2015 Informs Annual Meeting

TA53

INFORMS Philadelphia – 2015

4 - Strategic Consumers, Revenue Management and the Design of Loyalty Programs So Yeon Chun, McDonough School of Business, Georgetown University, 3700 O St. NW, Washington, DC, United States of America, sc1286@georgetown.edu, Anton Ovchinnikov Several major airlines recently switched their loyalty programs from ``mileage/segment-based” toward ``spending-based”. We study the impact of this switch on firm’s profit and consumer utility. 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 the solutions under the mileage-based versus spending-based design, and discuss managerial implications. TA51 51-Room 106B, CC Economics of Innovation in Supply Chains Sponsor: Manufacturing & Service Operations Management Sponsored Session Chair: Ayhan Aydin, Assistant Professor Of Operations Management, George Mason University School of Business, 4400 University Drive MS 5F4, Fairfax, VA, 22030, United States of America, aaydin2@gmu.edu 1 - Product Quality in a Decentralized Supply Chain: Value of Information Asymmetry Narendra Singh, Narendra.Singh@scheller.gatech.edu, Stylianos Kavadias, Ravi Subramanian We study an OEM’s optimal product design quality and sourcing strategies in a supply chain consisting of an OEM, who has in-house option, and a supplier, who has more favorable cost structure and the power to dictate contract terms. We show that a two-part tariff contract, as opposed to a price-only contract, may leave both the OEM and the supplier worse off. Further, we show that asymmetric information about the OEM’s cost structure may lead to higher profits for both the OEM and the supplier. 2 - Information Acquisition and Innovation in Competitive Markets Yi Xu, Associate Professor, Smith School of Business, University of Maryland, College Park, MD, 20742, United States of America, yxu@rhsmith.umd.edu, He Chen, Manu Goyal In this paper, we study firms’ information acquisition strategies and innovation strategies in a competitive market with uncertainty. The firms can resolve the market uncertainty through different information acquisition methods. We highlight the strategic interactions between information acquisition and innovation investments in such a market. 3 - Investment in Core Technologies and Consumer Markets Ayhan Aydin, Assistant Professor Of Operations Management, George Mason University School of Business, 4400 University Drive MS 5F4, Fairfax, VA, 22030, United States of America, aaydin2@gmu.edu, Rodney Parker We consider a two-tier supply chain, an upstream tier composed of two competing providers of a component that is used by multiple OEMS (integrators) in the lower tier. Upstream firms invest to develop the technology of the component further. We investigate the effects of downstream market factors, the nature of technology, competition, and the level of uncertainties in the R&D process on the level of upstream investments and the adoption of the higher technologies by the downstream firms. TA52 52-Room 107A, CC Consumer-driven Management Science Sponsor: Marketing Science Sponsored Session Chair: Ricardo Montoya, Assistant Professor, University of Chile, Republica 701, Santiago, Chile, rmontoya@dii.uchile.cl 1 - Product Showcasing in the Presence of Experience Attributes Daria Dzyabura, Assistant Professor of Marketing, NYU Stern School of Business, 40 West 4th Street, Tisch 805, New York, NY, 10012, United States of America, ddzyabur@stern.nyu.edu, Srikanth Jagabathula We formalize a firm’s showcase decision, or selecting a subset of products to carry in a physical store, while a ‘large’ product line is offered through the online channel. Some customers visit the offline store to gain information about product features. We formalize the showcase problem as an IP, which we show to be NP- complete, derive closed-form solutions for special cases, and adapt the local search heuristic to the general problem. We gather conjoint data to estimate the model parameters.

2 - Price Drop Protection Policy with Partial Refunds Dinah Cohen-Vernik, Assistant Professor Of Marketing, Rice University, 6100 Main St, Houston, TX, 77006, United States of America, dv6@rice.edu, Amit Pazgal Many retailers now offer to refund customers the full price difference as long as the price drop occurred within a specified short period of time after the purchase. Despite the popularity of such policy, the existing marketing research on the topic is scarce. In this paper we investigate the price difference refund policy (referred to as price drop protection) and demonstrate how it can improve retailer’s profits. 3 - Clicks and Editorial Decisions: How Does Popularity Shape Online News Coverage? Pinar Yildirim, Assistant Professor Of Marketing, The Wharton School. University of Pennsylvania, 748 Huntsman Hall, Philadelphia, PA, 19104, United States of America, pyild@wharton.upenn.edu, Ananya Sen Using online news data from a large Indian English daily newspaper, this paper analyzes how demand side incentives shape news media reporting. To establish a causal link, we instrument the views of articles using days with rain and days with electricity shortage as exogenous shocks to reader attention. We provide evidence for extended coverage and higher resource allocation to issues which receive high number of clicks. 4 - Stock-out Detection System Based on Sales Transaction Data

Ricardo Montoya, Assistant Professor, University of Chile, Republica 701, Santiago, Chile, rmontoya@dii.uchile.cl, Andres Musalem, Marcelo Olivares

We present a methodology based on real-time point-of-sales data to infer on-shelf product availability. We develop our methodology using process control theory an apply it to a big-box retailer. We use historical transactional data to develop our methodology and empirically test it in two field studies. We analyze the results and implications.

TA53 53-Room 107B, CC

Behavior in Operational Contexts Sponsor: Behavioral Operations Management Sponsored Session Chair: Anton Ovchinnikov, Queen’s University, 143 Union Str, West, Kingston, Canada, anton.ovchinnikov@queensu.ca 1 - Behavioral Ordering: Inventory, Competition and Policy Bernardo Quiroga, Assistant Professor, Business And Behavioral Science, Clemson University, 100 Sirrine Hall, Clemson, SC, 29634, United States of America, bfquirog@gmail.com, Anton Ovchinnikov, Brent Moritz We study the effect of observed inventory decisions on performance. Our goal is to measure and understand profit losses due to behavioral (intuitive but suboptimal) ordering. The current literature, primarily focused on a newsvendor making decisions in isolation, reports results implying profit losses of 1-5% compared to the analytical optimum. In contrast, we show that when a behavioral inventory manager competes against a management-science-driven competitor, profit losses are much larger. 2 - Inequity and Loss Aversion in Pay What You Want Yulia Vorotyntseva, PhD Candidate, The University of Texas at Pay-What-You-Want pricing is an exemplar of fairness-driven behavior in a business context: the price for a product is fully determined by a buyer, and the seller cannot reject any offer. The objective of our work is to find out key factors affecting the buyers’ selection of prices under PWYW. We use a distributional fairness approach and build a hierarchical Bayesian model of buyers’ behavior. We then test it in a controlled laboratory experiment. 3 - Inventory Decisions in the Presence of Strategic Consumers Yaozhong Wu, National University of Singapore, NUS Business School, Singapore, Singapore, yaozhong.wu@nus.edu.sg, Yang Zhang, Benny Mantin In the presence of strategic consumers, who may delay their purchase to the markdown season, a retailer is faced with an extra consideration in addition to the traditional newsvendor setting: excess inventory may induce strategic consumers to delay their purchase and may further harm the revenue. We develop a model that accounts for both the strategic consumers and the retailer’s inventory decisions. We design behavioral experiments to test our model predictions. Dallas, Richardson, United States of America, Yulia.Vorotyntseva@utdallas.edu, Ozalp Ozer

275