARKETPLACE , INFLUENCING MARKET OUTCOMES
605	THIS RESEARCH INVESTIGATES POST COMPLAINT RESPONSE AND SERVICE RECOVERY USING SURVEYS
605	INTEGRATING THE EXPECTATION DISCONFIRMATION THEORY AND ADAMS S JUSTICE THEORY , IT EXPLORES RELATIONSHIPS AMONG FACTORS AND EMPLOYS A MODERATED MEDIATION APPROACH
605	ADDITIONALLY , IT OFFERS INSIGHTS ON RESOURCE CUSTOMIZATION FOR CUSTOMER SEGMENTS AND MAINTAINING CUSTOMER RELATIONSHIPS FOR ENHANCED MARKET PRESENCE
605	MSOM , SERVICE OPERATIONS 
606	ON THE OPTIMALITY OF STEPWISE POLICIES FOR MANAGING CAPACITY , INVENTORY AND BACKORDERS
606	WE CONSIDER THE PROBLEM OF SIMULTANEOUSLY MANAGING CAPACITY , INVENTORY AND BACKORDERS IN A MULTI MODE PRODUCTION ENVIRONMENT MODELED VIA BROWNIAN MOTION
606	THE PRESENCE OF MORE THAN TWO MODES ADDS AN ADDITIONAL LEVEL OF COMPLEXITY , NOT JUST WHEN TO CHANGE MODES , BUT ALSO WHICH MODE TO CHANGE TO
606	WE IDENTIFY CONDITIONS UNDER WHICH , A STEPWISE POLICY THAT MOVES FROM ONE MODE TO THE NEXT FASTER OR THE NEXT SLOWER MODE MINIMIZES LONG RUN AVERAGE COST
606	OUR CONSTRUCTIVE PROOF LEADS TO A PRACTICAL ALGORITHM FOR FINDING AN OPTIMAL POLICY
606	A NUMERICAL STUDY DEMONSTRATES IMPACT OF OFFERING ADDITIONAL MODES AND BACKORDERING
606	MSOM , SUPPLY CHAIN APPLIED PROBABILITY MANUFACTURING AND SERVICE OPERATIONS MANAGEMENT , MSOM , 
607	A NOVEL WAY BASED ON BEHAVIORAL COGNITION AND HUMAN MACHINE COLLABORATION , THE STOCHASTIC ADAPTATION METHOD FOR BEER GAME
607	THE BEER GAME IS A CLASSIC PROBLEM IN INVENTORY MANAGEMENT AND IS WIDELY USED TO DEMONSTRATE THE BULLWHIP EFFECT
607	GIVEN BOUNDED RATIONALITY , IT MAKES SENSE TO EXPLORE BEHAVIORAL COGNITION
607	WE PROPOSE THE STOCHASTIC ADAPTATION , SA , METHOD TO PLAY THE BEER GAME
607	IT ORIGINATES FROM THE CHARACTERIZATION OF SIMILAR BEHAVIORS BETWEEN HUMANS AND AI ALGORITHMS
607	THE SA PROVIDES A UNIFIED FRAMEWORK , ALLOWING PLAYERS TO DECIDE WITH LIMITED OPTIONS UNDER PARTIAL INFORMATION
607	EXPERIMENTS SHOW THAT THE SA ACHIEVES STABLE OPERATION IN DIFFERENT SUPPLY CHAIN SCENARIOS
607	EACH PLAYER DEVELOPS A POLICY AROUND ITS LOCAL ADAPTATION BUT ULTIMATELY CAN REALIZE GLOBAL ADAPTABILITY
607	UNDER CERTAIN CONDITIONS , THE SA CAN EXHIBIT A SMALLER COST AND THE BULLWHIP EFFECT THAN OTHER METHODS
607	HUMAN MACHINE COLLABORATION HELPS FURTHER OPTIMIZE ITS PERFORMANCE
607	MSOM , SUPPLY CHAIN BEHAVIORAL OPERATIONS MANAGEMENT ARTIFICIAL INTELLIGENCE
607	THE OR OF HUMAN MACHINE COLLABORATION WILL BECOME AN IMPORTANT MEANS OF DRIVING THE DATA REVOLUTION 
608	MANAGING SUPPLY CHAIN DISRUPTIONS , A CASE STUDY
608	GIVEN A DISRUPTION IN SUPPLY RESULTING IN LOSS OF PRODUCTION , WHAT PROCESSES DO AUTOMOTIVE FIRMS FOLLOW IN ORDER TO QUICKLY RESOLVE ISSUES WITH SUPPLY
608	A CASE STUDY IS CONDUCTED TO UNDERSTAND BEST PRACTICES
608	THIS PROBLEM IS PRESENTED IN THE CONTEXT OF TIME PRESSURE , WHERE THE BUYER DOES NOT HAVE THE TIME TO FOLLOW ESTABLISHED PROCEDURES
608	MSOM , SUPPLY CHAIN BEHAVIORAL OPERATIONS MANAGEMENT SUPPLY CHAIN AND LOGISTICS IN PRACTICE
609	A MINIBATCH SGD BASED LEARNING META POLICY FOR INVENTORY SYSTEMS WITH MYOPIC OPTIMAL POLICY
609	STOCHASTIC GRADIENT DESCENT , SGD , HAS PROVEN EFFECTIVE IN SOLVING MANY INVENTORY CONTROL PROBLEMS WITH DEMAND LEARNING
609	HOWEVER , IT OFTEN FACES THE PITFALL OF AN INFEASIBLE TARGET INVENTORY LEVEL THAT IS LOWER THAN THE CURRENT INVENTORY LEVEL
609	IN THIS PAPER , WE ADDRESS THE INFEASIBLE TARGET INVENTORY LEVEL ISSUE FROM A NEW TECHNICAL PERSPECTIVE WE PROPOSE A NOVEL MINIBATCH SGD BASED META POLICY
609	BY DEVISING THE OPTIMAL MINI BATCH SCHEME , OUR META POLICY ACHIEVES O , T , , , REGRET FOR THE GENERAL CONVEX CASE AND O , LOG T , REGRET FOR THE STRONGLY CONVEX CASE
609	TO DEMONSTRATE THE POWER AND FLEXIBILITY OF OUR META POLICY , WE APPLY IT TO THREE IMPORTANT INVENTORY CONTROL PROBLEMS , MULTI PRODUCT AND MULTI CONSTRAINT SYSTEMS , MULTI ECHELON SERIAL SYSTEMS , AND ONE WAREHOUSE AND MULTI STORE SYSTEMS BY CAREFULLY DESIGNING APPLICATION SPECIFIC SUBROUTINES
609	MSOM , SUPPLY CHAIN DATA MINING DECISION ANALYSIS SOCIETY
610	GLOBAL SUPPLY CHAIN NETWORK ANALYSIS AND ITS RESILIENCE
610	SUPPLY CHAIN ANALYSIS MAINLY FOCUSES ON A BILATERAL RELATIONSHIP , A STATIC NETWORK , OR SUBNETWORKS EXTRACTED FROM AN INDUSTRY
610	THIS PAPER EXAMINES SUPPLY CHAIN NETWORKS RESILIENCE BASED ON A WORLDWIDE COMPLEX DYNAMIC SETTING
610	WITH THE FINANCIAL CRISIS AS THE CASE STUDY , WE IDENTIFY NOT ONLY FIRM LEVEL FACTORS BUT ALSO NETWORK STRUCTURES THAT MITIGATE DISASTER DISRUPTIONS
610	MSOM , SUPPLY CHAIN DATA MINING OPT , NETWORK OPTIMIZATION
611	SPEND ANALYSIS , AUTOMATING PROCUREMENT PRACTICES USING NATURAL LANGUAGE PROCESSING AND MACHINE LEARNING
611	CONDUCTING A SPEND ANALYSIS OF A PROCUREMENT PRACTICE IS A CHALLENGING TASK FOR MANUFACTURERS
611	IT REQUIRES MAKING SENSE OF LARGE SCALE SPEND DATA IN THE FORM OF UNSTRUCTURED TEXTS AND IDENTIFYING SAVINGS OPPORTUNITIES
611	WE PROPOSE A COMPREHENSIVE METHODOLOGY WITH AN AUTOMATE SPEND ANALYSIS AND REPLICATE THE EXPERT S KNOW HOW
611	ALSO , OUR DECISION SUPPORT TOOL PERFORMS A KRALJIC ANALYSIS TO IDENTIFY THE PRODUCT CATEGORIES WITH THE HIGHEST SAVINGS POTENTIAL , AND HELPS RECOMMEND SPECIFIC SUPPLIERS TO SEEK SAVINGS
611	USING THE SPEND DATA FROM CRANSWICK PLC , A MAJOR FOOD PRODUCER IN THE UK , WE TEST THE ACCURACY OF OUR METHODOLOGY AND SHOW SUPERIOR PERFORMANCE COMPARED TO BENCHMARK MODELS
611	SIMULATION OF IMPLEMENTATION ESTIMATES THAT AUTOMATION OF SPEND ANALYSIS CONTRIBUTES TO M IN ANNUAL SAVINGS FOR CRANSWIK PLC
611	MSOM , SUPPLY CHAIN DECISION ANALYSIS SOCIETY PRACTICE 
612	SELLING FORMAT AND SELLER SERVICES IN ONLINE RETAILING
612	WE STUDY THE SELLING FORMAT , AGENCY SELLING VERSUS RESELLING , AND THE STRATEGIES OF SELLER SERVICES , ADVERTISING AND INFORMATION SHARING , IN A SUPPLY CHAIN WITH A SUPPLIER AND AN ONLINE RETAILER
612	FOR A GAME THEORETIC MODEL WITH BOTH SELLER SERVICES , WE FULLY CHARACTERIZE ITS EQUILIBRIUM AND SHOW HOW EACH FIRM S PREFERENCE OF THE SELLING FORMAT DEPENDS ON THE MODEL PARAMETERS
612	WE ALSO CONSIDER TWO OTHER MODELS WITH EITHER ADVERTISING SERVICE ONLY OR NO SELLER SERVICES
612	BY COMPARING THE MODELS , WE SHOW HOW THE OFFERING OF MORE SELLER SERVICES IMPACTS THE FIRMS PROFITS AS WELL AS THEIR PREFERENCE OF THE SELLING FORMAT
612	MSOM , SUPPLY CHAIN EBUSINESS SHARING ECONOMY , INNOVATIVE MARKETPLACES , AND DATA 
613	SUPPLY CHAIN DESIGN AND OPERATIONS UNDER OMNI CHANNEL ENVIRONMENTS
613	WE FOCUS ON SUPPLY CHAIN DESIGN AND OMNICHANNEL STRATEGIES WITH DEMAND SEGMENTATION , COST STRUCTURE , AND THE COMPANY S OPERATION ABILITY
613	WE SHOW THAT OMNICHANNEL STRATEGIES ARE NOT NECESSARILY PROFITABLE FOR ALL RETAILERS
613	POOR EXECUTION ABILITY MAY RESULT IN LOSING THE INVENTORY POOLING BENEFITS WHEN RUNNING OMNICHANNEL STRATEGIES
613	MSOM , SUPPLY CHAIN EBUSINESS 
614	SUPPLY CHAIN LEARNING AND ENVIRONMENTAL PERFORMANCE , LEVERAGING RELATIONAL CAPITAL AND INFORMATION TECHNOLOGY
614	THIS STUDY EMPIRICALLY INVESTIGATES HOW RELATIONAL CAPITAL AND INFORMATION TECHNOLOGY , IT , IMPROVE SCL AND ENVIRONMENTAL PERFORMANCE BY USING SOCIO TECHNICAL SYSTEM THEORY AND A KNOWLEDGE BASED VIEW
614	WE EMPLOY STRUCTURAL EQUATION MODELLING TO EXAMINE THE PROPOSED MODEL BY COLLECTING DATA FROM CHINESE MANUFACTURING COMPANIES
614	THE RESULTS DEMONSTRATE THAT RELATIONAL CAPITAL WITH SUPPLIER AND CUSTOMER ENHANCES SUPPLIER AND CUSTOMER LEARNING WHEREAS IT IS NOT SIGNIFICANTLY RELATED TO SUPPLIER AND CUSTOMER LEARNING
614	ADDITIONALLY , OUR RESULTS CONFIRM THAT CUSTOMER LEARNING ENHANCES ENVIRONMENTAL PERFORMANCE
614	HOWEVER , WE DID NOT FIND AN ASSOCIATION BETWEEN SUPPLIER LEARNING AND ENVIRONMENTAL PERFORMANCE
614	MSOM , SUPPLY CHAIN ENRE , ENVIRONMENT AND SUSTAINABILITY MSOM , SUSTAINABLE OPERATIONS
615	HOW DOES SUPPLY CHAIN FINANCE ENABLE SMES TO DEVELOP RESILIENCE
615	A PROCESS OF PARADOXES MANAGEMENT
615	SUPPLY CHAIN FINANCE , SCF , HAS BECOME AN IMPORTANT MEASURE TO ENHANCE THE RESILIENCE OF SMALL AND MEDIUM SIZED ENTERPRISES
615	HOWEVER , HOW TO EFFECTIVELY RESPOND TO THE PARADOXICAL PHENOMENON IN THE DEVELOPMENT OF SCF SERVICES AND CONTINUOUSLY MEET THE DIVERSE AND EVEN CONFLICTING DEMANDS REMAINS A KEY ISSUE
615	THIS ARTICLE EXPLORES SCF DEVELOPMENT PARADOX COMPOSED OF THREE TYPES OF PARADOXES , ELEMENT PARADOX , RELATIONSHIP PARADOX , AND CONFIGURATION PARADOX
615	IT IS NECESSARY FOR FINANCIAL SERVICE PROVIDERS TO ESTABLISH CORRESPONDING PARADOX MANAGEMENT CAPABILITIES TO EFFECTIVELY PROMOTE THE CONSTRUCTION OF SME RESILIENCE
615	APART FROM DIFFERENCES , THE ABILITIES OF PARADOX MANAGEMENT HAVE THE SAME CONSTRUCTION PATH , SEPARATION AT THE LOWER LEVEL AND SYNTHESIS AT THE HIGHER LEVEL , NAMELY SUB LEVEL SEGMENTATION , HIGHER LEVEL INTEGRATION 
615	MSOM , SUPPLY CHAIN FINANCE DIVERSITY , EQUITY , AND INCLUSION
615	DATA INFORMATION REDUCTION , DATA EFFICIENCY MAGNIFICATION , COMPLIANT CIRCULATION OF DATA 
616	VALUATION OF SUPPLY CHAIN FIRMS WITH FINANCIALLY DISTRESSED RETAIL PARTNER
616	THE CURRENT ASSET VALUATION APPROACHES DO NOT CONSIDER DYNAMIC INTERACTIONS BETWEEN SUPPLY CHAIN FIRMS
616	HOWEVER , THE INTERCONNECTIONS OF SUPPLY CHAIN FIRMS AFFECT THEIR CASH FLOWS WHICH ARE THE FUNDAMENTAL FACTOR DETERMINING FIRM VALUATIONS
616	IN PARTICULAR , SUPPLY CHAIN RELATIONSHIPS CAN BECOME CRITICAL WHEN THERE ARE FINANCIALLY DISTRESSED FIRMS
616	THIS RESEARCH DEVELOPS AN ASSET VALUATION APPROACH WHICH CONSIDERS THE RELATIONSHIP BETWEEN SUPPLY CHAIN PARTNERS AS WELL AS THE STOCHASTIC NATURE OF THE CREDIT RISK
616	OUR APPROACH ANALYZES VALUATIONS OF FIRMS IN SUPPLY CHAIN NETWORKS BY INTEGRATING GAME THEORY WITH CREDIT RISK MODEL AND VALUATION MODEL IN FINANCE
616	WE APPLY THE APPROACH TO STUDY FIRMS WITH FINANCIALLY DISTRESSED RETAIL PARTNERS , AND PRESENT ANALYTICAL RESULTS AS WELL AS NUMERICAL EXAMPLES
616	MSOM , SUPPLY CHAIN FINANCE 
617	AUTOCORRELATED PRICE SENSITIVE DEMAND AND THE DYNAMICS OF SUPPLY CHAINS
617	WE INVESTIGATE THE DYNAMICS OF A SUPPLY CHAIN WITH AN AUTOCORRELATED , PRICE SENSITIVE , STOCHASTIC , AND LINEAR DEMAND MODEL
617	WE ASSUME THE EXOGENOUS MARKET PRICE FOLLOWS A FIRST ORDER AUTOREGRESSIVE PROCESS
617	THE DEMAND PROCESS IS A WEIGHTED FUNCTION OF THE CURRENT AND PREVIOUS MARKET PRICES , THE MARKET POTENTIAL , AND THE POSITIVE DEMAND SENSITIVITY COEFFICIENT
617	WE ASSUME THAT A MANUFACTURER FACES FIVE DIFFERENT TYPES OF CUSTOMERS IN THE MARKET , RESPONSIVE , SELECTIVE , NAIVE , SPECULATIVE , AND SLOW CUSTOMERS
617	A WEIGHTING FACTOR DETERMINES HOW CUSTOMERS REACT TO PERIOD TO PERIOD PRICE CHANGES
617	IN ADDITION TO EXPLAINING THE BASIC DYNAMICS WITH THIS DEMAND MODEL , WE PROPOSE NEW IDEAS FOR DUAL SOURCING POLICIES , ASSUMING TWO SUPPLIERS , ONE OFFSHORE AND ONE NEAR SHORE
617	MSOM , SUPPLY CHAIN MANUFACTURING AND SERVICE OPERATIONS MANAGEMENT , MSOM , APPLIED PROBABILITY 
618	NEWSVENDOR S SUPPLIER SELECTION PROBLEM WITH CORRELATED SUPPLY AND DEMAND UNCERTAINTIES
