2016 INFORMS Annual Meeting Program

TA58

INFORMS Nashville – 2016

3 - “Hidden Profiles” In Corporate Prediction Markets: The Impact Of Public Information Precision And Social Interactions Jingchuan Pu, University of Florida, Gainesville, FL, United States, jingchuan@ufl.edu, Liangfei Qiu, Hsing K Cheng Recently, large companies are experimenting with corporate prediction markets run among their employees. we develop an analytical model to analyze the effects of information precision and social interactions on prediction market performance. But increased precision of public information is not always beneficial to prediction market accuracy because of the “hidden profiles” effect: participants place a larger than efficient weight on existing public information. A socially embedded prediction market with information sharing mechanism may help correct such inefficiency. We also identify conditions under which increased precision of public information is detrimental in both cases. 4 - Credit Card Companies And Is-integrated Marketing Platforms: A Comparison Of Social Network Promotions And Targeted Promotions Soohyun Cho, University of Florida, Gainesville, FL, United States, soohyun.cho@warrington.ufl.edu, Liangfei Qiu, Subhajyoti Bandyopadhyay In this paper, we investigate two types of marketing promotions that credit card companies have recently been featuring in collaboration with partnered retailers: public promotions through social networking services and targeted promotions through companies’ websites. To analyze the strategic impacts on the promotion’s participants (including companies/retailers and consumers), we develop a game theoretical model and then determine the best strategies for different participants. The study is extended by considering the advertising effect of social network services as well as security issues involving targeted promotions. TA57 Music Row 5- Omni Insights from Relaxing Traditional Modeling Assumptions about Human Behavior in OM Settings Sponsored: Behavioral Operations Management Sponsored Session Chair: Jordan Tong, Wisconsin School of Business, 4293 Grainger Hall,

4 - Selling To Experience-sampling Customers: Quality Conformance, Pricing, And Promotions Gregory A DeCroix, University of Wisconsin - Madison, greg.decroix@wisc.edu, Jordan Tong We consider a firm that sells a service, the quality of which is stationary but stochastic. Customers cannot directly observe mean quality, but instead base their estimate of quality on their own past purchases. Customers are risk neutral but boundedly rational - their purchase decisions are described by a logit model based on customer surplus (estimated quality minus price). We explore several phenomena that arise in such a setting. For example, poor quality conformance (high service variability) leads to reduced sales revenues, even though customers are risk neutral. In addition, under certain circumstances occasional promotions can help counter this erosion in revenues. TA58 Music Row 6- Omni Energy VX Contributed Session Chair: Ruediger Schultz, University of Duisburg Essen, Thea-Leymann- Str. 9, Essen, D-45127, Germany, ruediger.schultz@uni-due.de 1 - Managing Stored Energy In Microgrids Via Multistage Stochastic Programming Arnab Bhattacharya, PhD Candidate, University of Pittsburgh, 1031 Benedum Hall, 3700 O’Hara Street, Pittsburgh, PA, 15261, United States, cfcarnabiitkgp@gmail.com, Jeffrey P. Kharoufeh, Bo Zeng Energy storage systems are used to mitigate adverse effects of renewable sources in a microgrid where procurement and storage decisions are made under uncertain demand, renewable supply and prices. A multistage stochastic programming (SP) model is formulated to minimize the expected total costs in a microgrid. To improve computational tractability of the SP model, a customized stochastic dual-dynamic programming (SDDP) algorithm is employed to obtain high-quality solutions within reasonable time bounds. A numerical study highlights significant cost reductions and computational benefits. 2 - A Crowdfunding Model For Green Energy Investment Ying Xu, Assistant Professor, Singapore University of Technology Motivated by emerging community solar farms, this paper studies a new renewable energy investment model through crowdfunding. We develop a sequential game theory model to capture the interactions among crowdfunders, the solar farm owner, and an electricity company in a multi-period framework. We find that under crowdfunding although the farm owner reduces its investment level, the overall green energy investment level is increased due to the contribution of crowdfunders. We also find that crowdfunding can increase the penetration of green energy in consumption. Finally, the numerical results based on real data indicates crowdfunding is a simple but effective way to boost green generation. 3 - Incentive-based Coordination Mechanism For Backup Renewable Energy Investment Due to the intermittent nature of renewable energy, the renewable energy producers are exposed to high risks in delivering what they have already committed to the energy market. Cooperating with other market participants like conventional energy producers poses a possibility to mitigate this issue. Using stochastic modeling formulation, this paper aims to find optimal bidding strategies that provide incentive for both renewable and conventional power producers to cooperate with each other. Additionally, the trading volume and price between the participants are determined by using Nash game framework. Numerical experiments have been conducted to verify the effectiveness of the model. 4 - Nomination Validation In Gas Grids Under Uncertainty Ruediger Schultz, University of Duisburg Essen, Thea-Leymann- Str. 9, Essen, D-45127, Germany, ruediger.schultz@uni-due.de Gas flows in the pipes and pressures at the nodes, both under uncertainty of gas withdrawals from the network (loads) at exit (delivery) nodes are studied. Assuming the uncertainty of withdrawals is stochastic with known distributions, methods for calculating probabilities for the feasibility of load coverage are presented. Emphasis is placed on mildly meshed networks. Sadra Babaei, Oklahoma State University, Stillwater, OK, United States, sadra.babaei@okstate.edu, Chaoyue Zhao and Design, Singapore, Singapore, xu_ying@sutd.edu.sg, Ronghuo Zheng, Nilanjan. Chakraborty, Katia P. Sycara

Madison, WI, 53706, United States, jtong@bus.wisc.edu 1 - Utility Based Queueing: Predicting Delay When Servers Are Strategic Amy Ward, University of Southern California, amyward@marshall.usc.edu, Sherwin Doroudi,

Ragavendran Gopalakrishnan, Adam Wierman, Dongyuan Zhan Most common queueing models used for service system design assume the servers work at fixed (possibly heterogeneous) rates. However, real-life service systems are staffed by people, and people may change their service speed in response to incentives. To model this, we assume each server selfishly chooses his service speed in order to maximize his expected utility. Under various assumptions on the utility function, we characterize the equilibrium service

speed, which can then be used to estimate system performance. 2 - Service Systems With Unknown Quality & Customer Anecdotal Reasoning

Tingliang Huang, Carroll School of Management, Boston College, 140 Commonwealth Avenue, Chestnut Hill, MA, 02467, United States, tingliang.huang@bc.edu, Hang Ren, Kenan Arifoglu We consider a service system where customers do not know the distribution of uncertain service quality and cannot estimate it fully rationally; instead, they form beliefs by taking sample averages of anecdotes. The number of anecdotes can be used to measure to what extent customers are boundedly rational. We characterize customers’ joining behavior and the server’s pricing and quality decisions. 3 - The Effect Of Social Information On Demand In Quality Competition Dayoung Kim, Cornell University, dk668@cornell.edu We investigate the impact of different types of social information on the demand characteristics of firms competing through service quality. We develop a Hidden Markov model to understand the choice mechanism of a consumer under social information. We then conduct a lab experiment where a consumer chooses to visit one of two firms, each with unknown service quality. In the experiment, a consumer may have access to (1) no information, (2) market “share-based” social information, or (3) “quality-based” social information. Our results show that different types of information have dramatically different effects on firms’ market shares and demand uncertainty.

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