Informs Annual Meeting Phoenix 2018

INFORMS Phoenix – 2018

MC51

4 - Big Data and Institutional Research with a Focus on Job Monitoring and Education Program Transformation Grace Lin, Asia University and Chinese Medical University, Asia University, Taichung, 110, Taiwan, Weiting Chen, K. H. Chen, M.D. Chen, Y. J. Chung, C. T. Lee, Brick Tsai, Y. L. Tsai, Jeffrey Tsai, Tingying Young, YiJianian Zheng The rapid changing business environment and technologies have led to a shortage of talents. Education Institutions often fail to adapt their education programs fast enough to meet the changing industry talent needs. The objective of this research is to develop a job monitoring and education model to understand up-to-date talent and skill needs and to identify gaps between talent needs and the education programs to facilitate the intuitions’ course/program transformation and students’ personal development plans. In this talk, we will report our system design and analysis based on data from our university’s education system and Taiwan’s job market. We will also discuss current gaps and our recommendations 5 - A New Model for Supply Chain Finance It’s been extremely challenging for SMB to get financial support due to the lack of credit rating information and mechanism. In this research, we propose to leverage Supply Chain network information as well as advanced NLP, multi-source learning and stochastic network modeling, analysis and optimization to better asses SMB’s crediting rating and risks and to provide financial services either through loan, P2P or crowd sourcing as needed. In this talk, we will present the analysis framework and discuss some preliminary analysis using realistic data. n MC50 North Bldg 231A Behavioral Aspects Through the Lens of System Perspectives Emerging Topic: Behavioral Aspects of OR Emerging Topic Session Chair: Martin Kunc, University of Warwick, Coventry, CV4 7AL, United Kingdom 1 - How Big Data Can Contribute to System Dynamics Modeling Hamed Kianmehr, State University of New York at Binghamton, Binghamton, NY, 13905, United States, Nasim S. Sabounchi, Lina Begdache Our objective in this research is to use big data techniques to enhance system dynamics (SD) modeling regarding the relationship between diet and mood. We apply our approach to study the relationship between diet and mood. We estimate the parameters of the system dynamics model by applying some big data techniques on a large data set. Then, we feed the calibration parameters in SD models with the new estimations using big data analytics. Mixing these two different techniques based on longitudinal data provides more insights to develop more accuracy in SD models. Big data techniques and SD models can contribute to bringing more evidence to investigate the causal relationships between nutrition and mood. 2 - Supply Management and Supply Risk Burcu Tan, Assistant Professor, University of New Mexico, Albuquerque, NM, 87106, United States, Gokce Esenduran, John Gray In this paper, we examine whether, when, and how common supply chain risk management practices relate to realized supply risk. We employ system dynamics modeling with realistic parameters to illustrate situations where certain practices can inadvertently increase supply risk. 3 - Behaviour Based Pricing in Sharing Economy Mojtaba Araghi, Lazaridis School of Business and Economics, Wilfrid Laurier University, 75 University Ave W, Waterloo, ON, N2L 3C5, Canada, Tina Arabian, Hamid Noori In sharing economy and servicizing business models, where firms sell the functionality of a product rather than the product itself, customers have less incentives to consider the long term economical and environmental impacts of their usage behaviours. Implementing new technologies, such as Internet of Things (IOT), firms now can track how well customers are using the shared product. This study introduces a behavior-based pricing that consider the behaviour of customers in addition to their amount of usage. We determine conditions under which adopting behaviour based pricing is more profitable and environmentally superior to the traditional pricing models. Grace Lin, Asia University and Chinese Medical University, Asia University, Taipei, 110, Taiwan, K. H. Chen, Brick Tsai

n MC51 North Bldg 231B

Production Planning and Scheduling in Operations Emerging Topic: Project Management and Scheduling, in Memory of Joe Leung, Emerging Topic Session Chair: Chelliah Sriskandarajah, Texas A&M University, College Station, TX, 77843-4217, United States Co-Chair: Yunxia Zhu, University of Nebraska-Lincoln, Lincoln, NE, United States 1 - Optimal Stocking for Substitutable Products Vashkar Ghosh, University of Florida, P.O. Box 117169 356 Stuzin, Dis Dept Warrington College of Bus, Gainesville, FL, 32611-7169, United States, Anand Paul We study the optimal stocking of product variants of a retailer facing random product demand. Each customer who arrives has a preferred first-choice product variant, but will exercise a second-choice in the event that the first-choice variant is not available. We find the structural form of the optimal stocking quantities in a single period as well as over an infinite horizon, and show that it differs systematically from the ‘naive’ news-vendor solution. 2 - Optimal Structure of Joint Inventory-Pricing Management with Dual Suppliers Houmin Yan, City University of Hong Kong, Dept of Management Sciences, Kowloon Tang, Hong Kong Abstract not available. 3 - Three-machine Open Shop with a Bottleneck Machine Revisited Inna Drobouchevitch, Korea University Business School, Seoul, Korea, Republic of We consider the three-machine open shop scheduling problem to minimize the makespan. In the model, each job consists of two operations, one of which is to be processed on the bottleneck machine, the same for all jobs. A new linear-time algorithm to find an optimal non-preemptive schedule is developed. The suggested algorithm considerably simplifies the only previously known method as it straightforwardly exploits the structure of the problem and its key components to yield an optimal solution. 4 - Cross-dock Terminal Scheduling We study various scheduling problems encountered in cross-dock terminals. The typical objective is to minimize the total time spent to perform unloading and loading for a planning horizon. We also study other objective functions under various cross-dock terminal environments (e.g., with no-wait processing and with the presence of temporary storage). 5 - An Optimization Framework for Influencers in Social Media Rakesh Reddy Mallipeddi, Texas A&M University, 320 Wehner - 4217, Mays Business School, Dept of Info&Operations, College Station, TX, 77843-4217, United States, Subodha Kumar, Chelliah Sriskandarajah, Yunxia Zhu Influencer marketing, which involves hiring influential users of social media, is being increasingly employed by firms to market their products. In this study, we propose a data-driven analytical framework to answer the following questions from the perspective of a firm: (i) how many influencers to hire, (ii) whom to hire, (iii) how to schedule and sequence the content by multiple influencers. A pilot study conducted using data collected from Twitter demonstrates that our framework consistently outperforms the current industry practice of selecting influencers based on the reach of influencers by 10%-90%. Yunxia Zhu, University of Nebraska-Lincoln, Lincoln, NE, United States, Harry Neil Geismar, Chelliah Sriskandarajah, Inna Drobouchevitch

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