618	IT IS ESTABLISHED IN LITERATURE , DADA ET AL , A NEWSVENDOR S PROCUREMENT PROBLEM WHEN SUPPLIERS ARE UNRELIABLE , M SOM , , , , , , THAT FOR A NEWSVENDOR FACING MULTIPLE SUPPLIERS , THE OPTIMAL SELECTION RULE , DPS S RULE , IS THAT THE CHEAPER ONES ARE ALWAYS SELECTED FIRST
618	TWO CRUCIAL ASSUMPTIONS ARE MADE , THE DEMAND AND SUPPLY RISKS ARE INDEPENDENT , AND THE NEWSVENDOR IS RISK NEUTRAL
618	IN THIS RESEARCH , WE RELAX THESE ASSUMPTIONS
618	WE FIRST STUDY THE SUPPLIER SELECTION PROBLEM WITH CORRELATED SUPPLY AND DEMAND RISKS AND IDENTIFY CONDITIONS THAT PRESERVE OR DO NOT PRESERVE THE DPS S RULE 
618	WE FIND THAT A POSITIVE DEMAND SUPPLY RELATIONSHIP CAN LEAD TO VIOLATION OF THE RULE
618	WITH A CVAR OBJECTIVE , WE FIND THAT RISK AVERSION PER SE DOES NOT AFFECT DPS S RULE AND STUDY THE IMPACT OF SUPPLY DEMAND CORRELATION ON THE SELECTION RULE BR THIS RESEARCH IS SUPPORTED BY THE GRF OF HK RGC
618	MSOM , SUPPLY CHAIN MANUFACTURING AND SERVICE OPERATIONS MANAGEMENT , MSOM , APPLIED PROBABILITY 
619	PRODUCTION NETWORKS RESILIENCE , CASCADING FAILURES , POWER LAWS AND OPTIMAL INTERVENTIONS
619	WE PROPOSE A NODE PERCOLATION PROCESS ON PRODUCTION NETWORKS THAT MODEL PRODUCT SUPPLIERS FAILING INDEPENDENTLY DUE TO EXOGENOUS , SYSTEMIC SHOCKS AND CAUSING OTHER PRODUCTS TO FAIL WHEN PRODUCTION REQUIREMENTS ARE UNMET
619	WE FIRST SHOW THAT THE SIZE OF THE CASCADING FAILURES FOLLOWS A POWER LAW IN RANDOM DIRECTED ACYCLIC GRAPHS , WHOSE TOPOLOGY ENCODES THE NATURAL ORDERING OF PRODUCTS FROM SIMPLE RAW MATERIALS TO COMPLEX PRODUCTS
619	THIS MOTIVATES THE NEED FOR A RESILIENCE METRIC , WHICH WE DEFINE AS THE MAXIMUM MAGNITUDE SHOCK THE PRODUCTION NETWORK CAN WITHSTAND WITH ONLY A SMALL FRACTION OF PRODUCTS FAILING
619	WE STUDY THE RESILIENCE OF SEVERAL ARCHITECTURES AND CLASSIFY THEM AS RESILIENT OR FRAGILE DEPENDING ON THEIR TOPOLOGICAL ATTRIBUTES
619	FINALLY WE OFFER OPTIMAL INTERVENTIONS FOR IMPROVING RESILIENCE , EMPIRICALLY EVALUATE THE RESILIENCE METRICS AND INTERVENTIONS
619	MSOM , SUPPLY CHAIN MANUFACTURING AND SERVICE OPERATIONS MANAGEMENT , MSOM , JUNIOR FACULTY INTEREST GROUP
619	USING DATA TO EVALUATE RESILIENCE OF LARGE SCALE SUPPLY CHAIN NETWORKS 
620	PARTIAL INFORMATION SHARING AND LEAKAGE IN THE PRESENCE OF ARMA DEMAND
620	WE SUGGEST A NOVEL MECHANISM FOR INFORMATION SHARING THAT ALLOWS A RETAILER TO CONTROL THE AMOUNT OF SHARED INFORMATION , AND THUS TO LIMIT INFORMATION LEAKAGE , WHILE STILL ASSISTING THE SUPPLIER TO MAKE BETTER INFORMED DECISIONS AND IMPROVE THE OVERALL EFFICIENCY OF THE SUPPLY CHAIN
620	WE ANALYZE A SUPPLY CHAIN IN WHICH A RETAILER OBSERVES AUTOREGRESSIVE MOVING AVERAGE , ARMA , DEMAND FOR A SINGLE PRODUCT WHERE ALL PLAYERS USE THE MYOPIC ORDER UP TO POLICY FOR DETERMINING THEIR ORDERS
620	WE INTRODUCE A NEW CLASS OF INFORMATION SHARING ARRANGEMENTS , COINED PARTIAL INFORMATION SHOCK , PAIS , SHARING
620	WE DEMONSTRATE THAT THE RETAILER CAN CONSTRUCT A PAIS SHARING ARRANGEMENT THAT ALLOWS FOR AN INTERMEDIATE LEVEL OF INFORMATION SHARING WHILE SIMULTANEOUSLY CONTROLLING THE AMOUNT OF LEAKAGE
620	MSOM , SUPPLY CHAIN MANUFACTURING AND SERVICE OPERATIONS MANAGEMENT , MSOM , SUPPLY CHAIN AND LOGISTICS IN PRACTICE
621	OPTIMUM USAGE OF D PRINTERS AND A REGULAR SUPPLIER , NONSTATIONARY DEMAND
621	IN THIS PAPER , WE CONSIDER A SINGLE ECHELON INVENTORY SYSTEM WHERE INVENTORY IS EITHER SOURCED FROM A REGULAR SUPPLIER WITH GENERAL LEAD TIME OR PRODUCED ON DEMAND USING A D PRINTER IN EXISTENCE OF MARKOV MODULATED DEMAND
621	IN OUR PROBLEM SETTING , WE CONSIDER THE QUALITY DIFFERENCE BETWEEN PRINTED AND REGULAR PARTS
621	WE SHOW THAT IN THIS PROBLEM SETTING A MARKOV MODULATED TAILORED BASE SURGE POLICY IS ASYMPTOTICALLY OPTIMAL
621	WE DEVELOP A PARAMETER OPTIMIZATION FOR THIS HEURISTIC POLICY
621	MSOM , SUPPLY CHAIN MANUFACTURING AND SERVICE OPERATIONS MANAGEMENT , MSOM , 
622	BENEFITS OF EXTREME POLITICAL STABILITY AND INSTABILITY OF SUPPLIERS COUNTRIES FOR FOCAL FIRMS , THE U SHAPED RELATIONSHIP
622	USING A LARGE SCALE PANEL DATASET , WE INVESTIGATE THE RELATIONSHIP BETWEEN A FIRM S PERFORMANCE AND ITS SUPPLIERS EXPOSURE TO POLITICAL INSTABILITY
622	THE EMPIRICAL EVIDENCE SUGGESTS A U SHAPED RELATIONSHIP BETWEEN A FOCAL FIRM S PERFORMANCE AND THE POLITICAL INSTABILITY OF ITS SUPPLIERS COUNTRIES , INDICATING THAT THE FIRM EXPERIENCES THE HIGHEST BENEFITS WHEN ITS SUPPLIERS ARE LOCATED IN HIGHLY STABLE OR UNSTABLE POLITICAL ENVIRONMENTS
622	FURTHERMORE , WE DISCOVERED THAT THE RELATIONSHIP VARIES DEPENDING ON THE INDUSTRY CATEGORY OF THE FIRM
622	MSOM , SUPPLY CHAIN MANUFACTURING AND SERVICE OPERATIONS MANAGEMENT , MSOM , IT DOES 
623	A RESEARCH OUTLOOK ON SUPPLY CHAIN SUSTAINABILITY AND PRODUCT RETURNS 
623	CONSUMERS MAY RETURN PRODUCTS FOR VARIOUS REASONS , THE PRODUCT RECEIVED MAY BE THE WRONG COLOR OR SIZE , FUNCTION POORLY , DAMAGED DURING SHIPMENT , OR PURCHASED IMPULSIVELY AND REGRETTED
623	PRODUCT RETURNS AND , THEREBY , PRODUCT RETURN POLICIES MAY PROFOUNDLY IMPACT SUSTAINABLE SUPPLY CHAIN LOGISTICS , ADDING EXTRA STRAIN ON THE ALREADY CHALLENGING REVERSE LOGISTICS OPERATIONS AND EATING UP RESOURCES FROM FORWARD LOGISTICS OF SUPPLY CHAINS
623	MOREOVER , THE ENORMOUS GROWTH IN OMNICHANNEL SHOPPING MAKES STUDYING PRODUCT RETURNS FROM CONSUMER BEHAVIOR AND SUSTAINABLE SUPPLY CHAIN PERSPECTIVES CRITICAL
623	IN THIS SHORT TALK , WE WILL DRAW ON SOME RELEVANT THEORIES AND OPTIMALITY RESULTS , DISCUSS PRACTICAL IMPLICATIONS , AND POINT TO FUTURE RESEARCH VENUES FOR MITIGATING THE IMPACT OF PRODUCT RETURNS ON SUPPLY CHAIN SUSTAINABILITY THROUGH THE QUADRUPLE BOTTOM LINE APPROACH
623	MSOM , SUPPLY CHAIN MSOM , SUSTAINABLE OPERATIONS SOCIALLY RESPONSIBLE AND SUSTAINABLE OPERATIONS
623	PRODUCT RETURNS , AND RELATED CONSUMER BEHAVIOR , GENERATE MASSIVE DATA THAT COULD BE USED IN SCM 
624	EXPLORING THE INTERPLAY OF AGILE METHODOLOGIES , RESILIENCE , AND ESG IN SUPPLY CHAINS , A BIBLIOMETRIC REVIEW AND QUALITATIVE ANALYSIS
624	THE IMPORTANCE OF AGILE METHODOLOGIES AND RESILIENCE HAS INCREASED DUE TO COMPETITIVENESS AND THE RISK OF VALUE CHAIN DISRUPTION
624	ESG FRAMEWORKS IN INVESTMENT DECISION MAKING ARE GAINING MOMENTUM , BUT IMPLEMENTATION ACROSS INDUSTRIES IS LIMITED , AND ITS RELATIONSHIP WITH FUNCTIONS SUCH AS SUPPLY CHAIN , AND LOGISTICS IS UNDERSTUDIED
624	THE IMPACT OF ESG AND AGILITY ON SUPPLY CHAIN RESILIENCE IS STILL BEING EXPLORED , RESULTING IN A LACK OF EXTENSIVE RESEARCH
624	A BIBLIOMETRIC REVIEW AND QUALITATIVE ANALYSIS OF ARTICLES FROM TO REVEALED A GROWTH IN SCIENTIFIC PRODUCTION ON THE TOPIC
624	THE STUDY EMPHASIZES THE INTERDEPENDENCE BETWEEN RESILIENCE AND AGILITY , FOCUSING ON FINANCIAL AND OPERATIONAL PERFORMANCE IN THE SUPPLY CHAIN REGARDING ESG
624	IDENTIFIED GAPS IN THE LITERATURE PROVIDE INSIGHTS FOR FUTURE RESEARCH
624	MSOM , SUPPLY CHAIN MSOM , SUSTAINABLE OPERATIONS SUPPLY CHAIN AND LOGISTICS IN PRACTICE
625	A MODEL FOR PERISHABLE INVENTORY MANAGEMENT IN COLD CHAINS
625	WE CONSIDER A SINGLE LOCATION PERISHABLE INVENTORY MODEL IN WHICH ITEMS ARE SHIPPED IN A COLD CHAIN , WHICH MAINTAINS THEIR FRESHNESS EITHER PERFECTLY OR TO A LARGE EXTENT IN COMPARISON WITH TRADITIONAL MEDIA
625	UPON ARRIVAL ITEMS START AGING AND EXPIRE AFTER A FIXED TIME
625	A MODIFIED , Q , R , POLICY IS EMPLOYED FOR INVENTORY CONTROL WITH A SINGLE BATCH RETAINED ON THE SHELF AT ANY TIME USABLE ITEMS ARE DISCARDED IN A SECONDARY MARKET WHEN A NEW BATCH IS RECEIVED
625	WE STUDY THE IMPACT OF VARIOUS FRESHNESS PRESERVING TECHNOLOGIES ON THE PERFORMANCE OF THE INVENTORY SYSTEM
625	WE PRESENT THEORETICAL FINDINGS AS WELL AS SOME NUMERICAL EXAMPLES
625	MSOM , SUPPLY CHAIN MSOM , SUSTAINABLE OPERATIONS SUPPLY CHAIN AND LOGISTICS IN PRACTICE
625	WE CONSIDER THE IMPACT OF STATE INFORMATION ON THE OPERATING CHARACTERISTICS OF THE MODEL 
626	PRICE STRATEGIES IN SUSTAINABLE O O SUPPLY CHAIN CONSIDERING CONSUMER PURCHASING AND LEASING BEHAVIORS 
626	THIS PAPER INVESTIGATES PRICING STRATEGIES IN SUSTAINABLE O O , ONLINE TO OFFLINE , SUPPLY CHAINS , TAKING INTO CONSIDERATION A MODEL WHERE A CONSUMER S PURCHASE AND LEASING BEHAVIORS COEXIST
626	WITH THE POPULAR OF SHARING ECONOMY , WE EXAMINE A NEW O O MODEL THAT COMBINES CONSUMERS PURCHASE AND LEASING BEHAVIORS
626	WE ANALYZE AN O O SUPPLY CHAIN WHERE MANUFACTURERS PRODUCE SUSTAINABLE PRODUCTS AND PROVIDE THEM THROUGH ONLINE CHANNEL , WITH RETAILERS RESPONSIBLE FOR ALL ORDERS AND OFFLINE SALES
626	WE ESTABLISH A MATHEMATICAL FUNCTION MODEL TO ANALYZE THE IMPACT OF SUSTAINABILITY PREFERENCES AND CONSUMER BEHAVIORS ON ONLINE AND OFFLINE PRICING AND PROFITS
626	THE CONTRIBUTION OF THIS PAPER IS TO OBTAIN PRICING AND RETAILING STRATEGIES IN SUSTAINABLE SUPPLY CHAINS THROUGH COLLABORATION BETWEEN ONLINE AND OFFLINE CHANNELS
626	MSOM , SUPPLY CHAIN MSOM , SUSTAINABLE OPERATIONS SUPPLY CHAIN AND LOGISTICS IN PRACTICE
627	STAY OR MOVE
627	THE IMPACT OF ENVIRONMENTAL REGULATION ON SUPPLY CHAIN RECONFIGURATION
627	WHETHER AND HOW ENVIRONMENTAL REGULATION INFLUENCE SUPPLY CHAIN NETWORKS IS THEORETICALLY AMBIGUOUS AND WARRANTS AN EMPIRICAL ANALYSIS
627	WE EMPIRICALLY STUDY THE IMPACT OF THE STRINGENCY OF ENVIRONMENTAL REGULATION ON FIRMS SUPPLY CHAIN DYNAMIC ADJUSTMENT USING FIRM LEVEL PANEL DATA
627	OUR RESULTS SHOW A NEGATIVE RELATIONSHIP BETWEEN ENVIRONMENTAL REGULATION AND SUPPLY CHAIN INVOLVEMENT
627	ALSO , THE MAIN NEGATIVE EFFECT IS MODERATED BY SEVERAL FACTORS
627	THESE RESULTS ARE ROBUST ACROSS MANY TESTS
627	THESE FINDINGS SHED NEW LIGHT ON HOW FIRMS USE SUPPLY CHAIN TO ARBITRAGE ACROSS INSTITUTIONAL ENVIRONMENTS
627	MSOM , SUPPLY CHAIN MSOM , SUSTAINABLE OPERATIONS 
628	DIRECT TRADE SOURCING STRATEGIES FOR SPECIALTY COFFEE
628	LEADING SPECIALTY COFFEE ROASTERS RELY ON DIRECT TRADE TO SOURCE PREMIUM COFFEE BEANS
628	WE STUDY HOW CHARACTERISTICS OF THE OPERATING AND MARKET ENVIRONMENT AFFECT THE OPTIMAL SOURCING STRATEGY AND INCENTIVES FOR A CLOSER RELATIONSHIP WITH A GROWER
628	MSOM , SUPPLY CHAIN MSOM , SUSTAINABLE OPERATIONS 
629	FINANCIAL HEDGING INCENTIVE CONTRACTS IN GLOBAL SUPPLY CHAINS , A DISTRIBUTIONALLY ROBUST APPROACH
629	THIS PAPER CONSIDERS GLOBAL SOURCING DECISIONS UNDER EXCHANGE RATE AND DEMAND UNCERTAINTIES , PROPOSES FINANCIAL HEDGING INCENTIVE CONTRACTS TO EXPLORE THE CHARACTERISTICS OF EXCHANGE RATE RISK MITIGATION POLICIES FOR GLOBAL SUPPLY CHAINS
629	THE DISTRIBUTIONALLY ROBUST STACKELBERG GAME MODEL IS DESIGNED TO SOLVE THE PROBLEM
629	OUR RESULTS SHOW THAT IN THE DISTRIBUTIONALLY ROBUST SETTING , THE CORRELATION BETWEEN THE EXCHANGE RATE AND DEMAND DOES NOT AFFECT THE RETAILER S ORDER DECISION
629	ADDITIONALLY , THE VARIANCE OF THE EXCHANGE RATE AND DEMAND FLUCTUATION HAS AN IMPACT ON THE RETAILER S ORDER DECISION , WHICH MAINLY DEPENDS ON THE MEAN VALUE OF THE EXCHANGE RATE
629	MOREOVER , FINANCIAL HEDGING INCENTIVE CONTRACTS MAKE WHOLESALE PRICE CONSTRAINTS LOOSER , INCREASING THE SCOPE FOR UPSTREAM AND DOWNSTREAM COOPERATION AND ENABLING HIGHER ORDER QUANTITY
