2016 INFORMS Annual Meeting Program

TC88

INFORMS Nashville – 2016

TC87 Broadway A-Omni Minority Issues Forum Paper Competition Sponsored: Minority Issues Sponsored Session Chair: Karen T Hicklin, University of North Carolina at Chapel Hill, 308 Bynum Hall, Chapel Hill, NC, 27599, United States, khicklin@email.unc.edu TC88 Broadway B-Omni Service Science Best Student Paper Competition III Award Session Chair: Robin Qiu, Penn State University, 30 E. Swedesford Road, Malvern, PA, 19355, United States, robinqiu@psu.edu 1 - Managing Service Systems With Unknown Quality And Customer Anecdotal Reasoning Hang Ren, University College London, London, United Kingdom, hang.ren.13@ucl.ac.uk, Tingliang Huang In this paper, we study a service system where customers estimate service quality from anecdotal evidence. We characterize the service provider’s pricing, quality information disclosure, and quality control decisions. We find that the service provider adopts a pricing strategy very different from the fully rational benchmark. Moreover, she should reserve quality information when queueing is more costly, and she may disclose one type of service quality anecdote but not the other type. Lastly, the service provider may reduce service quality when customers obtain more anecdotes. 2 - 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. 3 - Embedding Assignment-Routing Constraints through Multi- Dimensional Network Construction For Solving Multi-Vehicle Routing With Pickup & Delivery Time Windows Monireh Mahmoudi, Arizona State University, Tempe, AZ, United States, mmahmoudi@asu.edu, Junhua Chen, Xuesong Zhou Optimization of ride-sharing services in on-demand transportation systems involves solving a class of complex vehicle routing problems with pickup and delivery with time windows. In this paper, by embedding complex assignment- routing constraints through constructing a multi-dimensional network, we intend to reach optimality for local clusters derived from a reasonably large set of passengers on real world transportation networks. In addition, by the aid of the passengers’ cumulative service patterns defined in this paper, our solution approach is able to tackle the symmetry issue which is a common issue in the combinatorial problems. 4 - Using Patient-centric Quality Information To Unlock Hidden Health Care Capabilities Guihua Wang, Ross School of Business, University of Michigan, Ann Arbor, MI, 48105, United States, guihuaw@umich.edu, Jun Li, Wallace J Hopp We document a wide variation in quality among 188 surgeons at 35 hospitals in New York state that perform mitral valve surgery. Our analysis shows that patients of different demographics and levels of acuity benefit differently from elite surgeons. In this paper, we develop an approach for computing patient- centric information from outcome data and evaluate the potential health benefits from using such information to guide patients to surgeons. We estimate that the total societal benefits from using patient-centric information are comparable to those achievable by enabling the best surgeons to treat 40% more patients under population-average information.

2 - Scenario Generation Assessment For Stochastic Programs Didem Sari, Iowa State University, 3219 Roy Key Avenue, Unit 207, Ames, IA, 50010, United States, dsari@iastate.edu, Sarah M Ryan We propose an approach for assessing the reliability of a scenario generation method using historical outcomes. The distances among scenarios and the observed value are measured by fixing first-stage decisions to a common value and computing second-stage costs. A rank histogram constructed from these distances, motivated by mass transportation metrics, can diagnose bias or other defects. The method is demonstrated using unit commitment case studies and server location simulations. 3 - Route Optimization: A Risk Averse Shortest Path Problem Marcelo Ricardo Figueroa, Rutgers University, We study a risk-averse shortest path route optimization problem on a vehicular traffic setting, to inform users of optimal routing decisions under particular levels of risk-aversion. We make use of specialized travel-time distributions derived from analytic queueing models with Markov modulated service times to model random traffic interruptions. 4 - Developing A CCHP-microgrid Operation Decision Model Under Uncertainty Md Abdul Quddus, PhD Student, Mississippi State University, Department of Industrial & Systems Engineering, PO Box 9542, A combined cooling, heating, and power (CCHP) system provides a cost efficient solution for energy demand, energy security supply along with sustainability. The power grid is heavily vulnerable to breakdowns, natural disaster and targeted attacks. Researchers have proposed stochastic optimization models for CCHP operation for small scale (i.e. single buildings). However little attention has given for modeling CCHP units operation that satisfy multiple energy demand nodes. This study bridges the research gap by developing a scalable two stage stochastic programming model for large scale micro-grid operation under uncertainty considering a larger number of scenarios. TC86 GIbson Board Room-Omni Marketing VII Contributed Session Chair: Rajeev Kumar Tyagi, Professor, University of California, Irvine, 5 Murasaki, Irvine, CA, 92697, United States, rktyagi@uci.edu 1 - Showrooming And The Length Of Product Line Yilong Luo, Illinois Institute of Technology, 6716 Idaho Avenue, Hammond, IN, 46323, United States, yluo4@hawk.iit.edu, Jiong Sun Showrooming is a strategy that consumers touch and feel the products in the offline store but purchase from online store which usually offer a lower price. As the improvement of technology, like high speed internet and mobile phone, showrooming are widely applied by consumers. Thus offline stores always regard showrooming as something evil and attribute the sales decline to this effect. In our paper, however, we explore the strategy that brick store can actually benefit from showrooming effect by partially carrying the product line. We also show that the presence of showrooming behavior may or may not induce the brick-and- mortarretailer to reduce the length of the product line it carries. 2 - A Model Of Cause-related Marketing Sreya Kolay, Assistant Professor, University of California, Irvine, Irvine, CA, 92697, United States, skolay@uci.edu Cause-related marketing (CRM) is the popular practice of linking purchases to donations made to charitable causes. They include price-based CRM policies wherein a firm donates a percentage of revenues or profits for every purchase made, or quantity- or unit-based CRM policies wherein the firm donates a unit of its own product for every unit purchased. In this paper, we develop an analytical model to examine conditions on consumer valuations and seller’s cost structure that determine the optimality of CRM, price-based CRM, and quantity-based CRM from the perspective of a seller. We also compare and contrast these conditions with those that maximize donations and social welfare. 3 - Optimal Pricing Of Multiple Events Rajeev Kumar Tyagi, Professor, University of California, Irvine, 5 Murasaki, Irvine, CA, 92697, United States, rktyagi@uci.edu Event organizers often sell a series of events that occur sequentially over time. For example, concert series with multiple performers and sports tournaments. Consumers may enjoy more than one event in the series, and the events may differ in popularity with the audience (e.g. two operas of different popularity in successive months, pre-season games followed by more popular regular-season games). In this paper, we analytically characterize the optimal pricing and bundling strategy of such an event organizer. We allow for sellers who can commit to future prices as well as those who cannot. 93 Marvin Lane, Piscataway, NJ, 08854, United States, marcelo.figueroa@rutgers.edu, Melike Baykal-Gursoy Starkville, MS, 39762, United States, mq90@msstate.edu, Carlos Marino, Mohammad Marufuzzaman, Mengqi Hu

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