Informs Annual Meeting Phoenix 2018

INFORMS Phoenix – 2018

TE52

4 - Why Low Quality Firms Facilitate P2P Sharing While High Quality Firms do Not Chenchen Di, UIUC, Champaign, IL, 61820, United States, Yunchuan Liu We study whether and when should a firm actively facilitate consumers’ sharing behavior by reducing transaction costs in a competitive market considering consumer usage uncertainty and consumer heterogeneity in transaction costs. This research provides another rationale for seller-induced sharing strategy. We show that seller-induced sharing behavior depends on consumers’ usage uncertainty: when consumers face the great uncertainty of future needs, firms can actually benefit from facilitating consumer sharing by making it more convenient. In competitive sharing markets, the low-quality firm will choose to facilitate consumer sharing, and the high-quality firm will not. 5 - Timely Exposure of a Secret Project: Which Activities to Monitor? Ben Hermans, PhD Student, KU Leuven, Naamsestraat 69, Leuven, 3000, Belgium, Herbert Hamers, Roel Leus, Roy Lindelauf A defender wants to detect as quickly as possible whether some attacker is secretly conducting a project that could harm the defender. The attacker, in turn, schedules his tasks so as to remain undiscovered. One pressing question for the defender is: which activities to focus intelligence efforts on? We model the situation as a zero-sum game, establish that the late start schedule is a dominant attacker strategy, and derive a dynamic program that identifies the defender’s optimal response. We evaluate the harm-reduction thanks to each task’s intelligence effort by means of the Banzhaf value and illustrate our methods on a nuclear weapons development project. n TE50 North Bldg 231A Practice- Retail Management I Contributed Session Chair: Rachel Rong Chen, University of California-Davis, 3208 Gallagher Hall, One Shields Avenue, Davis, CA, 95616, United States 1 - Differential Effects of Product Variety on Retailing Performance Guanyi Lu, Florida State University, Tallahassee, FL, United States, Hyunseok Lee, Junbo Son Using transaction-level data from a local grocery store, we study how different types of product variety affect retailing sales and profit. Our results have managerial implications on product assortment, which may help retailers achieve better performance. 2 - Dynamic Labour Allocation to Improve Store Performance Shandong Mou, University of Auckland, 12 Grafton Road, Room 5121, OGGB, Auckland, 1142, New Zealand, David Robb Despite considerable research on workforce planning, there is limited coverage of real-time labour allocation - a common practice to address real-time mismatches between the demand and supply of labour among departments. We propose a mathematical framework modelling real-time labour allocation and construct heuristics in the context of retail stores. We conduct simulation experiments to compare the performance of heuristics with static and intuitive policies. Simulation results show proposed heuristics outperform other policies. 3 - The Impact of Capacity Changes on Labor Productivity in Retailing Chien-Ming Chen, Nanyang Technological University-Singapore, 50 Nanyang Avenue, Singapore, 639798, Singapore, Hao-Chun Chuang Matching in-store staffing level with shopper traffic has been a long-standing principle in retail operations. Using data from a large retail chain, we show that increment of manpower can adversely affect marginal labor productivity in the conversion and sales-generation process. Our findings suggest that managers should be wary of the dark side of capacity increment in the retail environment. 4 - Product Returns, Rebates, and Restocking Fees Rachel Rong Chen, University of California-Davis, 3208 Gallagher Hall, One Shields Avenue, Davis, CA, 95616, United States, Eitan Gerstner, Daniele Ragaglia, Paolo Roma We compare the profitability of rebate and restocking fee policies to manage consumer product returns. We show that the use of rebates can be more profitable than the commonly used restocking fee policy under certain conditions.

n TE52 North Bldg 231C Flash Session III General Session Chair: INFORMS, 5521 Research Park Drive, Suite 200, Catonsville, MD, 21228, United States 1 - Eco-conscious Returns for Retail Andrew Downard, Senior Product Manager, Happy Returns, 1106 Broadway, Santa Monica, CA, 90401, United States Much of the cardboard used for online shopping is from the high return rates and the inefficiency of individual returns by mail. At Happy Returns, we created a new box-free return model designed for minimal environmental impact. Returns are accepted at a nationwide network of 250+ Return Bars at the beginning of the process and shipped in bulk in reusable packaging to nearby hubs for routing to the most efficient destinations. In this presentation we quantify the environmental impact of box-free returns, and share our vision for making returns even happier for shoppers and for the environment. 2 - A Note on Newsvendor Problem with Optimism Coefficient Milena Bieniek, Maria Curie-Sklodowska University Lublin, Lublin, Poland We study the satisficing newsvendor problem, where the optimal order quantity is chosen by the maximization of the probability of exceeding the expected profit multiplied by a positive constant. This constant called optimism coefficient can be chosen by the firm’s management by preference or by available market opportunities. The coefficient indicates whether we deal with low or high optimistic decision maker. For general demand distribution the results are significantly dependent on this coefficient. The numerical example is given for normally distributed demand. 3 - Minimizing Idle Time and Late Start Time in Surgery Using Simulation Vikas Agrawal, Jacksonville Universtiy, 204 Ann Scott Drive, Saint Johns, FL, 32259, United States, Aber Elsaleiby, Yue Zhang, P. Sundararaghavan, Andrew Casabianca In this paper, we address a surgery scheduling problem in a hospital setting. Typically surgeries can be started only on or after the scheduled start time. Given that surgery time is stochastic in nature, it can go beyond the scheduled finish time in which case the next scheduled surgery will be delayed. Likewise, a surgery can be finished earlier than the scheduled finish time in which case the operating room will remain ideal until the star of next scheduled surgery. Both of these situations are undesirable. For this problem, we develop a simple method to assign start times so as to minimize the sum of idle times of the OR and late start times of the surgeries. 4 - Approximating Maximin Fair Guarantee Setareh Taki, University of Illinois at Urbana-Champaign, Champaign, IL, United States, Jugal Garg We present new results in allocating indivisible items to agents which is within a constant factor of their maximin share. 5 - Using Real-time Operational Data to Increase Labor Productivity in Retail This research is focused on developing models to support dynamic systems that can reassign labor to different activities. This work utilizes data from a pilot study in a store of a home improvement retail chain in the U.S. Security cameras were used to track the number of customers and employees on different sections. We use these operational data to measure - in real time - the demand for services in a specific store department, and the service capacity. This information can be linked to point of sales data, to measure the effect of the number of employees on the sales of specific departments. All this provide information for a dynamic labor allocation system in order to prioritize where to allocate employees. 6 - A Grounded Theory Model for Big Data in Supply Chain Mohammad Baitalmal, PhD Candidate, University of North Texas, Denton, TX, 76210, United States Mohammad Baitalmal, PhD Candidate, King Saud University, Riyadh, Saudi Arabia, Victor R. Prybutok, Abdulrahman Habib This research investigates the big data phenomena within supply chain and logistics using interviews to undertake a grounded theory approach. The current state of the literature indicates a gap in understanding the impact of big data’s emergence on the supply chain. To answer the call of Waller and Fawcett (2013) for detailed inductive research to understand changes in the supply chain as a result of using big data. The results of this research provide a theoretical framework that relates big data and the supply chain. Pablo Jofr , Universidad de Chile, Beaucheff 851, Santiago, 8370456, Chile, Marcelo Olivares, Andres I. Musalem

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