629	MSOM , SUPPLY CHAIN OPT , LINEAR AND CONIC OPTIMIZATION OPT , OPTIMIZATION UNDER UNCERTAINTY
629	DISTRIBUTED ROBUST OPTIMIZATION METHODS CAN HANDLE COMPLEX DECISION PROBLEMS UNDER UNCERTAIN DATA 
630	ANALYSIS OF RESILIENCE METRIC S CORRELATION
630	THIS WORK PROPOSES A NEW FRAMEWORK FOR COMPARING DIFFERENT RESILIENCE METRICS INCLUDING TOPOLOGICAL , FLOW BASED , AND ECONOMIC METRICS
630	THE FIRST CONTRIBUTION OF THIS PRESENTATIONCONSIDERS THE SOCIO ECONOMIC , SPATIAL , AND PHYSICAL CHARACTERISTICS OF THE NETWORK COMPONENTS IN THE COMPARISON
630	THEREFORE , THE CORRELATION BETWEEN RESILIENCE METRICS AND DIFFERENT CHARACTERISTICS OF THE NETWORK CAN BE ANALYZED
630	THE SECOND CONTRIBUTION IS AN ANALYSIS OF RESTORATION BEHAVIOR IN TERMS OF TIME AND PERCENTAGE OF RESTORED SERVICE CONSIDERING DIFFERENT RESILIENCE METRICS
630	THE APPLICABILITY OF THE PROPOSED FRAMEWORK IS ILLUSTRATE WITH THE SWEDISH RAILWAY NETWORK
630	MSOM , SUPPLY CHAIN OPT , NETWORK OPTIMIZATION 
631	NON COMMITTED COST AUDITING IN SUPPLY CHAIN CONTRACTS
631	AS A WIDELY USED MEANS IN SUPPLY CHAIN PRACTICE , AUDIT CAN BE USED AS AN AUXILIARY MEANS TO ALLEVIATE THE SUPPLY CHAIN INCOORDINATION PROBLEM UNDER ASYMMETRIC INFORMATION THAT CANNOT BE SOLVED BY PROFIT SHARING CONTRACT AND OTHER MEANS
631	ALTHOUGH SOME STUDIES HAVE CONSIDERED AUDIT ISSUES UNDER SUPPLY CHAIN CONTRACTS IN THE LITERATURE , FEW STUDIES ARE CONDUCTED FROM THE PERSPECTIVE OF PRINCIPAL AGENT THEORY , NOT TO MENTION THE SITUATION WHERE RETAILERS DO NOT COMMIT TO AUDIT STRATEGIES UNDER THE PRINCIPAL AGENT MODEL
631	IN THIS PAPER , UNDER THE PRINCIPAL AGENT THEORY MODEL , WE CONSIDER THE OPTIMAL AUDIT STRATEGY WHEN THE RETAILER MAKES NO COMMITMENT TO THE AUDIT MECHANISM
631	WE EXPLORE THE UNIQUE FEATURES OF THE AUDIT STRATEGY AND THE SENSITIVITY OF THE OPTIMAL STRATEGY TO VARIOUS FACTORS
631	MSOM , SUPPLY CHAIN OPT , OPTIMIZATION UNDER UNCERTAINTY BEHAVIORAL OPERATIONS MANAGEMENT
632	RESEARCH TRENDS FOR INVENTORY OPTIMIZATION WITH PRODUCT SUBSTITUTION , FROM MODEL BASED TO DATA DRIVEN APPROACHES
632	PRODUCT SUBSTITUTION IMPACTS DIFFERENT LEVELS OF THE SUPPLY CHAIN AND CONTRIBUTES TO THE DECISIONS IN ASSORTMENT PLANNING , INVENTORY OPTIMIZATION , AND PRICING
632	THE INCREASING VARIETY OF PRODUCTS , LEVEL OF CONSUMER DIVERSITY AND AMOUNT OF HISTORICAL DATA AVAILABLE HAS BEEN INSTIGATING THE DEVELOPMENT OF NEW DATA DRIVEN FRAMEWORKS THAT ACCOUNT FOR DIFFERENT DEMAND PATTERNS AND IMPROVE DECISIONS FLEXIBILITY DUE TO SUBSTITUTION
632	WE PRESENT A THOROUGH REVIEW ON THE STUDIES ABOUT PRODUCT SUBSTITUTION WITH A FOCUS ON ITS EFFECTS ON INVENTORY OPTIMIZATION , EVOLVING FROM THE CLASSICAL MODEL BASED APPROACHES THAT RELY ON DISTRIBUTIONAL ASSUMPTIONS , TO FULLY DATA DRIVEN DECISION MAKING METHODS
632	THE STUDIES ARE CATEGORIZED BASED ON THE METHODOLOGY TO MODEL AND SOLVE THE INVENTORY PROBLEM WITH THE AIM TO IDENTIFY KNOWLEDGE GAPS AND SUGGEST RESEARCH DIRECTIONS
632	MSOM , SUPPLY CHAIN OPTIMIZATION , OPT , MULTIPLE CRITERIA DECISION MAKING
632	EVOLUTION OF THE LITERATURE OF MODEL BASED TO DATA DRIVEN APPROACHES TO SOLVE PRODUCT SUBSTITUTION 
633	MATHEURISTIC FOR SYNCHRONIZED VEHICLE ROUTING PROBLEM WITH MULTIPLE CONSTRAINTS AND VARIABLE SERVICE TIME
633	THIS WORK CONSIDERS AN EXTENSION OF THE VEHICLE ROUTING PROBLEM WITH SYNCHRONIZATION CONSTRAINTS AND INTRODUCES THE VEHICLE ROUTING PROBLEM WITH MULTIPLE SYNCHRONIZATION CONSTRAINTS AND VARIABLE SERVICE TIME
633	WE PROPOSE A MIXED INTEGER PROGRAMMING MODEL FOR THIS CHALLENGING PROBLEM , ALONG WITH PROBLEM SPECIFIC VALID INEQUALITIES
633	A THREE PHASE POWERFUL MATHEURISTIC IS PROPOSED TO SOLVE LARGE INSTANCES ENHANCED WITH A NOVEL LOCAL SEARCH METHOD
633	USING REALISTIC DATA , RESULTS SHOW THAT OUR MATHEURISTIC IS FAST AND EFFICIENT IN TERMS OF SOLUTION QUALITY AND COMPUTATIONAL TIME COMPARED TO THE STATE OF THE ART MIP SOLVER
633	USING REAL WORLD DATA , WE DEMONSTRATE THE IMPORTANCE OF CONSIDERING AN OPTIMIZATION APPROACH TO SOLVE THE PROBLEM , SHOWING THAT THE POLICY IMPLEMENTED IN PRACTICE OVERESTIMATES THE COSTS BY MSOM , SUPPLY CHAIN OPTIMIZATION , OPT , SUPPLY CHAIN AND LOGISTICS IN PRACTICE
634	BUYER SUPPLIER CULTURAL DISTANCE AND ORGANIZATIONAL RESILIENCE
634	THIS STUDY INVESTIGATES THE IMPACT OF A BUYER FIRM S ORGANIZATIONAL CULTURE DISTANCE FROM ITS SUPPLIERS ON ORGANIZATIONAL RESILIENCE
634	WE USE A VALIDATED TEXT BASED METHOD TO CAPTURE CULTURAL DISTANCE TO TEST OUR HYPOTHESES
634	BASED ON ARCHIVAL DATA COLLECTED FROM , BUYER FIRMS AND THEIR SUPPLIERS LISTED IN THE UNITED STATES , WE FIND THAT FIRMS WITH HIGH CULTURAL DISTANCE FROM THEIR SUPPLIERS , EXPERIENCE MORE FIRM VALUE LOSS AFTER BEING EXPOSED TO AN EXTERNAL DISRUPTION AS WELL AS TAKING A LONGER TIME TO RECOVER FROM THE DISRUPTION
634	FURTHERMORE , THE IMPACT OF CULTURAL DISTANCE ON ORGANIZATIONAL RESILIENCE IS WEAKER FOR FIRMS OPERATING IN MORE TURBULENT ENVIRONMENTS
634	OUR STUDY COMBINES A SUPPLY CHAIN AND CULTURE PERSPECTIVE AS THE DETERMINANTS OF ORGANIZATIONAL RESILIENCE
634	MSOM , SUPPLY CHAIN PANDEMIC MANAGEMENT MANUFACTURING AND SERVICE OPERATIONS MANAGEMENT , MSOM , 
634	IT USED A TEXT BASED METHOD TO MEASURE ORGANIZATIONAL CULTURE , WHICH HAS NORMALLY MEASURED BY SURVEY 
635	RETHINKING SUPPLY CHAIN TRADE OFFS TO FACE PANDEMIC OUTBREAKS , CURRENT DECISION SUPPORT MODELS AND INSIGHTS FOR FUTURE DIRECTIONS
635	THE RECENT COVID HAD SEVERELY IMPACTED SUPPLY CHAINS THAT COMPANIES ARE STILL RECOVERING FROM THE SHOCK IT CAUSED TO THEIR SUPPLY CHAINS ALMOST FOUR YEARS AFTER THE PANDEMIC FIRST STARTED
635	THE PANDEMIC HAS EXPOSED MANY FLAWS IN MODERN SUPPLY CHAINS FORCING COMPANIES TO REASSESS THEIR EXISTING SUPPLY CHAIN STRATEGIES
635	IN THIS PAPER , WE REVIEW CURRENT RESEARCH ON SUPPLY CHAIN MANAGEMENT DURING EPIDEMICS AND DISCUSS HOW PANDEMIC OUTBREAKS LEAD TO THE RETHINKING OF SUPPLY CHAIN DECISIONS
635	WE MAINLY ANALYZE EXISTING SUPPLY CHAIN MODELS DEPLOYED FOR EPIDEMIC CONTROL AND ASSESS THEM FROM THE PERSPECTIVE OF THE NEW CHALLENGES IMPOSED BY COVID WE FOCUS ON DECISION SUPPORT MODELS AND QUANTITATIVE METHODOLOGIES USED IN SUPPLY CHAIN MANAGEMENT PRE AND POST COVID AND IDENTIFY MODELING GAPS TO ADDRESS AND IMPROVE RESPONSE IN FUTURE PANDEMICS
635	MSOM , SUPPLY CHAIN PANDEMIC MANAGEMENT SUPPLY CHAIN AND LOGISTICS IN PRACTICE
636	MODELING PURCHASE PREMIUM USING BINOMIAL TREE OPTIONS
636	IN , BLACK SWAN EVENTS , SUCH AS COVID AND THE UKRAINIAN RUSSIAN WAR , CAUSE SERIOUS UNCERTAINTY IN THE SUPPLY CHAIN
636	TO SHARE RISKS BETWEEN SUPPLIERS AND MANUFACTURES , THIS STUDY DESIGNS A PURCHASE PREMIUM CONTRACT
636	BY PAYING THE PREMIUM IN ADVANCE , THE MANUFACTURER HAS A RIGHT TO TERMINATE OR CONTINUE THE PURCHASE CONTRACT WITH THE SUPPLIER ACCORDING TO THE ACTUAL NEEDS
636	ON THE OTHER HAND , THE SUPPLIER COULD DIMINISH INVENTORY RISKS
636	WE DEVELOP THE PRICING MODEL USING THE BINOMIAL TREE OPTIONS METHOD
636	FOR THE NUMERICAL ANALYSIS , WE COLLECT SALES DATA FROM A TECHNOLOGY COMPANY IN TAIWAN AND ANALYZE THE EFFECTS OF THE PROPOSED CONTRACT DESIGN ON THREE DIFFERENT PERIODS BEFORE , DURING AND AFTER COVID THE DIFFERENCES IN COST SHARING UNDER THE CURRENT CONTRACT AND THE PREMIUM CONTRACT ARE DISCUSSED
636	MSOM , SUPPLY CHAIN REVENUE MANAGEMENT AND PRICING SUPPLY CHAIN AND LOGISTICS IN PRACTICE
636	WE MEASURE THE UNCERTAINTY FROM DATA TO ADDRESS THE RISK SHARING ISSUE IN THE SUPPLY CHAIN
637	BENEFIT OF OPAQUE SELLING FOR INVENTORY MANAGEMENT
637	IN THIS STUDY , WE EXPLORE THE CONCEPT OF OPAQUE SELLING WHEREIN SPECIFIC PRODUCT DETAILS ARE WITHHELD UNTIL AFTER PURCHASE AND ITS BENEFIT ON INVENTORY MANAGEMENT
637	WE FIND THAT THE ADVANTAGES OF OPAQUE SELLING EXTEND BEYOND MERELY ALLOCATION FLEXIBILITY
637	EVEN IN SCENARIOS WITH MINIMAL OR NO ALLOCATION FLEXIBILITY , SELLERS CAN STILL DERIVE BENEFITS FROM OPAQUE SELLING
637	WE FURTHER ESTABLISH THAT , IN LARGER MARKETS , A MIXED OPAQUE SELLING STRATEGY EFFECTIVELY BALANCES INVENTORY COSTS AND REVENUE , THEREBY IMPROVING THE PROFIT
637	MOREOVER , WE SHOW THAT EVEN IN THE ASYMMETRIC MARKET , SLIGHT FLEXIBILITY INTRODUCED THROUGH OPAQUE SELLING CAN LEAD TO ALMOST CONSTANT RELATIVE INVENTORY SAVINGS AS THE MARKET SIZE INCREASES
637	MSOM , SUPPLY CHAIN REVENUE MANAGEMENT AND PRICING 
638	ANALYZING TRADE AGENTS DECISIONS IN B B TRANSACTIONS
638	WE FORMULATE AND ANALYZE THE PROCUREMENT DECISIONS OF A TRADE AGENT IN B B MARKETS
638	WE CAST THE PROBLEM AS A NEW TYPE OF NEWSVENDOR PROBLEM WHERE THE TRADE AGENT BIDS TO PURCHASE A PREDETERMINED SUPPLY FROM SELLER , S , 
638	WE ANALYZE THE CONDITIONS UNDER WHICH THE OPTIMAL BIDS ARE MONOTONIC
638	WE ALSO SHOW THE EFFECT OF YIELD UNCERTAINTY ON OPTIMAL BIDS AND THAT IT MAY NOT BE OPTIMAL FOR THE TRADE AGENT TO PREFER A MORE RELIABLE SELLER WHEN ALL OTHER SUPPLY PARAMETERS ARE THE SAME
638	MSOM , SUPPLY CHAIN SERVICE SCIENCE MANUFACTURING AND SERVICE OPERATIONS MANAGEMENT , MSOM , 
639	SECONDARY MARKETPLACE OF ONLINE RETAIL PLATFORMS
639	WE EXAMINE THE INCENTIVE AND THE IMPACT OF AN ONLINE RETAIL PLATFORM INTRODUCING A SECONDARY MARKET IN ADDITION TO THE EXISTING NEW PRODUCT MARKET
639	WE CONSIDER A SUPPLY CHAIN WITH A MANUFACTURER SELLING A NEW PRODUCT THROUGH THE PLATFORM UNDER RESELLING OR AGENCY CHANNEL
639	GIVEN EACH CHANNEL STRUCTURE , THE PLATFORM DETERMINES WHETHER OR NOT TO OPEN A SECONDARY MARKET WHERE CONSUMERS CAN RESELL OR PURCHASE USED PRODUCTS
639	IF SO , HE FURTHER DECIDES WHETHER TO OPERATE THE SECONDARY MARKET UNDER A CONSUMER TO CONSUMER STRATEGY OR A BUY BACK STRATEGY
639	WE DEVELOP A MULTI STAGE GAME THEORETIC MODEL , FULLY CHARACTERIZE THESE EQUILIBRIUM DECISIONS , AND SHOW HOW THEY DEPEND ON KEY FACTORS SUCH AS PRODUCT DURABILITY AND SERVICE COMMISSION RATE
639	WE ALSO EXAMINE THE IMPACT OF THE EXISTENCE OF THE SECONDARY MARKET ON THE MANUFACTURER , THE CONSUMER SURPLUS AND THE ENVIRONMENT
639	MSOM , SUPPLY CHAIN SHARING ECONOMY , INNOVATIVE MARKETPLACES , AND DATA 
640	DEVELOPING SMART SUPPLY CHAIN CONTRACTS USING DATA ANALYTICS AND BLOCK CHAIN MODELS
640	THE THREE MAIN ELEMENTS OF A SUPPLY CHAIN CONTRACT ARE PRICE , QUANTITY , AND SUPPLY LEAD TIME
640	SUPPLY CHAIN RISK IS A FUNCTION OF THESE THREE ELEMENTS AND MANAGERS ARE CONSTANTLY MONITORING THIS TO MINIMIZE SUPPLY RISKS
640	A SMART SUPPLY CHAIN CONTRACT IS DESIGNED TO MONITOR SEVERAL DATA PARAMETERS ACROSS THE SUPPLY CHAIN , AND THEN USE INTELLIGENT DECISION MODELS TO TRIGGER ACTIONS BEFORE THE PERCEIVED RISK CAUSES SUPPLY CHAIN DISRUPTIONS
640	THIS RESEARCH WILL USE A SURVEY METHOD TO , I , IDENTIFY RISK SENSITIVE DATA PARAMETERS THAT CAN BE TRACKED IN REAL TIME AT ONE OR MORE SUPPLY CHAIN NODES , EXAMPLES , INVENTORY LEVELS , MARKET PRICE DATA , , AND , II , DEVELOP DECISION TRIGGERS MODELS THAT RELATE THE TRACKED DATA TO RISK QUANTIFICATION MODELS
640	THE TRIGGER MODELS ARE AMENABLE TO BLOCKCHAIN ANALYSIS , AND THE RESEARCH WILL INVESTIGATE HOW THIS APPROACH WILL PROVIDE SUPERIOR RESULTS
