Informs Annual Meeting 2017

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INFORMS Houston – 2017

2 - Pull and Push Contracts in a Decentralized Assembly System with Random Component Yields Yanling Feng, Beihang University, Haidian District, Xueyuan Road No. 37, Beijing, 100191, China, fengyanling.1@163.com This paper investigates how random component yields could influence the pricing and production decisions. Both suppliers’ yields are assumed to be random and all information is symmetric. The equilibrium solutions are studied under pull and push contracts. Compared results show that under the push contract the suppliers always achieve the first mover advantage, but this may not be true for the manufacturer under the pull contract. Sensitivity analysis are also performed to study the impact of random yields and the retail price on the equilibrium solutions. We then extend our analysis to a more general case of n suppliers. 3 - Assortment Optimization Considering Consumers Heterogeneity We propose an assortment optimization model in which customer heterogeneity is considered. We used id-pos data to estimate parameters of a demand model, considering brand loyalty of each customer heterogeneity. We build an optimization model to maximize total revenue. 4 - Determine the Customer Compensation for an Overbooked Flight Lijian Chen, Assistant Professor, University of Dayton, 300 College Park Ave, Dayton, OH, 45469-0001, United States, lchen1@udayton.edu We study the monetary impact of denying customers to board an overbooked flight. Overbooking has been a common practice of major airlines for decades to minimize the spoilage, i.e., the empty seats caused by no-shows. The airlines demand a quantitative measure to determine the monetary impact and we model the seat allocation problem with overbooking as a chance-constrained optimization. We compare our model with the seat allocation models without overbooking to gain insights regarding the benefit of overbooking and the related cost of denying economy customers. In addition to our analysis, we also present numerical results to support our conclusions. Shunichi Ohmori, Assistant Professor, Waseda University, Room 0903A, Okubo 3-4-1, Shinjuku, Tokyo, Japan, ohmori0406@gmail.com, Kazuho K. Yoshimoto 351B Supply Chain, Shipping and Transportation Contributed Session Chair: Yuhong Li, Virginia Tech, Blacksburg, VA, United States, yuhongli@vt.edu 1 - Host National Strategy Impact on Supply Chains: Consequences of Gaining Legitimacy via Supplier Development Remi Charpin, PhD Candidate, Clemson University, 250 Elm Street, Apt 501, Clemson, SC, 29631, United States, rcharpi@clemson.edu, Erin Powell, Aleda Roth The recent protectionist and nationalist waves coupled with the renaissance of industrial policies have pushed foreign firms to reconsider the role played by host governments.This study intends to understand how host policies impact foreign firms’ operations strategy. We use a grounded theory approach to explore how foreign managers’ sensemaking of the host national strategy towards foreign entities impact their decision-making. We extend the legitimacy-based view theory to the operations and supply chain fields and find that firms implement supplier development programs to increase their legitimacy in the host country at the risk of enabling their own competition. 2 - Performance Assessment of Traditional Inventory Policies as Resilience Strategy. Weimar Ardila, University of South Florida, Tampa, FL, United States, weimar@mail.usf.edu, Alex Savachkin, Daniel Romero One of the resilience improvement strategies widely referenced in the literature is inventory redundancy, which basically consists of maintaining high levels of inventory to respond adequately to failures presented in the operation. The main problem with these types of strategies is the difficulty of its implementation, since it is an alternative that against the reduction of costs and efficiency. Therefore, this work aims to evaluate the performance of different traditional inventory policies, and to determine which one offers the best balance between resilience and efficiency. 3 - The Impact of Supply Chain Risk Announcements on Stock Market Performance Laharish Guntuka, Robert H. Smith School of Business, University of Maryland, 4335 Rowalt Drive, # 301, College Park, MD, 20740, United States, lguntuka@rhsmith.umd.edu, Xiaodan Pan, Thomas M. Corsi, Curt Grimm We explore the effects of supply chain risks with major emphasis on plant- and labor-related risks on the stock market reaction. Focusing on main upstream manufacturing industries, we collected data on day-to-day basis for a period of 1 year (2015) by using “early monitoring system” created by Lexis Nexis which TD32

