Informs Annual Meeting 2017

TC11

INFORMS Houston – 2017

TC09

2 - Resolving Supplier Information Asymmetry: Reliability or Improvement Cost? Yutian Li, PhD Candidate, University of Miami, Coral Gables, FL, 33146, United States, ytli@umiami.edu, Sammi Tang We consider a manufacturer who sources from an unreliable supplier. The supplier can take costly effort to improve its reliability, but has private information about both its initial reliability level and improvement cost. We examine which type of supplier information is more valuable to the manufacturer. For that, we study two models with different asymmetric information, and compare how each type of information affects manufacturer’s Weihua Zhang, University of British Columbia, Sauder School of Business, University of British Columbia, Vancouver, BC, V6T.1Z2, Canada, weihua.zhang@sauder.ubc.ca, Hao Zhang We examine a classic machine-maintenance problem in which the state of the system evolves as a hidden Markov process under production. The state can be observed upon inspection and reset by replacement. The goal is to find a production-inspection-replacement policy to minimize the expected discounted cost over an infinite horizon. We adopt a new framework to derive an exact, analytical solution to this problem and uncover an elegant cyclic structure in the optimal solution, which are unavailable through the Bayesian framework. We find that the well-known and puzzling non-monotone optimal policy results from the transient behavior under optimal control. 4 - Position Ranking and Auctions for Online Marketplaces Heng Zhang, University of Southern California, Los Angeles, CA, 91776, United States, hengz@usc.edu, Leon Yang Chu, Hamid Nazerzadeh E-commerce platforms connect thousands of sellers and consumers every day. We study how such platforms should rank products displayed, and utilize the top slots with auction design. We present a model that considers consumers’ search costs and seller externalities. This model allows us to study a multi-objective optimization, whose objective includes consumer and seller surplus, and sales revenue, and derive the optimal ranking. Motivated in part by the sponsored search program, we propose a so-called surplus-ordered ranking mechanism for selling top slots, which is near-optimal. When the platform sells all slots, we show that our mechanism can be implemented as a NE in a modified GSP auction. Service Operations Sponsored Session Chair: Sukriye Nilay Argon, University of North Carolina, Chapel Hill, NC, 27599, United States, nilay@unc.edu Co-Chair: Serhan Ziya, University of North Carolina, Chapel Hill, NC, 27599, United States, ziya@unc.edu 1 - Do Mandatory Overtime Laws Improve Quality? Staffing Decisions and Operational Flexibility of Nursing Homes Lauren Xiaoyuan Lu, University of North Carolina at Chapel Hill, Kenan-Flagler Business School, CB #3490, Mccoll Building, Chapel Hill, NC, 27599, United States, lauren_lu@unc.edu, Susan F.Lu During the 2000s, over a dozen U.S. states passed laws that prohibit health care employers from mandating overtime for nurses. Using a nationwide panel dataset from 2004 to 2012, we find that these mandatory overtime laws reduced the service quality of nursing homes, as measured by an increase in deficiency citations. This outcome can be explained by two undesirable changes in the staffing hours of registered nurses: decreased hours of permanent nurses and increased hours of contract nurses per resident day. These observations are consistent with the predictions of a stochastic staffing model that incorporates demand uncertainty and operational flexibility. 2 - Transitional Care Appointment Scheduling Benjamin Grant, Kellogg School of Management, 1881 Oak Avenue, # 1307W, Evanston, IL, 60201, United States, b-grant@kellogg.northwestern.edu, Itai Gurvich, R. Kannan Mutharasan, Jan A. Van Mieghem In this paper we develop a framework modeling transitional-care appointment scheduling from the perspective of the hospital or social planner who takes into account the total cost of transitional-care under a value-based compensation model. We employ a stochastic dynamic programming model rich enough to capture many of the complexities that exist in practice, while enabling interesting insights and evaluation of a variety of simple scheduling policies compared to theoretical optimal policies. profit, information rent and channel loss differently. 3 - Analytical Solution to a Partially Observable Machine-maintenance Problem TC11 332A Healthcare Operations Sponsored: Manufacturing & Service Oper Mgmt,

330A Big Data and Innovation Sponsored: Manufacturing & Service Oper Mgmt Sponsored Session

Chair: Serguei Netessine, University of Pennsylvania, Wharton School, Philadelphia, PA, 138676, United States, serguei.netessine@insead.edu 1 - When to Innovate and When to Grow? Empirical Analysis of Startup Operation Christophe Pennetier, INSEAD, 6 Marina Boulevard, # 27-15, Singapore, 018985, Singapore, christophe.pennetier@insead.edu, Serguei Netessine, Karan Girotra We conduct a thorough examination of the effects of business model innovation on startups’ performance (probability to raise funding, exit) and we empirically evaluate them. We by that offer a new perspective to the pivoting approach that has captured practitioners’ attention in the past few years since the Lean Startup framework became widely adopted. 2 - Impact of Telematics: An Empirical Study of Drivers’ Behavior Vivek Choudhary, INSEAD Business School, 1 Ayer Rajah Avenue, Singapore, 138676, Singapore, Vivek.Choudhary@insead.edu, Serguei Netessine Telematics is one of the hottest developments in the automobile insurance industry. Adoption of this innovation suggests that this is going to be the future of motor insurance. We study a novel private dataset from a start-up company operating in this space. Using this dataset, which consists of trip level details; we study the effect of providing feedback of drivers’ behaviour on driving performance. 3 - Impact of Mobile Channel on Demand Concentration Fangyun Tan, Southern Methodist University, 6212 Bishop Blvd, Dallas, TX, 75275, United States, ttan@cox.smu.edu, Nitish Jain We analyze a large transactional data from an Indian online apparel to understand the impact of mobile channel on demand concentration. Utilizing the natural experiment where the company shut down its PC channel and kept only their mobile channel, we find that the mobile channel reduces the demand concentration because its search costs are higher than those in the PC channel. We show evidence of the mechanisms and discuss the implications for operational decisions. 4 - Reading Between the Stars: Understanding the Effect of Online Customer Reviews on Product Demand Many studies have examined star ratings in customer reviews and established that they are a relevant source of quality information. We examine the sentiments of text reviews and study the interplay between sentiments and star ratings and how this relates to product demand. To fully exploit the abundance of online reviews, we implemented a novel algorithm that reads the text portion of customer reviews and assesses its sentiment. We find that sentiments and star ratings both have a decreasingly positive effect on product demand and that their interaction effect on demand suggest they act as complements, not substitutes. 330B Value of Information in Games and Mechanism Design Sponsored: Manufacturing & Service Oper Mgmt Sponsored Session Chair: Leon Zhu, University of Southern California, Los Angeles, CA, 90089, United States, leonyzhu@usc.edu 1 - Price Competition in Customer Inertia Markets with Capacity Uncertainty Junhyun Bae, Cornell University, Ithaca, NY, United States, jb2258@cornell.edu, Li Chen, Yao Cui In this paper, we investigate price competition under capacity uncertainty in which consumers have costs of switching between two firms. While previous literature has examined the effect of switching costs on prices, our paper addresses the effect of capacity uncertainty on prices. Using a two-period duopoly setting, we show that capacity uncertainty increases price in both periods and it diminishes price discount in the first period. Hallie Cho, INSEAD, Singapore, 138676, Singapore, hallie.cho@insead.edu, Sameer Hasija, Manuel Sosa TC10

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