640	MSOM , SUPPLY CHAIN SUPPLY CHAIN AND LOGISTICS IN PRACTICE ARTIFICIAL INTELLIGENCE BY ENHANCING TRUST AND TRANSPARENCY , ENABLING COLLABORATION , AND ALIGNING INCENTIVES 
641	RISK SHARING IN A TWO LEVEL SUPPLY CHAIN WITH VARIABLE CAPACITY AND RANDOM YIELD
641	THE RESEARCH ON PRODUCTION UNCERTAINTY IN THE SUPPLY CHAIN HOLDS TREMENDOUS SIGNIFICANCE IN THE COMPLEX AND INTERCONNECTED BUSINESS ENVIRONMENT
641	SUPPLY CHAINS ARE AFFECTED BY VARIOUS UNCERTAINTIES , INCLUDING DEMAND FLUCTUATIONS AND SUPPLY DISRUPTIONS
641	BASED ON THREE CENTRALIZED SUPPLY CHAINS AND THREE DECENTRALIZED SUPPLY CHAINS , THIS STUDY EXAMINES TWO TYPES OF PRODUCTION UNCERTAINTY , VARIABLE CAPACITY , VC , AND RANDOM YIELD , RY , , AND THE IMPACT THEY HAVE ON SUPPLY CAPABILITY , RELATIONSHIPS AMONG SUPPLY CHAIN MEMBERS , BEHAVIOR , AND PERFORMANCE
641	RY ARISES FROM IMPERFECT PROCESSES AND IS PREDICTABLE AND MEASURABLE
641	IN CONTRAST , VC IS CAUSED BY RANDOM FACTORS LIKE UNFORESEEN INTERRUPTIONS AND UNPLANNED MAINTENANCE , MAKING IT UNCONTROLLABLE
641	OUR RESEARCH FINDINGS INDICATE THAT VC AND RY DO NOT ALWAYS AFFECT PRODUCTION AND ORDERING DECISIONS IN CERTAIN CASES
641	MSOM , SUPPLY CHAIN SUPPLY CHAIN AND LOGISTICS IN PRACTICE MANUFACTURING AND SERVICE OPERATIONS MANAGEMENT , MSOM , 
642	EXCHANGE RATES AND INTERNATIONAL TRADE , INSIGHTS FROM SPATIAL PRICE EQUILIBRIUM MODELING WITH POLICY INSTRUMENTS VIA VARIATIONAL INEQUALITIES
642	THIS PAPER PRESENTS A MULTICOMMODITY INTERNATIONAL TRADE SPATIAL PRICE EQUILIBRIUM MODEL WITH EXCHANGE RATES AND POLICY INSTRUMENTS
642	THE MODEL ALLOWS FOR MULTIPLE TRADE ROUTES , DIFFERENT MODES OF TRANSPORTATION , AND TRANSPORT THROUGH DISTINCT COUNTRIES
642	WE IDENTIFY THE GOVERNING EQUILIBRIUM CONDITIONS AS A VARIATIONAL INEQUALITY PROBLEM IN PRODUCT PATH FLOWS
642	A CASE STUDY INSPIRED BY THE IMPACTS OF THE WAR AGAINST UKRAINE ON AGRICULTURAL TRADE FLOWS AND PRODUCT PRICES IS PRESENTED
642	THE MODELING AND ALGORITHMIC FRAMEWORK ALLOWS FOR QUANTIFYING THE EFFECTS OF EXCHANGE RATES , VARIOUS TRADE POLICIES , AND THE AVAILABILITY OF ROUTES ON SUPPLY AND DEMAND MARKET PRICES AND THE VOLUME OF TRADE FLOWS WITH IMPLICATIONS FOR FOOD SECURITY
642	MSOM , SUPPLY CHAIN SUPPLY CHAIN AND LOGISTICS IN PRACTICE OPT , NETWORK OPTIMIZATION
643	A STUDY OF COLD CHAIN PRACTICES ACROSS FOUR SECTORS
643	WE STUDY AND ANALYSE COLD CHAIN PRACTICES FOR PERISHABLE GOODS
643	INDIA HAS A TOTAL INSTALLED CAPACITY OF MN MT OF COLD STORAGE TO SUPPORT PERISHABLE GOODS SUPPLY CHAIN
643	DESPITE AN IMPRESSIVE PRODUCING CAPACITY IN DAIRY , MEAT , FISHERIES AND AGRICULTURE , THE COUNTRY HAS A CAPACITY TO STORE ONLY OF ITS TOTAL PRODUCTION OF ALL PERISHABLE GOODS
643	THIS RESULTS IN SIGNIFICANT LOSS IN PERISHABLE SUPPLY CHAIN YIELD
643	OVERALL MARKET SIZE FOR INDIAN COLD CHAIN IS PROJECTED TO A CAGR OF BY HOWEVER WITH A HIGHLY FRAGMENTED STRUCTURE , OF THE MARKET SHARE IS HELD BY TOP TEN PLAYERS
643	CLASSIFYING THE BUSINESS OF COLD CHAIN AS THREE VERTICALS , COLD STORAGE , COLD TRANSPORT , AND OTHER VALUE ADDED SERVICES , WE ANALYSE IN DEPTH THE PERISHABLE GOODS SUPPLY CHAIN AS FISHERIES , PHARMA , AGRI GOOD , AND DAIRY PRODUCTS , ALONG WITH STATE POLICIES
643	INFERENCES AND INSIGHTS ARE DISCUSSED
643	MSOM , SUPPLY CHAIN SUPPLY CHAIN AND LOGISTICS IN PRACTICE SHARING ECONOMY , INNOVATIVE MARKETPLACES , AND DATA 
644	DATA SECURITY , PRIVACY , AND INTEROPERABILITY WITHIN DIGITAL HEALTHCARE SUPPLY CHAIN ECOSYSTEMS
644	THE DIGITAL TRANSFORMATION OF HEALTHCARE SUPPLY CHAINS BRINGS NUMEROUS BENEFITS , BUT IT ALSO INTRODUCES CHALLENGES AND CONSIDERATIONS RELATED TO DATA SECURITY , PRIVACY , AND INTEROPERABILITY
644	THIS RESEARCH AIMS TO EXPLORE THE COMPLEXITIES AND IDENTIFY BEST PRACTICES IN THE HEALTHCARE SUPPLY CHAIN
644	FURTHERMORE , THIS RESEARCH SEEKS TO PROVIDE VALUABLE INSIGHTS AND RECOMMENDATIONS FOR HEALTHCARE ORGANIZATIONS TO ADDRESS THESE CRITICAL ASPECTS OF DIGITAL SUPPLY CHAIN MANAGEMENT
644	MSOM , SUPPLY CHAIN SUPPLY CHAIN AND LOGISTICS IN PRACTICE TECHNOLOGY , INNOVATION MANAGEMENT AND ENTREPRENEURSHIP
645	SUBSTITUTION BASED PORTFOLIO OPTIMIZATION
645	WITH LIMITED CAPACITY , BUDGETARY , AND OPERATIONAL CONSTRAINTS , RETAILERS ARE OFTEN UNABLE TO PRODUCE AND OFFER ALL ITEMS IN THE PORTFOLIO AND THUS NEED TO DECIDE ON THE SUBSET THAT BEST MEETS THE CUSTOMERS EXPECTATIONS AND MAXIMIZES PROFIT
645	ONE APPROACH IS TO FOCUS ON THE MOST POPULAR ITEMS BASED ON HISTORICAL OR FORECASTED DEMANDS , BUT DOING SO FAILS TO ADEQUATELY MODEL CUSTOMER BEHAVIOR ESPECIALLY IN REGARD TO SUBSTITUTION
645	IN THIS WORK , WE STUDY OPTIMIZATION OF A PRODUCT PORTFOLIO TO MAXIMIZE THE EXPECTED PROFIT OVER THE PLANNING HORIZON
645	WE PROVIDE EMPIRICAL RESULTS FOR A CASE STUDY WITH OUR INDUSTRY PARTNER TO COMPARE THE RESULTING PRODUCT PORTFOLIO AND EXPECTED PROFIT WITH AND WITHOUT CONSIDERING THE SUBSTITUTION BEHAVIOR
645	MSOM , SUPPLY CHAIN SUPPLY CHAIN AND LOGISTICS IN PRACTICE 
646	VALUE OF INFORMATION AND FLEXIBILITY ANALYSIS FOR SUPPLY CHAIN NETWORK DESIGN UNDER UNCERTAINTY
646	IN THIS PAPER , WE FORMULATE AN OPTIMAL INFORMATION GATHERING STRATEGY , IGS , TO IDENTIFY WHICH UNCERTAINTIES IN THE SUPPLY CHAIN NETWORK DRIVE OUR DECISIONS
646	EXISTING APPROACHES CONSIDER UNCERTAINTIES , BUT DO NOT CONSIDER THE BENEFIT OF RESOLVING THEM
646	BASED ON STYLIZED , NUMERICAL , AND CASE STUDY RESULTS , WE SHOW A SIGNIFICANT VALUE OF OPTIMAL IGS
646	AS A NON MONOTONE NON SUBMODULAR MINIMIZATION PROBLEM , WE SOLVE THE PROBLEM WITH AN ALGORITHM WHICH ACHIEVES A CONSTANT APPROXIMATION GUARANTEE
646	MSOM , SUPPLY CHAIN TSL , FACILITY LOGISTICS DECISION ANALYSIS SOCIETY
647	SCATTERED STORAGE ASSIGNMENT TO MINIMIZE PICKING TRAVEL DISTANCES FOR LARGE ORDER LINES I E COMMERCE IS CHANGING THE WAY PEOPLE CONSUME
647	USUALLY , ONLY A FEW ITEMS ARE DEMANDED IN SMALL QUANTITIES IN THESE ONLINE STORES
647	FOR THIS REASON , MANY WAREHOUSES USE THE POLICY OF SCATTERED STORAGE TO PLACE ITEMS IN CLOSE PROXIMITY AND SPEED UP THE PICKING PROCESS
647	HOWEVER , THE QUESTION IS WHETHER SCATTERED STORAGE IS ALSO A GOOD STRATEGY FOR AN ATYPICAL ORDER THAT INVOLVES LARGE ORDER LINES , AS IN THE OMNICHANNEL STRATEGY WHERE INDIVIDUAL CUSTOMERS AND PHYSICAL STORES NEED TO BE SERVED FROM THE SAME WAREHOUSE
647	THE IDEA IS TO FIGURE OUT UP TO WHAT RATIO OF LARGE ORDER LINES SCATTERED STORAGE IS STILL A PROMISING STRATEGY
647	TO ENABLE STORAGE OF LARGE QUANTITIES , AN ADAPTATION OF SCATTERED STORAGE WITH PAIRWISE MINIMIZATION OF DISTANCES , SSA SPD , IS PRESENTED
647	PICKING ROUTING RESULTS SHOW THAT SSA SPD IS A GOOD STORAGE POLICY COMPARED TO TRADITIONAL STORAGE POLICIES I 
647	MSOM , SUPPLY CHAIN TSL , FACILITY LOGISTICS EBUSINESS
648	WHO GETS THE WHIP
648	HOW SUPPLIER DIVERSIFICATION INFLUENCES BULLWHIP EFFECT IN A SUPPLY CHAIN
648	EMERGENT TECHNOLOGIES , SUCH AS THE BLOCKCHAIN , ARE ENABLING UNPRECEDENTED COORDINATION ACROSS FIRMS IN SUPPLY CHAINS , SC , 
648	FIRM DECISION MAKERS ULTIMATELY ARE GOING TO NEED TO UNDERSTAND HOW THEY CAN CONTROL , AND OPTIMIZE , SUCH A NETWORK OF RELATIONSHIPS
648	HOWEVER , CURRENT APPROACHES TO THE STUDY OF SC LEVEL BEHAVIOR TYPICALLY ASSUME A FOCAL FIRM , AND THE MODELING OF SC BEHAVIOR IS USUALLY LIMITED TO SINGLE PRODUCT SERIAL NETWORKS
648	THIS PAPER AIMS TO UNDERSTAND HOW THE BULLWHIP EFFECT PROPAGATES AND INTENSIFIES THROUGHOUT A SC WITH MULTIPLE SUPPLIERS
648	WE FIND THAT SC THE STRUCTURE HAS TO BE ACCOMPANIED WITH A DYNAMIC POLICY TO SEE CHANGES IN DEMAND DISTURBANCES
648	WE ALSO EXPLICATE A NOVEL SC MODEL THAT CAN BE USED TO TEST THE IMPLICATIONS OF OUR MAIN RESULT , DIVERSIFYING A FIRM S SUPPLIER BASE HAS THE POTENTIAL TO AMPLIFY DISTURBANCES MORE QUICKLY
648	MSOM , SUPPLY CHAIN ARGUES AN IMPORTANT IMPLICATION FOR SUPPLY CHAIN MANAGEMENT BECAUSE OF BLOCKCHAIN TECHNOLOGIES 
649	STATIC AND DYNAMIC OPTIMIZATION FOR THE JOINT REPLENISHMENT PROBLEM
649	ORGANIZATIONS FREQUENTLY FACE STOCHASTIC SEQUENTIAL DECISION PROBLEMS AND MUST COME UP WITH DECISION POLICIES
649	THOSE PROBLEMS CAN BE DIVIDED INTO STATIC , MADE ONCE , E G CAPACITY , DELIVERY SCHEDULE , AND DYNAMIC DECISIONS , MADE FREQUENTLY , E G REPLENISHMENT , ROUTING , 
649	THE STATIC DECISION IS OFTEN MADE IN ISOLATION , NOT CONSIDERING THE FUTURE IMPACT ON THE DYNAMIC POLICY BR OUR RESEARCH REVOLVES AROUND COMBINING STATIC AND DYNAMIC PROBLEM SOLVING METHODS , MATHEMATICAL PROGRAMMING , APPROXIMATE DYNAMIC PROGRAMMING , REINFORCEMENT LEARNING , AND APPLYING THEM ON USE CASES FROM RETAIL OPERATIONS AND OR TRANSPORTATION
649	IN THIS WORK , WE AIM TO FIND THE BEST DELIVERY SCHEDULE IN A JOINT REPLENISHMENT PROBLEM , ONE WAREHOUSE MULTIPLE RETAILERS SETTING
649	MSOM , SUPPLY CHAIN 
650	THE VALUE OF BUYER FINANCING IN SUPPLY CHAINS WITH UNCERTAIN RAW MATERIAL PRICE 
650	THIS PAPER STUDIES A SUPPLY CHAIN SUBJECT TO DISRUPTION RISK , WHERE A CAPITAL ABUNDANT RETAILER SOURCES FROM A CAPITAL CONSTRAINED SUPPLIER AND OFFERS THE SUPPLIER BUYER FINANCING
650	THE SUPPLIER PROCEDURES THE RAW MATERIAL TO MANUFACTURE A FINAL PRODUCT , WHICH IS SOLD TO THE RETAILER , AND THE INPUT PRICE OF THE RAW MATERIAL FOLLOWS A GEOMETRIC BROWNIAN MOTION
650	WE CHARACTERIZE THE OPTIMAL PROCUREMENT STRATEGY UNDER DIFFERENT FINANCING SCHEMES , INCLUDING BANK FINANCING AND THE BUYER FINANCING
650	WE COMPARE THESE TWO FINANCING SCHEMES AND FIND THAT THE RETAILER MAY PLACE EARLIER UNDER BUYER FINANCING THAN UNDER BANK FINANCING WHEN THE INPUT PRICE HAS A DOWNWARD TREND AND THE PROBABILITY OF DISRUPTION IS SUFFICIENT LOW , AND THE FIRMS FINANCING PREFERENCES MAY BE INFLUENCED BY THE PROBABILITY OF DISRUPTION , THE DRIFT , THE CURRENT INPUT PRICE AND THE VOLATILITY OF THE GBM
650	MSOM , SUPPLY CHAIN 
651	HOW TO ADJUST CONSUMER SUBSIDIES OVER TIME
651	WE CONSIDER A SYSTEM INCLUDING A CENTRAL PLANNER AND A RETAILER SELLING A SOCIALLY RESPONSIBLE PRODUCT
651	THE CENTRAL PLANNER REGISTERS SUBSIDIES TO THE RETAILER TO ENCOURAGE THE ADOPTION OF THE PRODUCT
651	WE EXPLORE THE CHANGE IN THE CONSUMER SUBSIDIES OVER TIME WITH RESPECT TO CHANGES IN DEMAND , ADOPTION LEVEL AND BUDGET CONSIDERATION
651	MSOM , SUPPLY CHAIN 
652	OPTIMAL FULFILLMENT AND TRANSSHIPMENT STRATEGIES IN OMNICHANNEL RETAILING WITH CROSS CHANNEL RETURNS
652	TO SATISFY CUSTOMER DEMAND AND MAINTAIN THEIR COMPETITIVENESS , RETAILERS ARE EXPLORING WAYS TO EXPLOIT RISING ONLINE SALES , SUCH AS BY INVESTING IN CROSS CHANNEL STRATEGIES
652	ADDRESSING THE CHALLENGES IN OPERATING BOTH THE ONLINE AND OFFLINE CHANNELS EFFICIENTLY , IN THIS STUDY , WE BUILD A DYNAMIC PROGRAMMING MODEL AND INVESTIGATE OPTIMAL FULFILLMENT AND TRANSSHIPMENT STRATEGIES IN OMNICHANNEL RETAILING WITH CROSS CHANNEL RETURNS
652	WITH THE OBJECTIVE OF MAXIMIZING THE TOTAL PROFIT OF THE RETAILER , WE INVESTIGATE , I , FROM WHERE TO FULFILL A HOME DELIVERY ORDER WHEN IT OCCURS , , II , WHEN AND HOW TO TRANSSHIP RETURNS TO BALANCE INVENTORY