collects and scores risk announcements. We find the stock market reaction is notably negative in the face of plant- and labor-related risks. 4 - Cash Hedging in a Supply Chain Yixuan Xiao, City University of Hong Kong, 83 Tat Chee Avenue, Kowloon, Hong Kong, yixuxiao@cityu.edu.hk, Panos Kouvelis, Xiaole Wu We study hedging cash flow risks in a bilateral supply chain. Hedging reduces expected cost for firms due to the convexity of production cost in capital investment, while not hedging provides the flexibility for firms to adjust their operational decisions in response to different cash flow realizations. We quantify the tradeoff between the cost reduction effect and the flexibility effect of hedging, and characterize the firms’ hedging decisions in the supply chain. 5 - Network Characteristics and Supply Chain Disruption Resilience Yuhong Li, Virginia Tech, 301 Piedmont Street, Apt 8, Blacksburg, VA, 24060, United States, yuhongli@vt.edu, Christopher Zobel, Onur Seref Inspired by the growing needs to understand supply chain network structure and its impact on supply chain resilience, this study focuses on investigating the relationships between network characteristics and supply chain resilience. Specifically, we select the key influential characteristics and study how they influence network resilience. Then we conduct a case study to show how practitioners can use these characteristics to gain a knowledge of supply chain resilience and support decision making. 351C Empirical Research on Air Transportation Sponsored: Aviation Applications Sponsored Session Chair: Milind Sohoni, Indian School of Business, Hyderabad, 500032, India, milind_sohoni@isb.edu 1 - An Analytical Approach to Predicting Airline Planned Maintenance Inspections Shervin Beygi, Boeing, 441 Smith Avenue, Seattle, WA, 98109-2155, United States, shervin@umich.edu Airlines regularly perform major planned maintenance inspections on their fleet. Predicting such events is key for providers of spare parts and technical services to predict future demand. We present a data-driven model to determine airlines’ past maintenance logic and use it to predict future events. The model uses flight leg data to find gaps in the flight schedule of each airplane. A statistical model is used to determine if the detected gaps can be attributed to scheduled maintenance events, and then predicts when the next check will occur, for each tail number, up to three years before the actual event. Test cases illustrate that the proposed model can successfully predict major scheduled checks. 2 - Network Design and Fleet Management for Air Cargo Operations Timothy L. Jacobs, Amazon, 415 W. Larona Lane, Tempe, AZ, 85284, United States, tljacobs61@gmail.com, Hoda Parvin, David Michael Amazon’s Middle Mile Planning and Research Science (PROS) team is responsible for the design and implementation of optimization models and algorithms to design the air network and better utilize the Amazon air transportation assets. In 2017, PROS developed a network design and fleet assignment model to plan the air network for fall 2017 and beyond. The model uses a mixed integer programming approach that simultaneously builds the flight schedule, assigns fleets to flights, and determines how best to flow all air packages throughout the network. This model provides both tactical and strategic solutions taking into account available aircraft, station and hub capacity, the use of point to point and hub and spoke configurations, and other operational restrictions. Amazon uses the model to help select new stations, determine operating strategies at the hub, and to evaluate network topology. This talk will describe the major components of the model and our general solution approach. 3 - Analyzing How Individuals Filter and Screen Alternatives for Discrete Choice Modeling Applications Virginie Lurkin, Ecole Polytechnique Fédérale de Lausanne, Route Cantonale, Lausanne, 1015, Switzerland, vlurkin@ulg.ac.be, Laurie Garrow There has been little research into whether state of the art consumer welfare models accurately capture consumers’ decision-making process. Both the itinerary choice and welfare estimation literatures generate a “complete” set of itineraries and assume individuals look at and evaluate all itineraries in the choice set. This may not be a realistic assumption. We designed an online experiment to capture how individuals filter and screen alternatives for discrete choice modeling applications. We present preliminary results analyzing screening rules that have been used by respondents. TD33

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