Informs Annual Meeting 2017

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INFORMS Houston – 2017

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4 - How Newsvendors Reduce Cognitive Efforts Ehsan Elahi, Associate Professor, University of Massachusetts, Boston, 100 Morrissey Blvd, Boston, MA, 02125, United States, ehsan.elahi@umb.edu, Mahdi Malek, Babak Rezaee We introduce Order Clustering Preference and address supply chain coordination contracts. The effect of framing, free-item, feed-back and individual features (education and nationality) have been examined. Considering clustering tick-sizes and test results, this behavioral bias remains strongly stable. Our concluding remarks address cognitive driver and future studies. 5 - Supply Chain Decision Making under Financial Constraints Julie Niederhoff, Assistant Professor, Syracuse University, 721 University Avenue, Syracuse, NY, 13244, United States, jniederh@syr.edu, Panos Kouvelis, Wenhui Zhao, Ying Rong Capital availability creates constraints for decision makers. We consider the role of these constraints on the ordering behavior of decision makers in a behavioral study. 361C Transportation Modeling with Social Media Data and GIS Sponsored: TSL, Urban Transportation Sponsored Session Chair: Samiul Hasan, University of Central Florida, Orlando, FL, 32816, United States, samiul.hasan@gmail.com 1 - Activity Patterns Exploration and Location Recommendation Ying Chen, Northwestern University, 600 Foster St, Evanston, IL, 60208, United States, y-chen@northwestern.edu Location-based Social Networks (LBSN) allow users to check where their friends are and where their friends visited, to search location-tagged content, like notes and photos within their social connections, and to meet others nearby. Using data from two online LBSNs, the aim of this paper is to investigate the relationship between friendship and distance, the possible influence of friendship in travelers’ destination choices, and the importance of this factor in choosing a destination. 2 - Joint Inference of User Communities and Interest Patterns in Social Interaction Networks Arif Mohaimin Sadri, Valparaiso University, 149 Arnold Drive, Apt 12, West Lafayette, IN, 47906, United States, sadri.buet@gmail.com We present a modeling approach for characterizing social interaction networks by inferring user communities and interests based on social media interactions. We present several pattern inference models: i) Interest pattern model (IPM) captures population level interaction topics, ii) User interest pattern model (UIPM) captures user specific interaction topics, and iii) Community interest pattern model (CIPM) captures both community structures and user interests. We test our methods on Twitter data from Purdue University community and observed the interaction topics and communities related to two big events ,Purdue Day of Giving and Senator Bernie Sanders’ visit to Purdue University. 3 - Inferring Tourist Travel Behavior from Location based Social Media Data Md. Mehedi Hasnat, University of Central Florida, Orlando, FL, United States, hasnat@Knights.ucf.edu Location based information sharing platforms of social media have made it possible to extract individual activity records in time and space. Growing increase in the use of Twitter have opened a cost-effective and significant data source to track tourists’ travel activity. This research proposes a methodology to use geo- tagged tweets in order to infer travel behavior of tourists within Central Florida region of Florida, USA. Two major challenges addressed in this work include identifying tourists from local residents and extracting their most popular destinations in the study region. 4 - Quantifying the Quality of Mobility: Development of a Comprehensive Accessibility Metric Ambarish Nag, National Renewable Energy Lab (NREL), Golden, CO, United States, Ambarish.Nag@nrel.gov, Josh Sperling, Stan Young, Venu Garikapati The concept of mobility is difficult to quantify as it is only relevant in relation to the endpoints to be connected. The recent Department of Energy Vehicle Technology program area for Energy Efficient Mobility Systems uses the mantra ‘Maximizing Mobility while Minimizing Energy’. Whereas energy is objectively measured, mobility is more difficult to quantify, much less maximize. Traditional transportation engineering which focuses primarily on the National Highway System and associated urban roadways primarily characterizes the efficiency of roadways to carry the designed capacity. Measures like travel time and reliability reflect the relative health of a link on the roadway or set of links. WC50

361E Environmental Operations Contributed Session Chair: Sining Song, Arizona State University, Tempe, AZ, 8, United States, sining.song@asu.edu 1 - The Different Roles of Self-inspections and External Inspections in the Pipeline Industry Sehwon Kang, University of Minnesota, 321 Nineteenth Avenue South, Suite 3-150, Minneapolis, MN, 55455, United States, kangx584@umn.edu Operators and government agencies in pipeline industry have striven to reduce incidents through inspections: self-inspections by operators and external inspections by government agencies. Using econometric analysis with data sets from more than 800 pipeline operators, this study examines the differing role of self-inspections and external inspections on future incidents. 2 - Strategic Environmental Quality Investment in a Multi-tier Supply Chain Ozgen Karaer, Middle East Technical University, Endustri Muhendisligi Bolumu, Inonu Bulvari ODTU, Ankara, 06800, Turkey, okaraer@metu.edu.tr, Pinar Yalcin, Tim Kraft We study a buyer’s strategies to incentivize environmental quality investment in a three-tier supply chain. Environmental quality of the end product depends on the environmental performances of both the tier 1 and the tier 2 supplier. A higher environmental quality produces an increased demand for the end product; and hence for the whole supply chain. In this setting, we compare the effectiveness of delegation vs. full control strategies from the buyer’s cost-sharing perspective. 3 - The Future of Indian Aviation Network in the Wake of a Prospective Carbon Tax Regime Himanshu Rathore, Indian Institute of Management, Rohtak, India will be the third largest aviation market in the world by 2020 and has witnessed the world’s highest growth rate of 20.3% in 2015-16. The emissions from aviation have been growing exponentially and would double up in the next decade if no actions are taken. EU-ETS has also been pushing for carbon tax on aviation. India is opposing the proposed carbon tax on apprehensions that its growth rate would be inhibited. We test this apprehension by building a mixed possibilistic low carbon integrated hub location model which takes into account the landing and take-off cycle of the aircraft by using M/G/s queuing model. The results deliberate on the impact of prospective carbon tax on aviation network strategy. 4 - Greenhouse Gas Emissions and Supply Chain Spillovers Sining Song, Arizona State University, Tempe, AZ, United States, sining.song@asu.edu, Yan Dong, Thomas Kull, Craig Carter, Kefeng Xu Using public secondary data, we empirically investigate the relationship between emissions reduction programs of a firm and the GHG emissions of the firm’s supply chain. Our results suggest a supply chain spillover effect of a firm’ emissions reduction. 361F Statistical Methods in Traffic Simulation and Estimation Sponsored Session Chair: Yudi Yang, UC Davis, 1420 Lake Boulevard, Apartment 17, Davis, CA, 95616, United States, ydyang@ucdavis.edu 1 - Improvement of Estimation Method of the Nested Logit Model Siyu Tao, Southwest Jiaotong University, Cheng Du, China, siyu.tao@okstate.edu, Lisha Wang, Qiyuan Peng, Kuniaki Sasaki Because of the drawbacks of conventional method, nowadays researchers prefer to use discrete model to forecast traffic demand. And nested logit model is widely used on the simulation of discrete model.However, when we use R language to estimate, we have to do step by step. If the logsum terms or t-test values aren’t valid, we must establish another structure to estimate again, which makes estimation become burdened. Because if there are n dimensions, then the number of possible structures is n!. This thesis focus on realizing this work automatically by using R language and bootstrap. MDU. Rohtak, 124001, Rohtak, 124001, India, himanshu.rathore13@gmail.com, Shirsendu Nandi WC53

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