652	IN ORDER TO DEVELOP THE OPTIMAL OMNICHANNEL FULFILLMENT AND TRANSSHIPMENT POLICY , WE ACCOMMODATE THE UNCERTAINTY IN THE CUSTOMER DEMAND , RETURNS , AND THE PRODUCT PER UNIT COST OF HANDLING , SHIPPING , TRANSSHIPPING AND MANAGEMENT
652	MSOM , SUPPLY CHAIN 
653	THE BENEFIT OF COMMITMENT POWER IN A DUAL CHANNELSUPPLY CHAIN WITH CHANNEL DIFFERENTIATION
653	COMMITMENT POWER IS VALUABLE IN BUSINESS INTERACTIONS , ENHANCING RELIABILITY AND COLLABORATION
653	HOWEVER , OUR RESEARCH SHOWS COMMITMENT POWER CAN NEGATIVELY IMPACT PROFITABILITY
653	WE INVESTIGATE ITS EFFECTS IN A DUAL CHANNEL SETTING , QUESTIONING IF COMMITTING TO A PRICE IS ALWAYS OPTIMAL AND IF IT BENEFITS BOTH FIRMS AND THE SUPPLY CHAIN
653	WE STUDY A MANUFACTURER AND RETAILER COMPETING ON CHANNEL PRICES
653	FINDINGS REVEAL THAT THE FIRM S PRICING STRATEGY AND COMMITMENT POWER S BENEFITS DEPEND ON THE OTHER FIRM S COMMITMENT POWER
653	IF LACKING , THE FIRM SHOULD COMMIT TO THE EQUILIBRIUM PRICE
653	YET , IF THE OTHER FIRM HAS COMMITMENT POWER , NOT COMMITTING MAY BE ADVANTAGEOUS
653	COMPARING DUAL CHANNEL AND INTEGRATED SUPPLY CHAINS , EFFICIENCY IS HIGHEST WHEN THE MANUFACTURER HOLDS COMMITMENT POWER AND LOWEST WHEN BOTH LACK IT
653	MSOM , SUPPLY CHAIN 
654	BUYING FROM A COMPETITOR , A MODEL OF KNOWLEDGE SHARING AND INNOVATION
654	MANY FIRMS BUY A PRODUCTION INPUT FROM A COMPETITOR
654	WE DEVELOP A GAME THEORY MODEL IN WHICH A FIRM CAN BUY AN INPUT FROM A COMPETITOR OR A THIRD PARTY IN EACH PERIOD , AND IN ORDER TO INNOVATE , THE FIRM MUST INVEST IN IMPROVING THE INPUT AND MUST SHARE THE RESULTING KNOWLEDGE WITH ITS CHOSEN SUPPLIER
654	WE FIND THAT BUYING FROM THE COMPETITOR , , , MITIGATES PRICE COMPETITION IN THE CONSUMER MARKET , AND , , PUTS THE COMPETITOR IN A STRONGER NEGOTIATING POSITION IN THE SECOND PERIOD IF THE FOCAL FIRM INVESTS IN INNOVATION
654	IN EQUILIBRIUM , IF THE VALUE OF THE INNOVATION IS SUFFICIENTLY LOW OR SUFFICIENTLY HIGH , THE FIRM BUYS FROM ITS COMPETITOR
654	HOWEVER , IF THE VALUE OF INNOVATION LIES IN AN INTERMEDIATE RANGE , AND THERE IS SUFFICIENT HORIZONTAL PRODUCT DIFFERENTIATION , THEN THE FIRM BUYS FROM THE THIRD PARTY TO ENSURE INNOVATION OCCURS
654	MSOM , SUPPLY CHAIN 
655	FLOW OF INFORMATION AND ITS PRESERVATION
655	IN THIS RESEARCH , WE INVESTIGATE FLOW OF INFORMATION AMONG MEMBERS OF A SUPPLY CHAIN AND PRESERVATION OF SHARED AND USED INFORMATION
655	SIMULATION OF OUR THEORETICAL MODEL IS ALSO DISCUSSED
655	MSOM , SUPPLY CHAIN 
656	INFORMATION SHARING OF TWO COMPETING RETAIL PLATFORMS
656	WE USE A MULTI STAGE GAME TO MODEL THE SETTING OF ONE MANUFACTURER SELLING PRODUCTS VIA TWO COMPETING RETAIL PLATFORMS
656	THE MANUFACTURER CHOOSES THE OPERATING MODES , RESELLER OR MARKETPLACE
656	THE RETAIL PLATFORMS DECIDE WHETHER TO SHARE DEMAND INFORMATION WITH THE MANUFACTURER
656	WE FULLY CHARACTERIZE THE EQUILIBRIUM DECISIONS AND SHOW HOW THEY DEPEND ON THE COMMISSION RATE OF THE AGENCY CHANNEL , CHANNEL SUBSTITUTABILITY , AND INFORMATION ACCURACY
656	MSOM , SUPPLY CHAIN 
657	BIG DATA ANALYTICS IN LOGISTICS AND SUPPLY CHAIN MANAGEMENT , CERTAIN INVESTIGATIONS FOR RESEARCH AND APPLICATIONS
657	REALIZING THE IMPORTANCE OF BIG DATA BUSINESS ANALYTICS , BDBA , , WE REVIEW AND CLASSIFY THE LITERATURE ON THE APPLICATION OF BDBA ON LOGISTICS AND SUPPLY CHAIN MANAGEMENT AND PROPOSE A MATURITY FRAMEWORK , BASED ON FOUR CAPABILITY LEVELS
657	MSOM , SUPPLY CHAIN 
658	ENVIRONMENTAL DISCLOSURE IN SUPPLY CHAINS
658	FIRMS IN SUPPLY CHAINS HAVE INCREASINGLY ADOPTED ENVIRONMENTAL DISCLOSURE TO IMPROVE ENVIRONMENTAL PERFORMANCE
658	THIS RESEARCH STUDIES THE SPILLOVER EFFECT OF A FIRM IN DISCLOSING ITS ENVIRONMENTAL PERFORMANCE ON ITS SUPPLIERS DECISION TO DO THE SAME
658	THE FIRM S DISCLOSURE CREATES BOTH A PRESSURE TO DISCLOSE AND AN OPPORTUNITY TO FREERIDE
658	USING PANEL DATA AND ECONOMETRIC ANALYSIS , WE INVESTIGATE THE OUTCOME OF THIS TRADEOFF IN SUPPLY CHAINS
658	MSOM , SUSTAINABLE OPERATIONS ENRE , ENVIRONMENT AND SUSTAINABILITY MSOM , SUPPLY CHAIN
659	THE IMPACT OF REPLENISHMENT STRATEGIES FOR BASKET OF GOODS CONSUMERS TO REDUCE GHG EMISSIONS ASSOCIATED WITH FOOD WASTE
659	ON AVERAGE , OF THE FOOD PRODUCED IS WASTED
659	THIS IMPLIES THAT , OF ALL THE GREENHOUSE GASSES ASSOCIATED WITH THE PRODUCT LIFECYCLE , FOOD WASTE DISPROPORTIONATELY INCREASES THE ENVIRONMENTAL IMPACT OF THE SUPPLY CHAIN
659	IN THIS PAPER , WE STUDY DIFFERENT ALTERNATIVES TO REDUCE FOOD WASTE , PARTICULARLY AT THE CONSUMER LEVEL , THE LEVEL WITH THE HIGHEST RATE OF FOOD WASTE COMPARED TO OTHER STAGES OF THE SUPPLY CHAIN
659	VIA CONSIDERING DIFFERENT REPLENISHMENT STRATEGIES , WE PRESENT AN ANALYTICAL MODEL THAT DEFINES OPTIMAL POLICIES FOR CONSUMERS TO BUY PRODUCTS FROM THE BASKET OF GOODS FROM BOTH RETAIL FORMATS , THE MODERN AND THE TRADITIONAL CHANNEL
659	IN MEXICO , OUR RESULTS PROVIDE MANAGERIAL INSIGHTS INTO THE POLICIES THAT DECREASE ENVIRONMENTAL IMPACTS BY BALANCING THE EMISSIONS ASSOCIATED WITH FOOD WASTE , TRANSPORTATION , AND REFRIGERATION , AMONG OTHERS
659	MSOM , SUSTAINABLE OPERATIONS ENRE , ENVIRONMENT AND SUSTAINABILITY SOCIALLY RESPONSIBLE AND SUSTAINABLE OPERATIONS
660	SERVICIZING MODELS WITH PRODUCT REMANUFACTURING REGARDING UNCERTAIN COLLECTION QUALITY
660	SERVICIZING BUSINESS MODELS HAVE BEEN WIDELY ADOPTED BY MANUFACTURERS TO PROVIDE MAINTAINABLE SERVICE ESPECIALLY WHEN PRODUCTS ARE NOT FULLY FUNCTIONAL
660	BUT THE UNCERTAIN QUALITY OF COLLECTED CORES REDUCES THE ECONOMIC BENEFIT OF REMANUFACTURING PROCESS
660	TO INVESTIGATE THE INFLUENCE OF QUALITY UNCERTAINTY ON SERVICIZING , FIRST , WE PROPOSE NEW COLLECTION FUNCTIONS WITH CUSTOMERS HETEROGENEOUSLY PRIORITIZING MAINTAINABLE SERVICE IN A TWO PERIOD MODEL , IN WHICH THE MANUFACTURER CHOOSE TO PROVIDE SERVICIZING , PURCHASING , OR LEASING BUSINESS
660	SECOND , THE COLLECTION RATES AND PROFITS OF MANUFACTURERS CHOOSING DIFFERENT BUSINESS MODELS ARE COMPARED UNDER QUALITY UNCERTAINTY AND REMANUFACTURING OF WASTED PRODUCTS
660	WE FIND OUT THE BEST BUSINESS MODEL CHOICE UNDER DIFFERENT QUALITY SCENARIO AND IMPACT OF UNCERTAIN QUALITY ON SERVICIZING EFFICIENCY
660	MSOM , SUSTAINABLE OPERATIONS MSOM , SERVICE OPERATIONS MANUFACTURING AND SERVICE OPERATIONS MANAGEMENT , MSOM , 
661	SUPPLY CHAIN RELATIONSHIP DEPENDENCIES AND CIRCULAR ECONOMY PERFORMANCE , THE CONTINGENCY ROLE OF DIGITALIZATION CAPABILITY
661	DRAWING ON RESOURCE DEPENDENCE THEORY , WE INVESTIGATED HOW THE DEGREE OF DEPENDENCE OF FOCAL FIRMS ON SUPPLIERS AND CUSTOMERS AFFECTS THEIR CE PERFORMANCE
661	EMPLOYING HIERARCHICAL LINEAR MODELING ON A PANEL DATASET OF LISTED CHINESE MANUFACTURERS DURING , WE FOUND THAT THE MORE DEPENDENT A FIRM IS ON ITS MAJOR SUPPLIERS AND CUSTOMERS , THE HIGHER THE SUPPLIER AND CUSTOMER CONCENTRATIONS , , THE WORSE ITS CE PERFORMANCE
661	IN ADDITION , WE UTILIZED DATA MINING TECHNIQUES TO CAPTURE MANUFACTURERS DIGITALIZATION CAPABILITIES
661	WE EXAMINED HOW DIGITALIZATION EMPOWERS MANUFACTURERS TO ALLEVIATE POWER IMBALANCES IN SUPPLY CHAIN DEPENDENCIES
661	OUR RESULTS SUGGEST THAT THE MANUFACTURERS DIGITALIZATION CAPABILITY SIGNIFICANTLY WEAKENS THE NEGATIVE IMPACTS OF SUPPLIER AND CUSTOMER CONCENTRATIONS ON CE PERFORMANCE
661	MSOM , SUSTAINABLE OPERATIONS MSOM , SUPPLY CHAIN BEHAVIORAL OPERATIONS MANAGEMENT
662	SUSTAINABLE SUPPLY CHAIN MANAGEMENT , A CASCADE OF EMISSION BASED PRODUCTION AND INVENTORY CONTROL SYSTEM , EPICS , 
662	SUSTAINABILITY REQUIRES TRANSITIONING FROM A TRADITIONAL GOAL ORIENTED POINT OF VIEW TO A PROCESS BASED APPROACH , AS IT IS SEEN AS AN UNENDING PROCESS DEFINED BY NEITHER FIXED GOALS NOR MEANS OF ACHIEVING THEM
662	SUCH A TRANSITION NEEDS ANALYSIS OF A COMPLEX SOCIO ECONOMIC SYSTEM WHERE A FEEDBACK BASED APPROACH FOR NON LINEAR AND ORGANIC THINKING ENHANCES AS THE UNDERSTANDING OF THE SYSTEM AS A CONTINUOUS IMPROVEMENT PROCESS
662	A DECISION SUPPORT SYSTEM BASED ON REAL TIME DATA ENSURES PERFORMANCE CONTROLLABILITY FROM SYSTEM POLICIES
662	OUR PROPOSED WORK USES AN EMISSION BASED PRODUCTION AND INVENTORY CONTROL SYSTEM , EPICS , FOR THE SUPPLY CHAIN FOR THE DECISION PROCESS ON SIMULATION BASED DATA
662	THE IDEA IS TO DEVELOP ROBUST SYSTEM POLICIES AS SUSTAINABILITY INITIATIVES TO MINIMISE SYSTEM EMISSIONS , ENSURE BETTER CUSTOMER SERVICE LEVELS , AND REDUCE SUPPLY CHAIN COSTS
662	MSOM , SUSTAINABLE OPERATIONS MSOM , SUPPLY CHAIN SIMULATION SOCIETY
663	BLOCKCHAIN ENABLED TRACEABILITY OF GREENHOUSE GAS EMISSIONS , EVIDENCE FROM MOROCCAN AGRICULTURE PRODUCTION
663	CLIMATE CHANGE IS A MAJOR GLOBAL ISSUE IMPACTING THE FOOD SUPPLY CHAIN INDUSTRY
663	MANY COMPANIES ARE TURNING TO INNOVATIVE TECHNOLOGIES LIKE BLOCKCHAIN TO INCREASE TRANSPARENCY AND TRACEABILITY AND PROMOTE SUSTAINABILITY IN THEIR SUPPLY CHAINS
663	THIS STUDY PROPOSES BLOCKCHAIN BASED TRACEABILITY SMART CONTRACTS TO TRACK AND TRACE GREENHOUSE GAS EMISSIONS , GHG , IN THE MOROCCAN OLIVES SUPPLY CHAIN FROM THE FARM TO THE PORT IN THREE STAGES , CULTIVATION , HARVESTING , AND SHIPPING
663	MSOM , SUSTAINABLE OPERATIONS MSOM , SUPPLY CHAIN 
664	FROM LINEAR TO CIRCULAR ECONOMY , A NEWSVENDOR S PERSPECTIVE
664	THE CIRCULAR ECONOMY PROMISES TO REDUCE WASTE AND ENABLE US TO LIVE IN A SUSTAINABLE MANNER
664	IN THIS WORK , WE EXAMINE THE TRANSITION FROM THE CURRENT LINEAR ECONOMY TO THE CIRCULAR ECONOMY THROUGH THE LENS OF A NEWSVENDOR MODEL
664	THE INSIGHTS WE PROVIDE MAY BE SURPRISING BUT WILL INFORM REGULATORS AND FIRMS ON THE IMPACT OF THE TRANSITION FROM THE LINEAR TO THE CIRCULAR ECONOMY
664	MSOM , SUSTAINABLE OPERATIONS SOCIALLY RESPONSIBLE AND SUSTAINABLE OPERATIONS ENRE , ENVIRONMENT AND SUSTAINABILITY
665	WHEN DOING GOOD MAY BACKFIRE , SMALLHOLDER FARMER SELECTION INTO YIELD IMPROVEMENT PROGRAMS
665	IN AGRICULTURAL INTENSIVE ECONOMIES , MANUFACTURERS OFTEN HELP SMALLHOLDER FARMERS IMPROVE THEIR YIELDS THROUGH TRAINING AND YIELD IMPROVEMENT PROGRAMS
665	HOWEVER , AND PERHAPS PARADOXICALLY , SOME FARMERS FEEL THAT THESE PROGRAMS CAN LOWER THEIR PROFIT , IN PART DUE TO A DECREASE IN COMMODITY PRICES
665	USING A COURNOT MODEL , WE SHOW THAT A , THESE PROGRAMS CAN PUSH PRICES DOWN , WHICH MAY INDEED DECREASE THE PROFITS OF SOME FARMERS , B , THE OBJECTIVES OF MINIMIZING MARKET PRICES AND PROTECTING FARMER WELL BEING MIGHT BE CONFLICTING , AND C , CERTIFYING MORE EFFICIENT FARMERS MAY PERFORM WELL IN TERMS OF BOTH INDIVIDUAL AND AGGREGATE FARMER WELL BEING
665	MSOM , SUSTAINABLE OPERATIONS SOCIALLY RESPONSIBLE AND SUSTAINABLE OPERATIONS FAIRNESS IN OPERATIONS
666	STRATEGIC PRICING AND INVESTMENT IN ENVIRONMENTAL QUALITY BY AN INCUMBENT FACING A GREENWASHER ENTRANT
666	WE EXAMINE HOW GREENWASHING AFFECTS THE STRATEGIES AND OUTCOMES OF COMPANIES AND CONSUMERS
666	WE DEVELOP A TWO STAGE GAME , WHERE A MONOPOLIST SETS PRICE AND INVESTS IN ENVIRONMENTAL QUALITY IN THE FIRST STAGE , AND COMPETES WITH A NEW ENTRANT IN THE SECOND STAGE
666	THE INCUMBENT COMPANY IS GENUINELY ENVIRONMENTALLY FRIENDLY , WHILE THE NEW ENTRANT MAY USE DECEPTIVE GREEN MARKETING
