2015 Informs Annual Meeting

TD14

INFORMS Philadelphia – 2015

TD12 12-Franklin 2, Marriott

3 - Dynamic Delegated Search Morvarid Rahmani, Assistant Professor, Georgia Tech, Atlanta, GA, morvarid.rahmani@scheller.gatech.edu, Karthik Ramachandran

MAS Tutorial: The State of Operations Research in the US Military: A 75th Anniversary Perspective Sponsor: Military Applications Sponsored Session Chair: Greg Parlier, Past President, MAS of INFORMS, 255 Avian Lane, Madison, AL, 35758, United States of America, gparlier@knology.net 1 - The State of Operations Research in the U.S. Military: A 75th Anniversary Perspective Greg Parlier, Past President, MAS of INFORMS, 255 Avian Lane, Madison, AL, 35758, United States of America, gparlier@knology.net This extended presentation offers perspectives on the past, present, and future of Operations Research in the US Department of Defense with emphasis on the Army. The need for a critical review is argued, and a framework for a comprehensive assessment is developed. Enduring principles are suggested and new concepts are presented, including both strategic and transformational analytics. TD14 14-Franklin 4, Marriott Engineering Systems Applications Sponsor: Optimization/Optimization Under Uncertainty Sponsored Session Chair: Honggang Wang, Assistant Professor, Rutgers University, 96 Frelinghuysen Rd, 201 CoRE, Piscataway, NJ, 08854, United States of America, honggang.w@rutgers.edu 1 - Optimization of Maintenance Planning for Water Distribution Network under Stochastic Failures Xin Chen, Assistant Professor, Southern Illinois University, P.O. Box 1805, Edwardsville, IL, 62034, United States of America, xchen@siue.edu, Honggang Wang Cost-effective and preventive maintenance for water distribution networks (WDN) is essential for sustainable and reliable use of water resources. We develop mathematical models and apply optimization procedures for optimal WDN maintenance planning under stochastic failures. We demonstrate the mathematical models and optimization approach using a regional WDN in a large U.S. city. We apply genetics algorithms to solve the optimization problem and find the optimum maintenance plan for the WDN. 2 - Optimal Development of Shale Gas Field Optimal development of shale gas involves determining the most-productive fracturing network via hydraulic stimulation processes in shale reservoirs. Shale gas development problems can be formulated with mixed-integer optimization models. We apply a simplex interpolation based optimization method to solve mixed integer optimization problems associated with shale gas production projects. The optimization performance is demonstrated with the example case of developing the Barnett shale field. 3 - Resource Abstraction in Planning and Design of Virtual Data Centers Dimitri Papadimitriou, Copernicuslaan 50, 2018, Antwerp, 2018, Belgium, dimitri.papadimitriou@alcatel-lucent.com Virtual data centers enable flexible allocation of capacity to customer demands by aggregating physical resources taken out of a subset of data centers (facilities) to satisfy customer demands. The goal is to determine the capacity to be provisioned on opened facilities and the assignment that minimize the cost of opening, supplying demands and connecting each customer to a subset of facilities. We compare the resulting cost against the corresponding capacitated facility location problem. Honggang Wang, Assistant Professor, Rutgers University, 96 Frelinghuysen Rd, 201 CoRE, Piscataway, NJ, 08854, United States of America, honggang.w@rutgers.edu

Firms often delegate the search for solution of their innovative problems to third parties (e.g., search for designs, advertisements, executive leaders, etc.) In this paper we study how the client’s choice of search process (i.e., defined or open- ended) depends on the strategic behavior of the provider. Taking the client’s and provider’s perspective, we identify conditions for which a defined search is preferred to an open-ended search. 4 - The Impact of Health Information Technology Bundles on Hospital Performance: An Econometric Study Aravind Chandrasekaran, Associate Professer, The Ohio State University, 2100 Neil Avenue, Columbus, OH, 43210, United States of America, chandrasekaran.24@osu.edu, Luv Sharma We examine how two HIT bundles: Clinical (used for patient data collection, diagnosis and treatment) and Augmented Clinical (used for integrating patient information and decision making) jointly impact operating cost and process quality. Results suggest complementarities between these bundles with respect to process quality but not cost. A posthoc analyses offers additional explanation on the lack of association with cost. Sponsor: E-Business Sponsored Session Chair: Jason Chan, Assistant Professor, University of Minnesota, 321 19th Ave S, Minneapolis, MN, United States of America, jchancf@umn.edu 1 - Dynamic Strategies for Successful Online Crowdfunding Zhuoxin (Allen) Li, Assistant Professor, Boston College, 140 Commonwealth Avenue, Chestnut Hill, MA, 02467, United States of America, zhuoxin.li@gmail.com, Jason A. Duan This paper empirically investigates the dynamics of investors’ backing behaviors in the presence of network externalities and a finite time window. Model estimation shows that investors are more likely to back a project that has already attracted a critical mass of funding. For the same amount of achieved funding, the backing propensity declines over time. 2 - The Effect of Disclosing Purchase Information on Review Helpfulness: Evidence from Amazon.com Marios Kokkodis, Assistant Professor, Boston College, 34 E 10th, New York, NY, 10009, United States of America, mkokkodi@stern.nyu.edu In this work, we study how the introduction of the Verified Purchase (VP) feature affected review helpfulness on the Amazon platform. We find that all else equal, `search’ product VP reviews are on average 3.6% more helpful than nonVP reviews, and `experience’ product VP reviews are 5.6% more helpful than non- VP reviews. 3 - The Business Value of Recommendations: A Privacy-preserving Econometric Analysis Panagiotis Adamopoulos, Doctoral Candidate, New York University, 44 W 4th St, New York, NY, United States of America, padamopo@stern.nyu.edu, Alexander Tuzhilin We study the effectiveness of different types of mobile recommendations and their impact on economic demand, using a privacy-preserving econometric analysis. Our observational data set is based on a real-world mobile recommender system, which we further supplement with climate, geospatial, and population and household data. Based on our findings, an increase by 10% in the number of times a venue is recommended raises the demand by about 6.7%. 4 - Effect of Valuation Uncertainty on Buyer Indecision and Bidder Regret in Online Labor Markets TD10 10-Room 310, Marriott Platform-Based Markets in the Digital Era

Kevin Hong, Assistant Professor, Arizona State University, 400 E Lemon St, Tempe, AZ, United States of America, hong@asu.edu, Paul Pavlou, Alvin Zheng

In online labor markets, 60% of projects fail to reach to a contract, and significant bidder remorse is observed, indicating a waste of time and effort for both buyers and freelancers.This paper empirically examines how valuation uncertainty - measured as bids price dispersion - affects buyer’s contract indecision and bidders’ regret after the buyer awards a contract. We find bids valuation uncertainty increases both buyer’s contract indecision and bidders’ regret.

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