2015 Informs Annual Meeting

WB06

INFORMS Philadelphia – 2015

WB04 04-Room 304, Marriott Economics III Contributed Session Chair: Wei Ye, Tongji University, Shanghai,China, Siping Rd 1239, Shanghai,China, Shanghai, China, yw0129@126.com 1 - Contractual Adaptation through Voluntary Renegotiation Jiulin Teng, HEC Paris, 1 rue de la Liberation, Department of Strategy, Jouy-en-Josas, 78351, France, jiulin.teng@hec.edu I study the efficiency benefits of contractual adaptation. With a game theoretic model that delves into the microfoundation of bilateral interaction in a non- stochastic, non-deterministic environment, I find the dynamic contract that is ‘temporarily’ renegotiation-proof benefits from inter-temporal, Pareto-improving updates – I refer to them as ‘voluntary renegotiation’. Their efficiency advantage over static contracting alternatives arises from the balance between flexibility and precision. 2 - Evaluation of City-Production Integration Based on DEA Model and Coupling Method The level of city-production integration is essential for urban development; however the current research mainly focuses on the definition of the concept. In this paper, we took typical cities in China as cases by using the combination of Dea Model And Coupling Method to quantitatively evaluate and classify the level of city-production fusion, and finally proposed policy recommendations. 3 - The Impact of Corporate Welfare Policy on Firm’s Productivity: Evidence from Unemployment Insurance Heedong Kim, PhD Student, Robert H. Smith School of Business, University of Maryland, 6100 Westchester Park Drive, Apt. 1007, College Park, MD, 20740, United States of America, hekim@rhsmith.umd.edu, Emanuel Zur, Masako Darrough We examine the relation between the state-run unemployment insurance benefits (UIBs) and firm productivity. We test two competing theories and find that our results support the efficiency wage rather than the compensating wage differential theory. We find that an increase in UIBs is likely to exacerbate moral hazard and leads to a decrease in firm productivity. We also find that firms tend to enhance their employee welfare policies as a complementary mechanism to manage moral hazard problems. 4 - How the Family Life Cycle Affects Rural Labor Migration: Evidence from China Wei Ye, Tongji University, Shanghai,China, Siping Rd 1239, Shanghai,China, Shanghai, China, yw0129@126.com This paper studies how the family life cycle affects rural labor migration in China. We constructed an unique 5-stage family life cycle model and used a logistic regression model to examine the effect. The original data is from a valid questionnaire of 2107. Empirical results showed that the family life cycle has significant impact on rural labor migration. Different stage has different impact on migration. As the family becomes older, the possibility of migration shows a “S- curve” fluctuation. WB05 05-Room 305, Marriott Better Business using Social Media Analytics Cluster: Social Media Analytics Invited Session Chair: Chris Smith, TRAC-MTRY, 28 Lupin Lane, Carmel Valley, CA, 93924, United States of America, cmsmith1@nps.edu 1 - Predicting Digital Currency Price from Social and Traditional Media Peng Xie, Georgia Institute of Technology, Room 907, 100 10th Street, Atlanta, GA, 30309, United States of America, peng.xie@scheller.gatech.edu Using daily Bitcoin price data and Bitcoin Forum discussion, we try to understand if social media can affect Bitcoin price and how long does it take. We use the percentage of negative words as the measure of the article sentiment. The results show that social media can affect price. However, for information sources focusing on speculation, the effects on prices are immediate. In contrast, information concerning fundamentals impacts prices in a longer holding period. Jingjing Jia, Tongji University, School of Economic and Management, Siping Road No.1239, Shanghai, China, yjshsl@163.com, Lin Su, Yixi Xue

2 - What Products to Feature on Retail Website Landing Pages? Patrali Chatterjee, Professor, Montclair State University, 1 Normal Avenue, Montclair, NJ, 07043, United States of America, chatterjeep@mail.montclair.edu Landing pages on retailer websites are critical in inducing new shoppers to browse deeper and ultimately purchase. Using field-experiment data this research examines the relative effectiveness of using various real-time marketing analytics like social media likes/pins (unique vs. shared) with site-specific behavioral data (most purchased/most placed in cart/searched) on conversion. 3 - Decision Sciences Initiative in Analytics: The Nexus of Operations Efficiency and Big Data Decision Sciences Journal has a strong interest in the analysis and understanding of large-scale data. We offer a panel describing analytics research publication opportunities, and prospective authors will receive one-on-one mentorship with key editors in preparation for Journal submission. Topics of interest span social media, descriptive, predictive and prescriptive analytics. 4 - Situational Understanding: A Military Perspective of Where we Need to Go and the Exploitation of Open Source Data Utilizing “Social Signal Processing for Anomaly Determination” Michael A. Kolodny, Senior Technology Advisor, Army Research Laboratory, michael.a.kolodny.ctr@mail.mil We are drowning in the deluge of data that is being collected world-wide, while at the same time starving for knowledge and understanding. In the military domain, there is a need to autonomously access & synthesize all relevant available data & information into situational understanding for the Warfighters to rapidly & effectively make critical decisions. A key aspect of this process is to provide only information that is relevant and useful for the needed mission decision at hand. Innovative research is needed to achieve the necessary situational understanding required by military decision makers especially at the tactical edge. This presentation will discuss the following topics: • The different levels of understanding from physical representation to the levels of comprehension (insight) and prediction (foresight). • The types of data processing and analytics needed to understand group behaviors and their mutability and resiliency. • A military perspective on data-to-decision to provide Situational Understanding at the tactical edge. • The exploitation of open-source data such as social media for the determination of anomalous group behaviors • The ARL’s initiatives to enable collaborative research “Social Signal Processing for Anomaly Determination”. Chair: Kuno Huisman, Tilburg University, Post Office Box 90153, Tilburg, 5000LE, Netherlands, k.j.m.huisman@tilburguniversity.edu 1 - Entry Deterrence by Location under Stochastic Demand Kuno Huisman, Tilburg University, Post Office Box 90153, Tilburg, 5000LE, Netherlands, k.j.m.huisman@tilburguniversity.edu, Peter Kort Huisman and Kort (2015, RJE) showed that by overinvesting an incumbent ÷rm can delay entry by a competitor. This paper analyzes how location can play a role in entry deterrence strategies. Location can be geographical, but can also relate to product positioning 2 - Assessing Pollution Abatement Investment Policy under Ambiguity Motoh Tsujimura, Associate Professor, Doshisha University, Kamigyo-ku, Kyoto, 602-8580, Japan, mtsujimu@mail.doshisha.ac.jp This paper investigates a pollution abatement investment policy under ambiguity. We consider there are representative consumer and firm in an economy and formulate the social welfare maximization problem. Then we derive the optimal abatement investment timing. Furthermore, we analyze the comparative static effects of the model’s parameters. 3 - Product Innovation under Declining Demand and Uncertainty Tom Stafford, Editor, Decision Sciences Journal, Fogelman College of Business, University of Memphis, Memphis, TN, 38152, United States of America, descieditor@gmail.com, Ramesh Sharda WB06 06-Room 306, Marriott Real Options Sponsor: Financial Services Sponsored Session

Verena Hagspiel, Norwegian University of Science and Technology, Alfred Getz vei 3, Trondheim, Norway, verena.hagspiel@iot.ntnu.no, Peter Kort, Claudia Nunes

This paper studies a firm’s optimal product innovation decision facing volatile and deteriorating product demand. The firm has to decide about the optimal time to adopt new technology required to successfully launch a new product generation and therewith boost demand. The innovation process is considered stochastic with uncertainty about the speed of the arrival. Besides timing we also study the optimal capacity choice for the new product.

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