666	WE ASSUME THAT ONLY INEXPERIENCED CONSUMERS CAN BE INFLUENCED BY GREENWASHING , AND CONSIDER TWO IMPORTANT DYNAMIC FACTORS , I E , A CHANGE IN COMPETITIVE STRUCTURE AND A LEARNING EFFECT IN THE MARKET
666	WE INVESTIGATE THE CONDITIONS UNDER WHICH GREENWASHING IS PROFITABLE FOR THE NEW ENTRANT , THE WAYS IN WHICH THE INCUMBENT COMPANY RESPONDS TO IT , AND THE IMPACT OF GREENWASHING ON THE ENVIRONMENT AND CONSUMERS
666	MSOM , SUSTAINABLE OPERATIONS SOCIALLY RESPONSIBLE AND SUSTAINABLE OPERATIONS MANUFACTURING AND SERVICE OPERATIONS MANAGEMENT , MSOM , 
667	FINANCING RISKY SUPPLIER , GREEN TECHNOLOGY INVESTMENT AND REGULATION
667	AS SUSTAINABILITY PLAYS A PROMINENT ROLE EVERYWHERE , SUPPLY CHAIN DISRUPTION FREQUENTLY OCCURS BECAUSE OF SUPPLIER S VIOLATION TO ENVIRONMENTAL REGULATION
667	IN A SUPPLY CHAIN CONSIST OF A SUPPLIER AND A MANUFACTURE , BOTH OF THEM TRY TO INVEST IN GREEN TECHNOLOGY TO REDUCE THE RISK OF REGULATION VIOLATION
667	HOWEVER , THIS INVESTMENT AGGRAVATES THE SUPPLIER S FINANCIAL PROBLEM WHICH IS A SIGNIFICANT RISK OF SUPPLY DISRUPTION AS WELL
667	IN THIS PAPER , WE EXPLORE HOW A MANUFACTURE FINANCIALLY SUBSIDIZES SUPPLIER TO MITIGATE THE DISRUPTION RISK FROM REGULATION VIOLATION AND BANKRUPTCY
667	MEANWHILE , WE WILL SHOW THAT AN AGGRESSIVE REGULATION IS NOT ALWAYS ENCOURAGING INVESTMENT ON GREEN TECHNOLOGY
667	MSOM , SUSTAINABLE OPERATIONS SOCIALLY RESPONSIBLE AND SUSTAINABLE OPERATIONS MSOM , SUPPLY CHAIN
668	ALL YOU NEED IS GREEN A TEXT MINING ANALYSIS OF THE IMPACT OF GREEN MANUFACTURING ORIENTATION
668	HARNESSING AND ANALYZING DATA IS AN OPPORTUNITY FOR INCREASED SUSTAINABILITY AND A KEY ELEMENT OF GREEN MANUFACTURING , GM , 
668	WE STRIVE TO UNDERSTAND BETTER THE RELATIONSHIP BETWEEN GM ORIENTATION , GMO , AND ECONOMIC AND ENVIRONMENTAL PERFORMANCE
668	THEREFORE , WE MEASURE GMO THROUGH A QUANTITATIVE APPROACH , USING TEXT MINING AND COUNTING RELEVANT WORDS IN MD A SECTIONS OF ANNUAL REPORTS FROM S P MANUFACTURING COMPANIES
668	OUR PRELIMINARY RESULTS INDICATE A NEGATIVE CORRELATION BETWEEN A COMPANY S GMO AND CO EMISSIONS
668	FURTHER , WE FIND A CONVEX CURVILINEAR , U SHAPED , CORRELATION WITH TOBIN S Q HENCE , IT SEEMS ENVIRONMENTALLY BENEFICIAL FOR COMPANIES TO IMPLEMENT GM ELEMENTS , SUCH AS AI , TO INVESTIGATE BIG DATA
668	OUR STUDY PROPOSES A NEW METHODOLOGICAL APPROACH FOR GMO MEASUREMENT , WHILE OUR EMPIRICAL FINDINGS ADD TO THE NATURAL RESOURCE BASED VIEW
668	MSOM , SUSTAINABLE OPERATIONS SOCIALLY RESPONSIBLE AND SUSTAINABLE OPERATIONS MSOM , TECHNOLOGY , INNOVATION AND ENTREPRENEURSHIP
668	WE SEE POTENTIAL OF HARNESSING DATA AS A KEY ELEMENT OF GMO TO POSITIVELY IMPACT ENVIRONMENTAL KPIS 
669	THE REAL EFFECT OF AMAZON S CLIMATE PLEDGE , ANALYSIS OF FIRM EMISSION LEVEL AND FINANCIAL MARKET FEATURES
669	THE INCREASING CONCERNS ABOUT CLIMATE CHANGE HAVE PROMPTED MANY FIRMS TO ADOPT ENVIRONMENTAL COMMITMENTS TO REDUCE THEIR CARBON EMISSIONS
669	IT REMAINS TO BE STUDIED HOW FIRM EMISSION LEVEL AND FINANCIAL MARKET FEATURES CHANGE UPON MAKING A GREEN PROMISE
669	USING AMAZON S CLIMATE PLEDGE AS AN EXAMPLE , WE BUILD AN EVENT STUDY TO EXAMINE HOW FIRM EMISSION LEVEL AND FINANCIAL MARKET FEATURES LIKE RETURN , VOLATILITY , ETC , CHANGE WHEN FIRMS ANNOUNCE THEIR PARTICIPATION IN THE PLEDGE , AND HOW THE CHANGES VARY AMONG DIFFERENT FIRM OWNERSHIP TYPE , INDUSTRY SECTOR , ETC
669	MSOM , SUSTAINABLE OPERATIONS SOCIALLY RESPONSIBLE AND SUSTAINABLE OPERATIONS 
669	AMAZON S CLIMATE PLEDGE DATA , FIRM FINANCIAL MARKET DATA , FIRM EMISSION DATA 
670	THE IMPACT OF DIFFERENT CONTRACTING MECHANISMS ON THE PERFORMANCE OF REUSABLE PACKAGING SYSTEMS
670	IMPLEMENTING FUNCTIONING REUSABLE PACKAGING SYSTEMS THAT GUARANTEE A SMOOTH CIRCULATION OF THE REUSABLES REQUIRES THE COLLABORATION AND COORDINATION OF VARIOUS STAKEHOLDERS IN A SUPPLY CHAIN
670	WE INVESTIGATE THE IMPACT OF DIFFERENT CONTRACTUAL AGREEMENTS IN A TWO STAGE SUPPLY CHAIN CONSISTING OF TWO PRODUCERS WITH DIFFERENT PRODUCTS AND A WHOLESALER , WHO HAS TO INVEST IN SORTING CAPACITY TO MANAGE THESE RETURN RATES
670	WE DEVELOP A GAME THEORETICAL MODEL AND STUDY DIFFERENT TYPES OF CONTRACTS AND THEIR IMPACT ON THE PERFORMANCE OF THE REUSE SYSTEM ALONG DIFFERENT DIMENSIONS , COST AND RETURN RATES , 
670	MSOM , SUSTAINABLE OPERATIONS 
671	CROSS PLATFORM VALUE CO CREATION AND CO DESTRUCTION , THE CASE OF INFORMATION AND EXPLOIT VIDEOS ON YOUTUBE
671	WE STUDY THE INTERACTIONS BETWEEN TWO DIGITAL PLATFORMS , MOBILE APPS AND YOUTUBE , TO SHOW HOW CONTENT PUBLISHED ON YOUTUBE INFLUENCES USERS MOBILE APP ENGAGEMENT AND THE APP S REVENUE GENERATION
671	SPECIFICALLY , WE IDENTIFY TWO TYPES OF VIDEOS , INFORMATION AND EXPLOIT VIDEOS , THAT LEADS TO VALUE CO CREATION AND CO DESTRUCTION
671	WE DEPLOY ECONOMETRIC ANALYSIS ON DATA COLLECTED FROM THE MOBILE APP MARKET AND YOUTUBE THAT CONTAINS THE LONGITUDINAL PERFORMANCE OF APPS AND CHARACTERISTICS OF RELATED YOUTUBE VIDEOS
671	RESULTS SHOW THAT INFORMATION VIDEOS INCREASE USER ENGAGEMENT AND REVENUE STREAMS , WHILE EXPLOIT VIDEOS DECREASE REVENUE STREAMS
671	INFORMATION VIDEOS ALSO INCREASE THE LIKES AND VIEWS OF YOUTUBE CONTENT CREATORS
671	IN POST HOC ANALYSES , WE SHOW THE ASYMMETRIC IMPACTS ON DIFFERENT REVENUE SOURCES AND THE ANTECEDENTS OF VIDEO CREATION BEHAVIOR
671	MSOM , TECHNOLOGY , INNOVATION AND ENTREPRENEURSHIP MSOM , SERVICE OPERATIONS SOCIAL MEDIA ANALYTICS
672	INNOVATION ON FIRM PERFORMANCE AND MODERATING ROLE OF STATE OWNERSHIP AND CORPORATE GOVERNANCE , EMPIRICAL EVIDENCE CHINA
672	ALTHOUGH VARIOUS ASPECTS OF INNOVATION AND FIRM PERFORMANCE HAVE BEEN STUDIED , PREVIOUS RESEARCH HAS OVERLOOKED THE OVERALL IMPACT OF INNOVATION ON FIRM PERFORMANCE
672	THEREFORE , THIS STUDY AIMS TO DETERMINE THE SIGNIFICANCE OF INNOVATION ON THE PERFORMANCE OF CHINESE FIRMS
672	THIS STUDY USES DATA FROM CHINESE FIRMS LISTED ON THE SHENZHEN AND SHANGHAI STOCK EXCHANGES FROM TO THE RESULT SIGNIFIES THAT INNOVATION HAS A POSITIVE IMPACT ON FIRM PERFORMANCE
672	STATE OWNERSHIP AND CORPORATE GOVERNANCE BOTH POSITIVELY MODERATE THIS EFFECT
672	THE STUDY ALSO FOUND THAT WHEN CORPORATE GOVERNANCE IS HIGH AND STATE OWNED SUPPORT IS LOW , THE RELATIONSHIP BETWEEN INNOVATION AND FIRM PERFORMANCE IS STRONGER
672	CONVERSELY , WHEN CORPORATE GOVERNANCE IS LOW AND STATE OWNED SUPPORT IS HIGH , THE RELATIONSHIP BETWEEN INNOVATION AND FIRM PERFORMANCE IS WEAKER
672	MSOM , TECHNOLOGY , INNOVATION AND ENTREPRENEURSHIP MSOM , SUSTAINABLE OPERATIONS BEHAVIORAL OPERATIONS MANAGEMENT
673	FREEMIUM VERSUS FREE TRIAL , THE ART OF ATTRACTING CUSTOMERS AND WINNING IN THE BUSINESS WORLD
673	A STYLIZED MODEL IS DEVELOPED IN ORDER TO QUANTITATIVELY ANALYZE AND COMPARE TWO MAJOR BUSINESS MODELS WHICH IS APPLICABLE TO A VARIETY OF PRODUCTS AND SERVICES , FREEMIUM MODEL AND FREE TRIAL MODEL
673	WHILE FREEMIUM MODEL OFFERS A LIMITED PORTION OF THE MAXIMUM PROVIDABLE PRODUCT OR SERVICE FOR UNLIMITED TIME LENGTH , FREE TRIAL MODEL GIVES A POTENTIAL CUSTOMER AN OPPORTUNITY TO EXPERIENCE THE COMPLETE VERSION OF THE SAME PRODUCT OR SERVICE BUT WITH A FAIRLY LIMITED TIME FRAME
673	TAKING VARIOUS FACTORS , THE LEARNING RATE OF CUSTOMERS UPON THE UTILITY OF A GIVEN PRODUCT OR SERVICE , COST TO PROVIDE A PRODUCT OR SERVICE FOR A UNIT LENGTH OF TIME , ETC , INTO CONSIDERATION , THE STUDY AIMS TO CHARACTERIZE WHICH BUSINESS MODEL IS MORE FAVORABLE UNDER WHAT CIRCUMSTANCES
673	THEREBY THE RESULT OF THIS STUDY MAY CONTRIBUTE TO THE NEVER ENDING DEBATE ON FREEMIUM VS FREE TRIAL 
673	MSOM , TECHNOLOGY , INNOVATION AND ENTREPRENEURSHIP REVENUE MANAGEMENT AND PRICING NEW PRODUCT DEVELOPMENT
674	DATA DRIVEN PREFERENCE LEARNING METHODS FOR MULTIPLE CRITERIA SORTING WITH TEMPORAL CRITERIA
674	THIS STUDY PRESENTS A NOVEL PREFERENCE LEARNING METHOD FOR MULTIPLE CRITERIA SORTING PROBLEMS WITH TEMPORAL INFORMATION
674	EXISTING METHODS LACK CONSIDERATION OF TEMPORAL DYNAMICS
674	OUR APPROACH UTILIZES ADDITIVE PIECEWISE LINEAR VALUE FUNCTIONS AS THE BASIC PREFERENCE MODEL FOR EACH TIME POINT , EMPLOYING A FIXED TIME DECAY RATE TO AGGREGATE VALUES OVER THE TIME SERIES
674	BY FORMULATING THE PROBLEM AS A QUADRATIC PROGRAMMING MODEL , THE SOLUTION RELIES ON A SUBSET OF TRAINING SAMPLES
674	TO ENHANCE GENERALIZATION , WE INCORPORATE ARBITRARY TIME DECAY RATES AND INTRODUCE A MONOTONIC RECURRENT NEURAL NETWORK , MRNN , TO LEARN PREFERENCE MODEL PARAMETERS
674	THE PROPOSED MRNN ENSURES MONOTONICITY AND AUTOMATICALLY ADAPTS THE TIME DECAY RATE FOR EXTENSIVE TEMPORAL DATA
674	WE DEMONSTRATE THE EFFICACY IN EVALUATING THE VALUE OF MOBILE GAME USERS , ADDRESSING A REAL WORLD PROBLEM
674	MULTIPLE CRITERIA DECISION MAKING DATA MINING ARTIFICIAL INTELLIGENCE
675	COMPUTING AN EQUILIBRIUM OF COMPETITION AMONG SHARING PLATFORM OPERATORS MODELED AS AN M N STACKELBERG GAME
675	THE M N STACKELBERG GAME , CONSISTING OF MULTIPLE LEADERS AND FOLLOWERS , IS INTRICATELY INTERTWINED WITH THE HIERARCHICAL INTERACTION BETWEEN LEADERS AND FOLLOWERS , AS WELL AS THE SIMULTANEOUS INTERACTION AMONG LEADERS AND AMONG FOLLOWERS
675	THIS GAME IS ESSENTIAL FOR MODELING COMPETITIVE SHARING PLATFORM MARKETS WITH MULTIPLE PLATFORM OPERATORS
675	HOWEVER , DUE TO THE INTRICATE INTERACTIONS BETWEEN LEADERS AND FOLLOWERS , FINDING OPTIMAL SOLUTIONS FOR LEADERS IS CHALLENGING
675	IN THIS STUDY , WE PROPOSE A GENERAL METHODOLOGY TO FIND THE STACKELBERG EQUILIBRIUM OF THE M N STACKELBERG GAME
675	WE APPLY OUR ALGORITHM TO ANALYZE THE COMPETITION IN SHARING PLATFORM MARKETS , SUCH AS SHARING ENERGY STORAGE SYSTEM PLATFORMS AND CAR SHARING PLATFORMS
675	MULTIPLE CRITERIA DECISION MAKING DECISION ANALYSIS SOCIETY AUCTIONS AND MARKET DESIGN
676	INTEGRATION OF AGRICULTURAL FIELDS WITH HYDROGEN VALLEYS , A DECISION SUPPORT MODEL FOR A CIRCULAR ECONOMY
676	THE DECARBONIZATION OF THE GLOBAL ECONOMY IS A PRESSING CHALLENGE IN THE ST CENTURY , REQUIRING SUBSTANTIAL REDUCTIONS IN GREENHOUSE GAS EMISSIONS
676	THE EUROPEAN UNION , EU , HAS SET AN AMBITIOUS TARGET TO BECOME THE FIRST CLIMATE NEUTRAL ECONOMY BY , WITH HYDROGEN VALLEYS PLAYING A SIGNIFICANT ROLE IN ACHIEVING THIS GOAL
676	HYDROGEN VALLEYS CONTRIBUTE TO THE DECARBONIZATION OF THE EU S ECONOMY BY PROMOTING THE PRODUCTION OF GREEN HYDROGEN AND FACILITATING ITS UTILIZATION IN VARIOUS APPLICATIONS
676	DESPITE THE SIGNIFICANT POTENTIAL FOR INTEGRATING AGRICULTURAL FIELDS WITH HYDROGEN VALLEYS TO FOSTER A CIRCULAR ECONOMY , THIS AREA REMAINS LARGELY UNEXPLORED IN THE EXISTING LITERATURE
676	THIS PAPER AIMS TO DEVELOP A DECISION SUPPORT MODEL THAT FACILITATES THE INTEGRATION OF AGRICULTURAL FIELDS WITH HYDROGEN VALLEYS
676	MULTIPLE CRITERIA DECISION MAKING ENRE , ENERGY CLIMATE SUPPLY CHAIN AND LOGISTICS IN PRACTICE
677	MULTIOBJECTIVE ALGORITHM FOR THE POLITICAL REDISTRICTING PROBLEM
677	THIS PRESENTATION CONTINUES ON PREVIOUS WORK BY THE AUTHORS TOWARDS CREATING A MULTICRITERIA MODEL FOR SOLVING THE POLITICAL DISTRICTING PROBLEM IN SOUTH CAROLINA
