2016 INFORMS Annual Meeting Program

SD58

INFORMS Nashville – 2016

2 - CPOE Adoption Impacts On Medicare Reimbursements Hilal Atasoy, Temple University, hilal.atasoy@temple.edu Computerized Physician Order Entry (CPOE) systems allow physicians to seamlessly enter information in patient records compared to paper-based records, potentially leading to higher quality of care. On the other hand, the ease of capturing information into electronic medical records can be deliberately used by hospitals to inflate their reimbursement requests from Medicare by overstating the complexity of patients’ diagnoses. We study the relationship between CPOE adoption and reported patient complexity of hospitals. We find that, on average, the adoption of CPOE systems is associated with an increase in the case mix index. This increase is significantly higher among for-profit hospitals. 3 - Not What The Doctor Ordered: Physician Mobility And Technology Adoption Brad N Greenwood, Temple University, brad.n.greenwood@gmail.com, Corey M Angst, Kartik Krishna Ganju In this work we investigate the relationship between EMR implementation and physician mobility. Strikingly, although significant anecdotal evidence would suggest that EMR implementation is associated with an exodus of physicians, we find that this reaction is strongly moderated by hospital characteristics, physician characteristics, and the type of EMR implemented. 4 - Detecting Anomalous Patterns Of Care Using Health Insurance Claims Sriram Somanchi, University of Notre Dame, 344 Mendoza College of Business, Notre Dame, IN, 46556, United States, somanchi.1@nd.edu, Edward McFowland Patient care data using health insurance claims can be used to improve clinical practice by analyzing patterns across patients and providing actionable insights. Our goal in this project is to analyze this complex patient care data in order to identify interesting patterns in patient care that have led to anomalous health outcomes. Specifically, we detect treatments in the outpatient patient care that have significantly deviated from the regular treatment process and have affected health outcomes either negatively or positively. This can further help both in terms of improving patient health and reducing health care costs. SD57 Music Row 5- Omni Joint Session BOM/RMP: Consumer Behavior in Pricing and Loyalty Sponsored: Behavioral Operations Management Sponsored Session Chair: Anton Ovchinnikov, Queen’s School of Business, Kingston, ON, Canada, ao37@queensu.ca 1 - Impact Of Tiered Incentives On Behavior: Case Of The Airline Loyalty Programs Tong Guo, University of Michigan, Stephen M Ross School of Business, 701 Tappan Street, Ann Arbor, MI, 48109, United States, tongguo@umich.edu, A. Yesim Orhun This paper explores the impact of status incentives provided by a major U.S. airline on the purchasing behavior of its frequent flier program members. We leverage a database of complete transaction histories of more than six million members to study within-person changes in the distribution of price and route characteristics of tickets purchased from the airline as members progress towards a status goal. We present novel empirical manifestations of increased customer loyalty on market outcomes. 2 - Stockpile Or Redeem: How Do Consumers Value Loyalty Program Points So Yeon Chun, McDonough School of Business, Georgetown University, sc1286@georgetown.edu, Rebecca Hamilton Loyalty programs are designed to reward customers for buying more or buying more frequently from a firm. Typically, customers earn points for their purchases, which can then be exchanged for additional products and services. In a sense, these loyalty program points function as a currency that consumers can spend (redeem) on a purchase instead of money. We conduct a series of behavioral lab experiments to examine differences in the way customers think about loyalty points as compared to money, and how they choose whether to make a purchase with cash or points. 3 - Which Customers Are More Valuable In A Dynamic Pricing Situation? Jue Wang, Queen’s School of Business, Kingston, ON, Canada, jw171@queensu.ca, A. Yesim Orhun, Anton Ovchinnikov We consider a firm that dynamically price its inventory and examine whether customers who purchase at higher prices indeed add higher marginal value to the firm. We present modeling and computational results which are calibrated on a unique data set from a major travel firm.

4 - Strategic Consumers, Revenue Management And The Design Of Loyalty Programs Anton Ovchinnikov, Queen’s School of Business, ao37@queensu.ca, So Yeon Chun Several major firms recently switched their loyalty programs from quantity/’mileage’-based toward ‘spending-based’. We study the impact of this switch on firm’s profit and consumer surplus. We present a novel model of strategic consumers’ response to firm’s pricing and loyalty program decisions, incorporate such response into the firm’s pricing and loyalty program design problem, compare several plausible loyalty-program designs, and discuss managerial implications.

SD58 Music Row 6- Omni Energy IV Contributed Session

Chair: Byungkwon Park, Ph.D student, University of Wisconsin - Madison, 202 N Eau Claire Avenue, # 314, Madison, WI, 53705, United States, bpark52@wisc.edu 1 - Two-stage Multi-agent Stochastic Optimization In Power Systems Shasha Wang, Clemson University, 107 Wyeth LN, Central, SC, 29630, United States, shashaw@g.clemson.edu Harsha Gangammanavar, Sandra D Eksioglu, Scott J. Mason We present a two-stage stochastic optimization framework for a multi-agent system in which the global objective function incorporates individual agents’ objective functions. Our approach applies to the problem of managing energy in microgrids that contain integrated renewable energy resources. A sequential sampling-based, stochastic approach—stochastic decomposition—is used to analyze the problem. Computational experiments are conducted and demonstrate the effectiveness of our proposed methodology using real world case study data. 2 - Analysis Of Co2 Emission Performance And Abatement Potential For Municipal Industrial Sectors In Jiangsu, China Jie Zhang, Hohai University, Nanjing, China, zhangjie_jie@126.com, Jigan Wang, Zhencheng Xing As the main source of CO2 emissions in China, industrial sector has been faced with the tremendous pressure of reducing emissions. Based on the analysis of SBM-Undesirable model, GIS visualization method, kernel density estimation and industrial abatement model, we find that there exists a significant spatial inequality of CO2 emission performance across various regions in Jiangsu, the largest CO2 emitter in China, but the regional disparity has been narrowing during our study period. Additionally, average annual industrial CO2 emission reductions in Jiangsu can attain 15654.00 (10 thousand tons), accounting for 28.2% of its average annual actual emissions. 3 - Production Intermittence In Spot Electricity Markets Olivier Massol, IFP School, 228-232 Avenue Napoleon Bonaparte, Rueil-Malmaison, 92852, France, olivier.massol@ifpen.fr, Albert Banal-Estanol, Augusto Ruperez-Micola This paper analyses the influence of production intermittence on spot markets. We use both game theory concepts and an agent-based simulation approach derived from the Camerer and Ho (1999) behavioral model. Controlling for costs, we find that intermittent technologies yield lower prices when incumbents have individual market power, but higher when they do not have it. This happens when firms are risk-neutral and risk-averse, and also under different intermittence and ownership configurations. Replacing high-cost assets with low- cost ones results in higher prices than letting them co-exist. 4 - A Sparse Tableau Analysis Formulation For The Security- constrained Optimal Power Flow Byungkwon Park, PhD Student, University of Wisconsin-Madison, 202 N Eau Claire Avenue, # 314, Madison, WI, 53705, United States, bpark52@wisc.edu, Christopher DeMarco The nonlinear security-constrained optimal power flow (SCOPF) is computationally challenging, with difficulties in obtaining even feasible points due to the nonconvexity of power flow equations and the large dimension when many contingencies are considered. As illustrated in literature on semidefinite programming for OPF, a well-chosen formulation can yield better solutions, more efficiently. To this end, this work considers a range of SCOPF problems in new sparse tableau formulations that explicitly maintain port currents and voltages of all grid elements, and examines computational time and quality of solutions with different nonlinear solvers.

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