2015 Informs Annual Meeting

MC44

INFORMS Philadelphia – 2015

MC45 45-Room 103C, CC

3 - Selling Information in Oligopolies Alireza Tahbaz-Salehi, Columbia Business School, 3022 Broadway, Uris Hall 418, New York, NY, 10023, United States of America, alirezat@columbia.edu, Kostas Bimpikis, Davide Crapis This paper studies the strategic interaction between a monopolist seller of an information product and a set of potential buyers that compete in a downstream market. We argue that the nature of competition among the buyers largely determines the price and accuracy of the product that the monopolist decides to sell. 4 - Analysis of a Simple Cost Allocation Rule for Joint Replenishment Xuan Wang, New York University, 44 West 4th Street, Suite 8-154, New York, NY, 10012, United States of America, xwang3@stern.nyu.edu, Jiawei Zhang, Simai He, Jay Sethuraman We consider the joint replenishment game in which the major setup cost is split equally among the retailers who place an order together. Each retailer pays his own holding and minor setup cost. Under this allocation rule each retailer determines his replenishment policy to minimize his own cost anticipating the other retailers’ strategy. We show that a payoff dominant Nash equilibrium exists and quantify the efficiency loss of the non cooperative outcome relative to the social optimum. MC44 44-Room 103B, CC Empirical and Data-Driven Research in Revenue Management and Pricing Sponsor: Revenue Management and Pricing Sponsored Session Chair: Jun Li, Assistant Professor, Ross School of Business, University of Michigan, 701 Tappan St, Ann Arbor, 48103, United States of America, junwli@umich.edu Co-Chair: Serguei Netessine, Professor, INSEAD, 1 Ayer Rajah Avenue, Singapore, 138676, Singapore, Serguei.Netessine@insead.edu 1 - Interpreting “3 Seats Left”: An Empirical Analysis of Airline Inventory Announcements Kate Ashley, UC Berkeley Haas School of Business, 2220 Piedmont Ave, Berkeley, CA, 94720, United States of America, kate_ashley@haas.berkeley.edu, Pnina Feldman, Jun Li Does inventory announcement affect the timing of customer purchases? We estimate the impact of inventory announcement policy on purchases of airline tickets. We analyze the extent to which customers treat messages from the firm as cheap talk or credible information, and the extent to which firms use announcements strategically to influence demand. 2 - Contextual Treatment Selection and its Application to Pricing Optimization Yan Zhao, MIT, 77 Mass Ave, 1-245, Cambridge, MA, United States of America, zhaoyan@mit.edu With the rapid growth of eCommerce, the wealth of data makes it possible to exploit the heterogeneity among customer pricing sensitivity and maximize revenue. We develop a general framework for the customized pricing problem and propose a tree-based algorithm, which shows superior performance on both simulated data and real transaction data. Under mild regularity conditions we prove the upper bound of the difference of expected revenue between a simplified version of our algorithm and an oracle. 3 - Dynamic Pricing and Inventory Management: An Empirical Perspective Yan Shang, PhD Student, Duke University, 845 Ivy Meadow Ln, This paper applies structural modeling to study joint inventory and pricing management of perishable product, using fresh vegetable data from the largest state-owned supermarket chain in China. Demand of fresh vegetables depends not only on price but also freshness, and complementarity exists between items. We use a multiple continuous model to incorporate these features. Based on demand estimates, optimal prices are solved, which achieves significant profit improvement and waste reduction. Apt. 3D, Durham, NC, 27707, United States of America, yan.shang@duke.edu, Yiting Deng, Jing-Sheng Song

From Store to Omni-Channel: Choice-Driven Pricing Models Sponsor: Revenue Management and Pricing Sponsored Session Chair: Stefanus Jasin, Stephen M. Ross School of Business, University of Michigan, Ann Arbor, MI, United States of America, sjasin@umich.edu Co-Chair: Joline Uichanco, Asst. Professor, University of Michigan, Ross School of Business, 701 Tappan Ave, Ann Arbor, MI, 48109, United States of America, jolineu@umich.edu 1 - Drivers of Demand for Consumer Packaged Goods that Have Wide Variations in Price and Perceived Quality Olga Pak, Student, University of South Carolina, 1014 Greene Street, Columbia, SC, 29208, United States of America, olga.pak@grad.moore.sc.edu, Mark Ferguson In joint work with Oracle Retail, we identify the drivers of demand for consumer packaged goods that have wide variations in price and perceived quality. We investigate the problem with the use of hierarchical models on retail transaction data across multiple market and store locations to analyze the influence of prices, promotions and individual store effects. 2 - Integrated Lifecycle Price and Inventory Optimization in an Omni-channel Environment Pavithra Harsha, IBM, 1101 Kitchawan Road, Room 34-225, Yorktown Heights, NY, 10598, United States of America, pharsha@us.ibm.com, Shivaram Subramanian, Joline Uichanco, Markus Ettl In an omni-channel environment, inventory is shared across channels through multiple fulfillment options (e.g. ship-from-store). Without accounting for this, existing pricing solutions take steep markdowns in stores. We present a tractable optimization model to determine optimal lifecycle channel prices, inventory allocations and partitions across channels that maximizes the total chain level profit. Our experiments show a 6-12% improvement in profit over multiple categories of a large retailer. 3 - Data-driven Learning in Dynamic Pricing using Adaptive Optimization Phebe Vayanos, Assistant Professor, University of Southern California, 3551 Trousdale Pkwy, University Park, Los Angeles, CA, 90089, United States of America, pvayanos@mit.edu, Dimitris Bertsimas We consider the pricing problem faced by a retailer endowed with a finite inventory of a product with unknown demand curve offered to price-sensitive customers. We formulate the seller’s problem as an adaptive optimization problem with decision-dependent uncertainty set and propose a tractable solution approach. Pricing and Strategic Behavior in Queueing Systems Sponsor: Manufacturing & Service Oper Mgmt/Service Operations Sponsored Session Chair: Philipp Afeche, Associate Professor, University of Toronto, 105 St. George Street, Toronto, ON, M5S3E6, Canada, afeche@rotman.utoronto.ca 1 - Pricing, Diagnosis and Overtreatment in Expert Services Senthil Veeraraghavan, Associate Professor, The Wharton School, 3730 Walnut St, Philadelphia, PA, 19104, United States of America, senthilv@wharton.upenn.edu In many services, consumers must rely on advice of experts to identify the type of treatment/service they need. The information asymmetry between service provider and the consumers creates inefficiencies in the form of cheating and over-treatment. We show that congestion and waiting costs act as natural “fraud costs” which mitigate cheating, inducing honesty and increasing social welfare. We show the informational value of pricing in inducing either honesty or overtreatment. MC46 46-Room 104A, CC

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