677	WE CONSIDER FOUR KEY OBJECTIVES , POPULATION EQUALITY , COUNTY DIVISIONS , DISTRICT COMPACTNESS , AND POLITICAL FAIRNESS
677	BY UTILIZING A NON DOMINATED SORTING GENETIC ALGORITHM , NSGA II , , WE CAN FIND A SET OF HIGH QUALITY SOLUTIONS APPROXIMATING A PARETO FRONT FOR THE STATE OF SOUTH CAROLINA
677	MULTIPLE CRITERIA DECISION MAKING OPTIMIZATION , OPT , 
678	OPTIMIZATION MODEL FOR SELECTING TARGET SEGMENT IN MASS MARKETING CAMPAIGNS
678	DEFINING A TARGET GROUP FOR A MASS MARKETING CAMPAIGN IS A NON TRIVIAL GOAL , WHICH DEPENDS ON THE CORRECT DEFINITION OF THE COMMERCIAL STIMULI AND THE SELECTION OF A CUSTOMER TARGET SEGMENT THAT WILL MAXIMIZE THE CAMPAIGN S EFFECTIVENESS
678	IN THIS RESEARCH , WE PROPOSE A METHODOLOGY BASED ON A MIXED MULTI OBJECTIVE OPTIMIZATION FORMULATION THAT ALLOWS DETERMINING A MINIMUM CONTINUOUS CUSTOMER TARGET SEGMENT FOR MASSIVE CAMPAIGNS TO MAXIMIZE ITS EFFECTIVENESS WITH A MAXIMUM BUDGET CONSTRAINT
678	THE MODEL MULTI OBJECTIVE FUNCTION MAXIMIZES THE CAMPAIGN S EFFECTIVENESS WHILE MINIMIZING THE BROADNESS OF THE SEGMENTS TARGETED , ALLOWING THE DETECTION OF THE MOST EFFECTIVE AND HOMOGENEOUS TARGET GROUP POSSIBLE
678	THE METHODOLOGY PERFORMANCE WAS BENCHMARKED AGAINST TRADITIONAL CUSTOMER SEGMENTATION ALGORITHMS LIKE K MEANS AND GREEDY SELECTION METHODOLOGY
678	MULTIPLE CRITERIA DECISION MAKING PRACTICE USING CUSTOMER DATA WE DETERMINE OPTIMAL TARGET SEGMENTS 
679	A PARAMETRIC PERSPECTIVE ON BENDERS DECOMPOSITION
679	WE CONSIDER A LINEAR PROGRAM SUITABLE FOR BENDERS DECOMPOSITION WITH A PARAMETER IN THE OBJECTIVE FUNCTION
679	APPLYING PARAMETRIC LINEAR PROGRAMMING DUALITY AND FOLLOWING ON THE ORIGINAL RESULTS BY BENDERS ON THE FEASIBLE REGION OF THE RELAXED MASTER PROBLEM TO YIELD AN OPTIMAL SOLUTION OF THE ORIGINAL PROBLEM , WE DEVELOP A THEORY FOR A PARAMETRIC MASTER PROBLEM AND PARAMETRIC SUB PROBLEM IN SUPPORT OF ANALOGOUS CONDITIONS
679	EXAMPLES ARE INCLUDED
679	MULTIPLE CRITERIA DECISION MAKING 
680	UNIVERSAL BOUNDS FOR SPREADING ON NETWORKS
680	SPREADING , DIFFUSION , OF INNOVATIONS IS A STOCHASTIC PROCESS ON SOCIAL NETWORKS
680	WHEN THE KEY DRIVING MECHANISM IS PEER EFFECTS , THE AGGREGATE ADOPTION LEVEL DEPENDS STRONGLY ON THE NETWORK STRUCTURE
680	IN MANY APPLICATIONS , HOWEVER , THE NETWORK STRUCTURE IS UNKNOWN
680	TO ESTIMATE THE AGGREGATE ADOPTION LEVEL FOR SUCH INNOVATIONS , WE SHOW THAT THE TWO NETWORKS THAT CORRESPOND TO THE SLOWEST AND FASTEST ADOPTION LEVELS ARE A HOMOGENEOUS TWO NODE NETWORK AND A HOMOGENEOUS INFINITE COMPLETE NETWORK , RESPECTIVELY
680	SOLVING THE STOCHASTIC BASS MODEL ON THESE TWO NETWORKS YIELDS EXPLICIT LOWER AND UPPER BOUNDS FOR THE ADOPTION LEVEL ON ANY NETWORK
680	THESE BOUNDS ARE OPTIMAL , AND THEY ALSO HOLD FOR THE INDIVIDUAL ADOPTION PROBABILITIES OF NODES
680	THE GAP BETWEEN THE LOWER AND UPPER BOUNDS INCREASES MONOTONICALLY WITH THE RATIO OF THE RATES OF INTERNAL AND EXTERNAL INFLUENCES
680	NEW PRODUCT DEVELOPMENT APPLIED PROBABILITY OPT , NETWORK OPTIMIZATION
681	THE PREDICTIVE UTILITY OF LANGUAGE COMPLEXITY ON NEW PRODUCT ADOPTION
681	RESEARCH ON PROCESSING FLUENCY SUGGESTS THAT PEOPLE PERCEIVE SIMPLE AND COMMON LANGUAGE AS MORE POSITIVE THAN COMPLEX AND TECHNICAL LANGUAGE
681	IN THIS SENSE , CONSUMERS MAY PREFER NEW PRODUCTS WITH DESCRIPTIONS USING SIMPLE , VS COMPLEX , LANGUAGE
681	BUT THIS STUDY PROPOSES AND DEMONSTRATES THAT THE EFFECT MAY BE REVERSED DEPENDING ON NEW PRODUCT TYPES
681	ACROSS FOUR STUDIES , INCLUDING ONE FIELD EXPERIMENT , WE SHOW THAT WHILE A SIMPLE LANGUAGE FACILITATES HEDONIC NEW PRODUCT ADOPTION , A COMPLEX LANGUAGE BETTER PROMOTES UTILITARIAN NEW PRODUCT ADOPTION
681	MOREOVER , THE CURRENT RESEARCH SHOWS THAT THE INTERACTION EFFECT OF THE NEW PRODUCT TYPES AND LANGUAGE COMPLEXITY ON PURCHASE INTENTION IS MEDIATED BY CONSUMERS ATTENTION SALIENCE
681	NEW PRODUCT DEVELOPMENT SOCIAL MEDIA ANALYTICS EBUSINESS
682	PERFECT BAYESIAN EQUILIBRIUM WITH COMMON ACTION INDEPENDENT CONSISTENCY AND ITS SQUARE ROOT BARRIER SELECTION
682	THE CONCEPT OF PERFECT BAYESIAN EQUILIBRIUM WAS ESTABLISHED THROUGH A SLIGHT RELAXATION TO THE REQUIREMENTS OF SEQUENTIAL EQUILIBRIUM WHILE SUSTAINING THE SUBGAME PERFECTION
682	HOWEVER , THIS ESTABLISHMENT LACKS A PRACTICABLE AND EFFECTIVE FORMULATION FOR COMPUTATIONALLY FINDING SUCH AN EQUILIBRIUM
682	TO RESOLVE THIS DEFICIENCY , THIS PAPER INTRODUCES COMMON ACTION INDEPENDENT CONSISTENCY ON BELIEFS AND DEVELOPS A MATHEMATICAL CHARACTERIZATION OF PERFECT BAYESIAN EQUILIBRIUM WITH THIS CONSISTENCY THROUGH LOCAL SEQUENTIAL RATIONALITY
682	AS A RESULT OF THIS CHARACTERIZATION , THE PERFECT BAYESIAN EQUILIBRIUM CAN BE EXPLICITLY SPECIFIED BY A POLYNOMIAL SYSTEM , WHICH LEADS TO A DIFFERENTIABLE PATH FOLLOWING METHOD FOR COMPUTING SUCH AN EQUILIBRIUM
682	NUMERICAL RESULTS FURTHER CONFIRM THE EFFECTIVENESS AND EFFICIENCY OF THE METHOD
682	OPT , COMPUTATIONAL OPTIMIZATION AND SOFTWARE DECISION ANALYSIS SOCIETY 
683	MARITIME EMERGENCY SEARCH AND RESCUE PATH PLANNING CONSIDERING SHIPBORNE UAV
683	THE PAPER STUDIES MARITIME EMERGENCY SEARCH AND RESCUE PATH PLANNING PROBLEM BASED ON SHIPBORNE UAV , MEPPSU , 
683	IN THE PROBLEM , EACH UAV IS FIRST LAUNCHED FROM A SHIP TO CARRY A SEARCH AND RESCUE MISSION AND THEN RETURN TO THE SHIP AT LAST
683	AFTER VISITING ALL THE TARGETS , THE SHIP WILL RETURN TO THE DESTINATION
683	WE INTRODUCE AN EXACT ALGORITHM BASED ON BRANCH AND BOUND TO OBTAIN THE BEST CLUSTERING OF THE TARGETS AND VISITING ORDER OF DIFFERENT CLUSTERS
683	MOREOVER , UAV S LAUNCH LOCATION WILL BE EVALUATED BY A SECOND ORDER CONE PROGRAMMING
683	SEVERAL HEURISTICS BASED ON SECOND ORDER CONE PROGRAMMING IS DESIGNED FOR LARGER INSTANCES AS WELL
683	WE ALSO SHOW THAT OUR SCHEMES ARE FLEXIBLE TO ACCOMMODATE A VARIETY OF ADDITIONAL OBJECTIVE FUNCTIONS
683	IT S PROVED THAT OUR METHOD CAN PROVIDE EFFECTIVE DECISION SUPPORT FOR MARITIME TRANSPORT SECTOR
683	OPT , COMPUTATIONAL OPTIMIZATION AND SOFTWARE OPT , GLOBAL OPTIMIZATION IN MARITIME EMERGENCY SEARCH AND RESCUE , WE CAN USE EXISTING REALISTIC DATA AND OR TO PLAN SEARCH AN 
684	CAROUSEL GREEDY ALGORITHMS FOR FEATURE SELECTION IN LINEAR REGRESSION
684	THE CAROUSEL GREEDY ALGORITHM , CGA , WAS PROPOSED SEVERAL YEARS AGO AS A GENERALIZED GREEDY ALGORITHM
684	IN THIS PAPER , WE IMPLEMENT THE CGA TO SOLVE LINEAR REGRESSION PROBLEMS WITH A CARDINALITY CONSTRAINT ON THE NUMBER OF VARIABLES
684	WE COMPARE THIS AGAINST STEPWISE REGRESSION AND MORE SOPHISTICATED APPROACHES , ONE USING INTEGER PROGRAMMING AND A SECOND USING LASSO
684	OPT , COMPUTATIONAL OPTIMIZATION AND SOFTWARE OPT , INTEGER AND DISCRETE OPTIMIZATION OPTIMIZATION , OPT , 
685	LEVERAGING PARAMETRIC SENSITIVITIES TO ACCELERATE DISTRIBUTED OPTIMIZATION ALGORITHMS
685	LARGE SCALE OPTIMIZATION PROBLEMS , COMMON IN APPLICATIONS , SUCH AS OPTIMAL RESOURCE ALLOCATION AND MULTI AGENT NETWORKS , CAN BE DECOMPOSED INTO SEVERAL SMALLER SUBPROBLEMS THAT TAKE COORDINATED ACTIONS
685	THIS WORK FOCUSES ON ADDRESSING THE COMPUTATIONAL BURDEN OF REPEATEDLY SOLVING THE SUBPROBLEMS ARISING IN WIDE RANGE OF DISTRIBUTED OPTIMIZATION PROBLEMS
685	NOTING THAT IN MOST DECOMPOSITION STRATEGIES , BOTH CENTRALIZED DECENTRALIZED COORDINATION , , THE SUBPROBLEMS SOLVED BETWEEN CONSECUTIVE ITERATIONS DIFFER ONLY BY A FEW VARIABLES , THE KEY IDEA OF THIS WORK IS TO EXPLOIT THE PARAMETRIC NATURE OF THE SUBPROBLEMS TO REDUCE THE COMPUTATION TIME OF THE SUBPROBLEMS IN EACH ITERATION
685	CONVERGENCE GUARANTEES FOR A CLASS OF ADMM PROBLEMS WILL BE PRESENTED , ALONG WITH NUMERICAL EXAMPLES INCLUDING FLOW ROUTING , RESOURCE ALLOCATION , AND DISTRIBUTED LEARNING PROBLEMS
685	OPT , COMPUTATIONAL OPTIMIZATION AND SOFTWARE OPT , NETWORK OPTIMIZATION OPT , NONLINEAR OPTIMIZATION
686	COUNTING OPERATIONS IN DATA ENVELOPMENT ANALYSIS
686	ALGORITHMS AND COMPUTATIONS ARE AN IMPORTANT ASPECT OF DEA
686	CURRENT PRACTICES WHEN INTRODUCING A COMPUTATIONAL PROCEDURE FOR DEA CONSIST OF DESCRIBING THE APPROACH AND COMPARING ITS PERFORMANCE BASED ON EXECUTION TIMES
686	THE PREPONDERANT OPERATION IN DEA IS SOLVING LINEAR PROGRAMS , THEREFORE , AN OPERATION COUNT FOR DEA PROCEDURES CAN BE LIMITED TO THE LP WORKLOAD BASED ON THE NUMBER AND SIZE OF LPS SOLVED
686	OPERATION COUNTS PROVIDES A COMMON GROUND FOR ANALYZING AND COMPARING DEA PROCEDURES
686	THEY ARE INDEPENDENT OF HARDWARE , LP SOLVERS , AND PLATFORM
686	WE DISCUSS THE USE OF MACHINE INDEPENDENT OPERATIONS COUNT TO ANALYZE AND COMPARE DEA PROCEDURES
686	WE MAKE THE CASE FOR THE USE OF OPERATION COUNTS IN DEA PROCEDURES THAT CLAIM SUBSTANTIAL SPEEDUPS AS PART OF THE ANALYSIS AND COMPARISON WITH COMPETING APPROACHES
686	WE PROVIDE A TAXONOMY FOR DEA PROCEDURES
686	OPT , COMPUTATIONAL OPTIMIZATION AND SOFTWARE 
687	HYLAC I , I HYBRID LINEAR ASSIGNMENT SOLVER IN CUDA
687	THIS PAPER PRESENTS A HYBRID GPU ACCELERATED SOLVER FOR THE LINEAR ASSIGNMENT PROBLEM , LAP , THAT ACHIEVES SIGNIFICANT PERFORMANCE IMPROVEMENTS
687	THE LAP IS A FUNDAMENTAL COMBINATORIAL OPTIMIZATION PROBLEM
687	THE HUNGARIAN ALGORITHM IS A WELL KNOWN APPROACH FOR SOLVING LAP , WITH O , N SUP SUP , MUNKRES AND O , N SUP SUP , LAWLER S IMPLEMENTATIONS HAVING DIFFERENT SPEED ADVANTAGES DEPENDING ON THE SPARSITY OF PROBLEM INSTANCES
687	THE PROPOSED SOLVER , HYLAC , BLENDS THE GPU SOLUTIONS OF ABOVE IMPLEMENTATIONS AND IMPROVES MEMORY ACCESS AND CPU GPU SYNCHRONIZATION
687	HYLAC ACHIEVES A SPEEDUP OF UP TO X OVER EXISTING GPU SOLVERS FOR BOTH SPARSE AND DENSE INSTANCES
687	ADDITIONALLY , A TILED LAP SOLVER IS DEVELOPED TO SOLVE A LIST OF SMALL LAPS , IT PERFORMS X FASTER THAN EXISTING SOLVERS
687	OPT , COMPUTATIONAL OPTIMIZATION AND SOFTWARE 
688	PARALLELIZING DEA PROCEDURES
688	THERE HAS BEEN AN INTEREST SINCE THE EARLY DAYS OF DEA TO EXPLORE THE PARALLELIZATION OF ITS PROCEDURES
688	THE TRADITIONAL APPROACH ALONG WITH INNOVATIONS THAT FOLLOWED SUCH AS REDUCED BASIS ENTRY , ALI , , , HIERARCHICAL DECOMPOSITION , BARR DURCHHOLZ , , AND ITS VARIANTS ARE HIGHLY PARALLELIZABLE
688	OTHERS , SUCH AS BUILDHULL , DULA , , , LESS SO
688	WE SHOW HOW TO PARALLELIZE BUILDHULL TO ATTAIN SPEEDUPS FOR DEA COMPUTATIONS THAT MAKE IT COMPETITIVE SETTING NEW PERFORMANCE STANDARDS
688	OPT , COMPUTATIONAL OPTIMIZATION AND SOFTWARE 
689	HOW THE INFORMATION AND COMMUNICATION TECHNOLOGY MODERATE THE RELATIONSHIP BETWEEN AGRICULTURE GLOBAL VALUE CHAIN AND ENVIRONMENTAL PERFORMANCE
689	PARTICIPATION IN A SPECIALIZED GLOBAL VALUE CHAIN COULD CONDUCIVE THE IMPROVEMENT OF TECHNOLOGY IN DEVELOPING COUNTRIES , AT THE SAME TIME POLLUTION MAY ALSO BE TRANSFERRED FROM DEVELOPED COUNTRIES TO DEVELOPING COUNTRIES
689	THEREFORE , WE USE THE PANEL DATA OF THE BRICS COUNTRIES FROM TO TO INVESTIGATE HOW THE BRICS COUNTRIES PARTICIPATION IN THE AGRICULTURAL GLOBAL VALUE CHAIN , AGVC , WILL AFFECT THEIR ENVIRONMENT , AND TO EXPLORE THE MODERATING ROLE OF INFORMATION AND COMMUNICATION TECHNOLOGY , ICT , IN THE AGVC ENVIRONMENT NEXUS
