2016 INFORMS Annual Meeting Program

TB30

INFORMS Nashville – 2016

TB29 202A-MCC Incentives Issues in Sustainable Operations Sponsored: Manufacturing & Service Oper Mgmt, Sustainable Operations Sponsored Session Chair: Luyi Gui, The Paul Merage School of Business, UC - Irvine, Irvine, CA, United States, luyig@uci.edu 1 - Green Sourcing-the Role Of Premium Sharing And Consulting Services Xi Chen, University of Michigan - Dearborn, xichenxi@umich.edu Certified sustainable products often times enjoy a significant green premium in the retail market. In this paper, we study a retailer’s use of a sourcing contract as a tool of incentivizing suppliers to exert greening efforts which improves the chances of receiving certification, and in turn capturing the green premium. We also explore the rationale for retailer to involve in suppliers’ greening efforts. 2 - Inducing Prompt Disclosure In The Presence Of Evasive Effort Shouqiang Wang, The University of Texas at Dallas, Richardson, TX, United States, Shouqiang.Wang@utdallas.edu, Peng Sun, Francis E De Vericourt In supply chains, firms are typically exposed to negative impacts resulting from random adverse events that occur at and are privately observable to their suppliers. The firm can use fiscal instrument as well as inspections to uncover the adverse event. The supplier, however, prefers to conceal and even deliberately hide such adverse event so as to evade its responsibility. The goal of this paper is to devise optimal strategies for firms to induce the supplier’s prompt disclosure in the presence of such evasive behavior. 3 - The Adoption Of Smart Home Appliance For Energy Shifting Wenbin Wang, Shanghai University of Finance and Economics, Shanghai, China, wang.wenbin@shufe.edu.cn, Yannan Jin Smart home appliances can shift energy consumption in response to energy price and thus hold great potential for reducing the energy cost. This paper uses a game theoretical approach to analyze the consumers’ decisions on adopting smart home appliances. We study how the adoption decisions are affected by the pricing decisions of the appliance manufacturer and the utility company, as well as the government subsidy. We find the appliance manufacturer or the utility company alone may offer sufficient incentives to adopt smart home appliances. However, to increase the social welfare the government may need to interfere with these incentive programs. 4 - Incentives For Joint Product And Process Improvement Under Collective Extended Producer Responsibility Luyi Gui, UC Irvine, luyig@uci.edu Extended producer responsibility legislation mandates producers’ financial responsibility of proper post-use treatment of their products. This study investigates how the widely-adopted collective implementation of EPR legislation can promote more environmentally friendly product design and more efficient recycling technology. In particular, we analyze the impact of cost allocation choices on the joint design-technology advancement. TB30 202B-MCC Predictive Modeling in Healthcare Sponsored: Manufacturing & Service Oper Mgmt, Healthcare Operations Sponsored Session Chair: Anita L Tucker, Brandeis, 415 South Street, MS 032, Waltham, MA, 02453-2728, United States, atucker@brandeis.edu Co-Chair: Hummy Song, Harvard University, Soldiers Field, Boston, MA, 02163, United States, hsong@hbs.edu 1 - Accurate Emergency Department Wait Time Prediction Mohsen Bayati, Stanford University, bayati@stanford.edu, Erjie Ang, Sara Kwasnick, Erica Plambeck, Michael Aratow In this talk we discuss Q-Lasso method for wait time prediction, which combines statistical learning with fluid model estimators. In historical data from four remarkably different hospitals, Q-Lasso predicts the emergency department (ED) wait time for low-acuity patients with greater accuracy than existing methods. Q- Lasso achieves greater accuracy largely by correcting errors of underestimation in which a patient waits for longer than predicted. Implemented on the external website and in the triage room of the San Mateo Medical Center (SMMC), Q- Lasso achieves over 30% lower mean squared prediction error than would occur with the best rolling average method.

2 - New Core-Selecting Payment Rules With Better Fairness And Incentive Properties Benedikt Buenz, Stanford, buenz@stanford.edu Most of the recent large-scale combinatorial auctions, e.g. for spectrum rights, have used core-selecting payment rules. Such rules ensure that no subset of players is willing to outbid the total payments charged the winning players. However, while the particular rule used in practice, the Quadratic rule, is a core- selecting rule, there are many alternatives. We examine several hundred alternative core-selecting rules in Bayes-Nash equilibrium via a novel numerical solver to identify better rules. We show that Quadratic is not the optimal rule in terms of efficiency, incentives, revenue or fairness, and that we can design rules that outperform Quadratic in all of these dimensions simultaneously.

3 - Linear Item Pricing In Combinatorial Auctions Robert Day, University of Connecticut, Storrs, CT, Bob.Day@business.uconn.edu

I will present new results regarding the use of linear item prices in combinatorial auctions. Prices for items form a solution to an altered dual of WDP, are core- selecting, and constitute a combinatorial winning-level equilibrium.

TB27 201A-MCC Social Networks and Learning Sponsored: Manufacturing & Service Oper Mgmt Sponsored Session Chair: Elena Belavina, University of Chicago Booth School of Business, Chicago, IL, United States, elena.belavina@chicagobooth.edu 1 - The Use And Value Of Social Network Information In Selective Selling Ruslan Momot, INSEAD, Fontainebleau, France, Ruslan.Momot@insead.edu, Elena Belavina, Karan Girotra We consider the use and value of social network information in selectively selling goods and services whose value derives from exclusive ownership among network connections. Our model accommodates customers who are heterogeneous in their number of friends (degree) and proclivity for social comparisons (conspicuity). We show how the firm with information on either (or both) of these traits can use it to increase profits making a product selectively available to the firm’s best targets - high-conspicuity customers within intermediate-degree segments. We find that information about degree is more valuable than information about conspicuity and that the two are substitutes. 2 - The Sharing Newsboys Ming Hu, Rotman School at University of Toronto, Ming.Hu@Rotman.Utoronto.Ca We study resource sharing or demand referral behavior among a network of connected newsboys. Each newsboy only locally knows the number of his neighbors but does not know the number of his neighbor’s neighbors. Our focus is to investigate the change of the degree distribution on the newsboy decisions and social welfare. Surprisingly, we show that more connections may not lead to a higher social welfare. 3 - Information Externalities In Crowdfunding Projects We study the information externalities associated with crowdfunding projects. Crowdfunding projects suffer from the tragedy of the commons. To raise capital for successful funds requires overcoming the “startup problem”. We study and compare mechanisms to improve the project success — lotteries, seeking altruistic investments, up-front payments and quick dissemination of information. 4 - Managing Service Systems In Presence Of Social Networks Gad Allon, Wharton School, Philadelphia, PA, 19010, United States, gadallon@wharton.upenn.edu, Dennis Zhang We study a service system with the presence of a social network. In our model, firms can differentiate resource allocations among customers, and customers learn the service qualities from the social network. We study the interplay among network structure, customer characteristics, and information structure, and characterize the optimal policy. We further calibrate our model with data from Yelp.com and quantify the value of social network knowledge empirically. Senthil Veeraraghavan, Wharton School, senthilv@wharton.upenn.edu, Jiding Zhang

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