2016 INFORMS Annual Meeting Program

MD53

INFORMS Nashville – 2016

MD53 Music Row 1- Omni TIMES Distinguished Speaker Sponsored: Technology, Innovation Management

MD55 Music Row 3- Omni CPMS Isolated Practioner Sponsored: CPMS, The Practice Section Sponsored Session Chair: Jack Theurer, G Theurer Associates, Inc., 215 West 92nd Street, New York, NY, 10025, United States, theurer@aol.com 1 - Isolated Practitioner Workshop Jack Theurer, G Theurer Associates, Inc., 215 West 92nd Street, New York, NY, 10025, United States, theurer@aol.com Topics in this series address timely issues of interest to the isolated practitioner community of Analytics/OR/MS (“Lone Ranger” practicing the profession independently or within a large organization) while also having a universal appeal to a broader audience of practitioners from all walks of life in the profession. This is the 33rd in the series of workshops sponsored by the Practice Section of INFORMS since the first one at the 1992 fall meeting in San Francisco. MD56 Music Row 4- Omni IOT: Technology Innovation and Business Impact Sponsored: EBusiness Sponsored Session Chair: Zhe Shan, Assistant Professor, University of Cincinnati, 2925 Campus Green Dr, 317 Lindner Hall, Cincinnati, OH, 45221, United States, zhe.shan@uc.edu 1 - Internet Of Things Business Innovations And Opportunities Michael Chuang, State University of New York at New Paltz, New Paltz, NY, 1, United States, huangm@newpaltz.edu : Internet of Things (IoT), a global infrastructure enabling services by interconnecting physical and virtual things based on interoperable information and communication technologies, has emerged in business applications in various industrial areas. However, there is lack of holistic research that explores business opportunities enabled by IoT and related analytics. In this preliminary study, to build a needed foundation for IoT research, we review literature focusing on IoT- enabled business scenarios, and delineate related issues such as innovation for future research. . 2 - Network Analysis Of Supply Chain Adaptation For Disruption Recovery: An Empirically Grounded Complex Adaptive Systems Approach Kang Zhao, University of Iowa, kang-zhao@uiowa.edu This study investigates adaptive decisions and strategies in a real-world large-scale supply chain network in the face of a disruption in the network through the development and usage of an agent-based model. With real-world data, we show the supply chain network has structures similar to scale-free networks, and how the model of adaptive behaviors can leverage competition relationships within a supply chain network. We also illustrate how disruptions propagate in the supply chain network through cascading failures and develop metrics to predict such propagation. Finally, we test strategies an individual firm can trigger to reduce the negative effects of a supply chain network disruption. 3 - A Spatial Adaptive Sampling Procedure For Monitoring High-dimensional Data Streams Xiaochen Xian, University of Wisconsin, 500 Lincoln Drive, Madison, WI, 53706, United States, xxian@wisc.edu High dimensional (HD) data streams frequently appear in modern engineering applications and provide challenges for process monitoring. A spatial adaptive sampling and monitoring (SASAM) procedure is proposed under the limited resource constraint for detecting clustered out-of-control variables. Numerical studies show that the proposed method significantly outperforms the adaptive sampling strategy taking no consideration of the variables’ spatial distribution. 3 - Consumer's Preferences Modeling For Rail Transportation In Qatar Rana Sobh, Qatar University, Doha, Qatar; r.sobh@qu.edu.qa, Belaid Aouni The increase in traffic congestion, road safety and pollution have led Qatar to improve the existing public transportation system and introduce Doha Metro. This shift in public transportation requires changes in consumers’ perceptions about rail transportation. The aim of our paper is to predict the factors that may impact consumers’ behavior and their preferences in choosing transportation sys- tems. Moreover, our study aims to develop a better understanding of the rail transportation mode adoption in Qatar and provides some recommendations to the policy makers in Qatar Rail.

& Entrepreneurship Sponsored Session Chair: Sinan Erzurumlu, Babson College, 231 Forest St, Babson Park, MA, 02457, United States, serzurumlu@babson.edu 1 - Processes In Entrepreneurship Moren Levesque, York University, mlevesque@schulich.yorku.ca Phenomena in the scholarly field of entrepreneurship must often be studied as processes that involve assumptions of dynamism, nonlinearity, complexity, ambiguity, with multi-theoretical and multi-level analyses. While acknowledging these properties in the conceptual, formal or empirical framing of my research, I go over some findings from investigating the business investment process and entrepreneurial market process. I also offer some thoughts on research opportunities to further our understanding of such processes and their practical implications. I conclude with real-life examples where the knowledge of these practical implications has resulted in entrepreneurial achievements. MD54 Music Row 2- Omni Service Optimization, Design and Measure in Emerging Market Sponsored: Service Science Sponsored Session Chair: Yihong Hu, Tongji University, 1239, Siping Road, Shanghai, 200092, China, yhhu@tongji.edu.cn 1 - Benefiting From Seasonal Overloading Problem Of Delivery Service: A Strategic Analysis Of Dual Channel Business Xiang Ji, School of Management, University of Science and Technology of China, Hefei, China, xxj150630@utdallas.edu, Jie Wu, Jiasen Sun The tension between limited delivery service capacity and concentrated enormous orders in online hot selling seasons is one of the most serious problems that troubles nowadays e-commerce. To tackle this issue, we present a strategic analysis for the retailer who is involved in both online sales channel and bricks- and-mortar retail channel. A series optimal decisions on pricing, inventory and service level in different scenarios of consumer segments are derived. We also propose several contractual methods for the retailer to coordinate with its upstream manufacturer and its delivery supplier. 2 - Risk Measure Of Automobile Supply Chain Based On Conditional Value At Risk Approximation To Value At Risk Constrained Program Shiting Zhang, Tongji University, Shanghai, China, 1531159@tongji.edu.cn, Jiantong Zhang, Xiaodong Chen VaR and CVaR are time-honored risk measures in the field of finance. We apply them to construct a three-hierarchical quantitative risk measure model for automobile supply chain. VaR does not necessarily preserve the convexity and thus leads to difficulties of accurate computation. We first construct a tight binding with the CVaR approximation, which is known as the best CCA of VaR, then remedy the gap between VaR and CVaR by deriving the formulation of Hong et al., and finally obtain the accurate solution of VaR. We select fifteen public automobile companies, input their stock prices into the model, and finally explain its feasibility and practicality for risk assessment and risk orientation hunting. 3 - Path-Based Model And Algorithm For Emergency Evacuation Natural disasters such as earthquake or tsunami can easily take the lives of thou- sands of people and millions worth of property in a fleeting moment. A success- ful emergency evacuation plan is critical in response to disasters. In this paper, we seek to investigate the multi-source, multi-destination evacuation problem. First, we build a mixed integer linear programming model. Second, based on K shortest paths and User Equilibrium, we propose a novel algorithm (hereafter KPUE), whose complexity is polynomial in the numbers of nodes and evacuees. We prove that the algorithm is exact when there is only one source node. Finally, we demonstrate the effectiveness of Algorithm KPUE by a real evacua- tion network in Shanghai, China. The numerical examples show that the average computation time of the proposed algorithm is 93% less than that of IBM ILOG CPLEX solver and the optimality gap is no more than 5%. Tianhu Deng, Tsinghua University, Beijing, China, deng13@mail.tsinghua.edu.cn., Jianghua Zhang

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