689	THE RESULT OF OUR ESTIMATION IS THAT THE PARTICIPATION OF BRICS COUNTRIES IN THE AGVC WOULD LEAD TO A CERTAIN DEGREE OF ENVIRONMENT DEGRADATION , BUT ICT WILL ALLEVIATE THIS NEGATIVE IMPACT
689	OPT , GLOBAL OPTIMIZATION ENRE , ENVIRONMENT AND SUSTAINABILITY MSOM , SUSTAINABLE OPERATIONS
689	THE DEVELOPMENT OF THE DIGITAL ECONOMY AFFECTS THE GLOBAL VALUE CHAIN OF AGRICULTURAL PRODUCTS 
690	HIGH DIMENSIONAL PARAMETER ESTIMATION FOR COMPLEX CHEMICAL REACTION NETWORKS USING A HYBRID BAYESIAN OPTIMIZATION AND GRADIENT DESCENT APPROACH
690	CHEMICAL PROCESSES OFTEN INVOLVE COMPLEX REACTION NETWORKS
690	THE RATE FOR EACH REACTION DEPENDS ON VARIOUS FACTORS SUCH AS CONCENTRATION AND TEMPERATURE
690	EACH FACTOR CAN HAVE MULTIPLE PARAMETERS WHOSE VALUES ARE USUALLY UNKNOWN AND CAN ONLY BE ESTIMATED FROM DATA
690	FOR THIS WORK , WE PROPOSE A HYBRID APPROACH THAT COMBINES GLOBAL AND LOCAL OPTIMIZATION STRATEGY TO TACKLE SUCH HIGH DIMENSIONAL PARAMETER ESTIMATION PROBLEM EFFICIENTLY
690	THE METHOD INVOLVES USING HIGH DIMENSIONAL BAYESIAN OPTIMIZATION , SAASBO , TO SEARCH THE FULL PARAMETER SPACE AND THEN REDUCE PROBLEM DIMENSION BY ELIMINATING THE LESS SENSITIVE PARAMETERS
690	THEN THE CURRENT BEST SET OF PARAMETERS FOUND BY SAASBO WERE FURTHER REFINED USING GRADIENT BASED METHODS WHICH ARE COMPUTATIONALLY MORE EFFICIENT
690	ADDITIONALLY , THE POSTERIOR DISTRIBUTION WAS ALSO QUANTIFIED USING A MCMC SAMPLING APPROACH
690	OPT , GLOBAL OPTIMIZATION OPT , NONLINEAR OPTIMIZATION MACHINE LEARNING FOR OPTIMIZATION
691	THREE DIMENSIONAL CONTAINER LOADING PROBLEM SOLVED BY AN INNOVATIVE AND ITERATIVE ALGORITHM
691	THIS STUDY ADDRESSES A NOVEL METHOD FOR THE THREE DIMENSIONAL CONTAINER LOADING PROBLEM , DCLP , , WHICH IS AN NP HARD PROBLEM IN MANAGEMENT SCIENCE AND OPERATIONS RESEARCH
691	TO REDUCE COMPUTATIONAL COMPLEXITY AND GUARANTEE SOLUTION QUALITY , THIS STUDY DESIGNS A D RELATIVE POSITIONS SCHEME SO THAT THE DCLP CAN BE RELAXED TO A LINEAR PROGRAMMING PROBLEM
691	SOLVING THE RELAXED DCLP CAN OBTAIN A FEASIBLE SOLUTION
691	SUBSEQUENTLY , AN INNOVATIVE AND ITERATIVE ALGORITHM IS DESIGNED TO ENHANCE THE SOLUTION QUALITY
691	EXPERIMENTAL RESULTS HAVE SHOWN THAT THE PROPOSED METHOD HAS HIGHER EFFICIENCY AND ACCURACY IN DEALING WITH COMPLEX THREE DIMENSIONAL CONTAINER LOADING PROBLEMS
691	OPT , GLOBAL OPTIMIZATION OPTIMIZATION , OPT , OPT , LINEAR AND CONIC OPTIMIZATION
692	INNOVATIVE AND ITERATIVE ALGORITHM WITH RELATIVE POSITIONS SCHEME FOR THE TWO DIMENSIONAL VARIABLE SIZED BIN PACKING PROBLEM
692	THE TWO DIMENSIONAL VARIABLE SIZED BIN PACKING PROBLEM , DVSBPP , IS A CLASSICAL PROBLEM IN THE FIELD OF MANAGEMENT SCIENCE AND OPERATIONS RESEARCH
692	THIS STUDY PROPOSES A NOVEL METHOD THAT USES A RELATIVE POSITIONS SCHEME TO ADDRESS THE RELAXED DVSBPP LINEAR PROGRAMMING PROBLEM
692	ADDITIONALLY , AN INNOVATIVE AND ITERATIVE ALGORITHM IS ADOPTED TO IMPROVE THE SOLUTION QUALITY ITERATIVELY
692	THE PROPOSED ALGORITHM NOT ONLY OBTAINS OPTIMAL SOLUTIONS FOR SMALL SCALE PROBLEMS , BUT ALSO ENHANCES THE SOLUTION QUALITY FOR LARGE SCALE PROBLEMS
692	NUMERICAL EXPERIMENTS ALSO SHOW THAT THE PROPOSED ALGORITHM OUTPERFORMS STATE OF THE ART ALGORITHMS
692	OPT , GLOBAL OPTIMIZATION OPTIMIZATION , OPT , OPT , LINEAR AND CONIC OPTIMIZATION
693	ROBUST CONCURRENT ALGORITHMS FOR UNSTRUCTURED MIXED INTEGER LINEAR PROGRAMS
693	IN THIS STUDY , WE PROPOSE ROBUST CONCURRENT HEURISTICS FOR MIXED INTEGER LINEAR PROGRAMS THAT RUNS IN MASSIVELY PARALLEL PLATFORMS IN DISTRIBUTED MEMORY SETTINGS
693	SPECIFICALLY , BOTH FEASIBILITY PUMP AND OBJECTIVE FEASIBILITY PUMP ARE RUN IN PARALLEL STARTING FROM ALTERNATIVE POINTS IN THE FEASIBLE REGION
693	INFORMATION GENERATED BY A SUBROUTINE IS COLLECTIVELY USED BY ALL SUBROUTINES
693	THE ALGORITHM CONTINUES TO PROVIDE GOOD SOLUTIONS EVEN IF SOME OF THE COMPUTING NODES ARE UNREACHABLE
693	OPT , INTEGER AND DISCRETE OPTIMIZATION COMPUTING SOCIETY OPTIMIZATION , OPT , 
694	BIPARTITE GRAPH FOR BOOLEAN PATTERN RECOGNITION
694	BOOLEAN PATTERN RECOGNITION CAN BE FORMULATED AS AN IP WITH MIN COVER INEQUALITIES
694	TO ADDRESS THIS PROBLEM , WE UTILIZE A BIPARTITE GRAPH TO REPRESENT THE BOOLEAN LITERALS AS NODES ON ONE SIDE AND THE INEQUALITIES AS THE OTHER
694	NEXT , WE INTRODUCE AN EDGE BETWEEN A LITERAL AND A CONSTRAINT IF THE LITERAL APPEARS IN THE CORRESPONDING COVER INEQUALITY
694	FOR SOLUTION , WE DESIGN SCORES BASED ON LOCAL OPTIMALITY AND FEASIBILITY CRITERIA AND INTEGRATE THEM TO YIELD A COMBINATORIAL ALGORITHM THAT STRIVES TO IDENTIFY SOLUTIONS THAT ARE OPTIMAL IN A LARGE NEIGHBORHOOD
694	THROUGH PRELIMINARY EXPERIMENTS ON PUBLIC DATA MINING DATASETS , WE TEST ROBUSTNESS AND EFFICIENCY OF THE PROPOSED ALGORITHM
694	OPT , INTEGER AND DISCRETE OPTIMIZATION DATA MINING 
695	GRAPH NEURAL NETWORKS WITH DYNAMIC PROGRAMMING FOR WORKFLOW SCHEDULING
695	WORKFLOW SCHEDULING IS A WELL KNOWN COMBINATORIAL OPTIMIZATION PROBLEM FOR WHICH RESEARCHERS HAVE TRIED DESIGNING NUMEROUS HEURISTICS OVER THE YEARS
695	RECENT ADVANCES USE MACHINE LEARNING METHODS THAT EITHER REPLACE TRADITIONAL ALGORITHMS WITH FAST FUNCTION APPROXIMATIONS LEARNED THROUGH NEURAL NETWORKS OR REINFORCEMENT LEARNING
695	OUR APPROACH USES GRAPH NEURAL NETWORKS , GNN , TO CREATE A HEATMAP OF EDGES THAT DESCRIBES THE PROBABILITY OF EVERY TASK EXECUTOR PAIRING IN THE OPTIMAL SOLUTION
695	THIS HEATMAP IS LEARNED BY FORMULATING THE CORRESPONDING MIXED INTEGER LINEAR PROGRAM AND TRAINING THE GNN ON ITS OPTIMAL SOLUTIONS
695	THE HEATMAP GENERATED BY THE GNN IS THEN LEVERAGED TO FIND THE BEST SOLUTION USING DYNAMIC PROGRAMMING
695	OPT , INTEGER AND DISCRETE OPTIMIZATION MACHINE LEARNING FOR OPTIMIZATION 
695	OUR APPROACH USES DATA FROM OPTIMAL SOLUTIONS TO SOLVE COMBINATORIAL PROBLEMS 
696	A LEARNING BASED EXACT ALGORITHM FOR THE QUADRATIC MULTIPLE KNAPSACK PROBLEM
696	THE QUADRATIC MULTIPLE KNAPSACK PROBLEM , QMKP , IS A CLASSIC COMBINATORIAL OPTIMIZATION PROBLEM THAT FINDS WIDE APPLICATIONS IN VARIOUS SCENARIOS
696	DESPITE A PLETHORA OF HEURISTICS , ONLY A FEW EXACT ALGORITHMS FOR QMKP HAVE BEEN DEVELOPED
696	THIS PAPER PROPOSES A NEW EXACT BRANCH AND PRICE ALGORITHM TO SOLVE QMKP , IN WHICH WE REFORMULATE THE MASTER PROBLEM MODEL USING THE IDENTITY OF PRICING SUBPROBLEMS
696	IN ADDITION , A LEARNING BASED METHOD IS USED TO GENERATE THE NEAR OPTIMAL SOLUTION QUICKLY FOR THE PRICING SUBPROBLEMS , THUS ENHANCING THE EFFICIENCY OF COLUMN GENERATION
696	THE EXPERIMENTS SHOW THAT OUR METHOD EXHIBITS EXCELLENT PERFORMANCE IN SOLVING LARGE SCALE QUADRATIC MULTIPLE KNAPSACK PROBLEMS COMPARED TO EXISTING EXACT ALGORITHMS
696	OPT , INTEGER AND DISCRETE OPTIMIZATION MACHINE LEARNING FOR OPTIMIZATION 
697	ECONOMIC LOT SIZING PROBLEM WITH TANK SCHEDULING
697	WE INTRODUCE A MULTIPLE ITEM ECONOMIC LOT SIZING PROBLEM WHERE ITEMS ARE PRODUCED THROUGH THE FERMENTATION OF SOME RAW MATERIALS
697	FERMENTATION TAKES PLACE IN SPECIALIZED TANKS THAT HAVE FINITE CAPACITIES , AND DURATION OF THE FERMENTATION PROCESS IS ITEM DEPENDENT
697	WHEN FERMENTATION STARTS , THE TANKS ARE NOT AVAILABLE FOR THE DURATION OF THE FERMENTATION PROCESS
697	WE ANALYZE THE COMPLEXITY OF THIS PROBLEM UNDER VARIOUS ASSUMPTIONS ON THE NUMBER OF ITEMS AND TANKS
697	IN PARTICULAR , WE SHOW THAT SEVERAL CASES OF THE PROBLEM ARE , STRONGLY , NP HARD , AND WE PROPOSE POLYNOMIAL TIME ALGORITHMS TO SOME SINGLE ITEM CASES
697	IN ADDITION , WE PROPOSE A QUICK AND SIMPLE HEURISTIC APPROACH FOR ONE OF THE MULTIPLE ITEM CASES
697	OPT , INTEGER AND DISCRETE OPTIMIZATION MANUFACTURING AND SERVICE OPERATIONS MANAGEMENT , MSOM , SCHEDULING AND PROJECT MANAGEMENT
698	MAXIMAL COVERAGE INFORMATION COLLECTION PROBLEM USING KRIGING
698	THE GOAL OF THIS PROJECT IS TO IDENTIFY WHICH IMAGE SENSORS IN AN ISR MISSION SHOULD COLLECT DATA FROM WHICH CELLS AT WHICH RESOLUTIONS TO MAXIMIZE INFORMATION GAIN
698	HOWEVER , INFORMATION IS NOT ONLY GAINED FROM CELLS WHERE DATA IS DIRECTLY COLLECTED FROM , DATA FUSION TECHNIQUES SUCH AS KRIGING CAN BE USED TO COLLECT INFORMATION FROM OTHER CELLS AS WELL
698	USING KRIGING , THE ESTIMATED ERROR OF THE PREDICTION IN EACH CELL CAN BE CALCULATED
698	WE CAN SAY A CELL IS CONFIDENTLY COVERED IF THIS ESTIMATED ERROR IS BELOW A CERTAIN ACCEPTABLE LEVEL BR WHILE KRIGING IS NON LINEAR , WE DEVELOP AN APPROXIMATE MIP TO SOLVE THIS PROBLEM CALLED SIMPLIFIED KRIGING , SK , 
698	SK OBTAINS SOLUTIONS WITHIN OF OPTIMALITY
698	WE ALSO SHOW THAT SK IS EQUIVALENT TO THE MAXIMAL COVERAGE LOCATION PROBLEM , MCLP , AND WE TEST DIFFERENT HEURISTICS AND SOLUTION METHODS TO SOLVE THE INFORMATION COLLECTION PROBLEM
698	OPT , INTEGER AND DISCRETE OPTIMIZATION MILITARY AND SECURITY OPTIMIZATION , OPT , 
699	JOINT SCHEDULING OF AUTOMATED EXTERNAL DEFIBRILLATORS AND FIRST RESPONDERS WITH COORDINATION IN OUT OF HOSPITAL CARDIAC ARRESTS
699	A ONE MINUTE DELAY IN THE TREATMENT OF OUT OF HOSPITAL CARDIAC ARREST , OHCA , REDUCES A PATIENT S CHANCE OF SURVIVAL BY , MAKING THE TREATMENT EXTREMELY TIME SENSITIVE
699	HOWEVER , TIMELY REAL TIME ACCESS TO AUTOMATED EXTERNAL DEFIBRILLATORS , AED , REMAINS A CHALLENGE
699	THIS RESEARCH FOCUSES ON THE JOINT SCHEDULING PROBLEM OF AEDS AND FIRST RESPONDERS FOR AED DELIVERY
699	TO GUARANTEE A VERY SHORT TIME LIMIT AS WELL AS THE ACCURACY AND ROBUSTNESS OF DECISIONS , OUR RESEARCH ALSO CONSIDERS THE COORDINATION BETWEEN MULTIPLE TYPE FIRST RESPONDERS AND SOME OTHER DETAILED FACTORS
699	A MIXED INTEGER PROGRAMMING MODEL IS CONSTRUCTED FOR THIS PROBLEM AND IS SOLVED BY GUROBI
699	THE EXPERIMENTAL RESULTS REVEAL THAT A SIGNIFICANT DECREASE IN RESPONSE TIME IS ACHIEVED THROUGH OUR OPTIMIZATION AND THE IMPROVEMENT IN COORDINATION CONSIDERATION IS EFFECTIVELY VERIFIED
699	OPT , INTEGER AND DISCRETE OPTIMIZATION MSOM , HEALTHCARE SCHEDULING AND PROJECT MANAGEMENT
699	BOOST THE INTERACTION OF OR AND DATA OF EMERGENCY FIRST RESPONDER INTELLIGENT SCHEDULING PLATFORM 
700	NEW ADVANCES FOR QUANTUM INSPIRED OPTIMIZATION THE QUBO MODEL HAS BECOME HIGHLIGHTED AS AN EFFECTIVE ALTERNATIVE METHOD FOR REPRESENTING AND SOLVING A WIDE VARIETY OF COMBINATORIAL OPTIMIZATION PROBLEMS
700	ADDITIONAL MOMENTUM HAS RESULTED FROM THE ARRIVAL OF QUANTUM COMPUTERS AND THEIR ABILITY TO SOLVE THE ISING SPIN GLASS PROBLEM , ANOTHER FORM OF THE QUBO MODEL
700	THIS PAPER HIGHLIGHTS ADVANCES IN SOLVING QUBO MODELS AND EXTENSIONS TO MORE GENERAL PUBO MODELS AS IMPORTANT ALTERNATIVES TO TRADITIONAL APPROACHES
700	COMPUTATIONAL EXPERIENCE IS PROVIDED THAT COMPARES THE PERFORMANCE OF UNIQUE METAHEURISTIC SOLVERS NGQ , AND NGQ PUBO FOR QUBO AND PUBO MODELS WITH THE PERFORMANCE OF CPLEX AND A LEADING QUANTUM SOLVER
700	EXTENSIVE RESULTS DISCLOSE THAT OUR SOLVERS OUTPERFORM BOTH CPLEX AND THE QUANTUM SOLVER BY A WIDE MARGIN IN TERMS OF BOTH COMPUTATIONAL TIME AND SOLUTION QUALITY OPT , INTEGER AND DISCRETE OPTIMIZATION OPT , COMPUTATIONAL OPTIMIZATION AND SOFTWARE OPT , NONLINEAR OPTIMIZATION