2016 INFORMS Annual Meeting Program

MA66

INFORMS Nashville – 2016

4 - Economic Effects Of European Union’s External Aviation Policy Megersa Abate, Swedish National Road and Transport Research Institute, megersa.abate@vti.se

criteria decision problem, we apply the robust ordinal regression approach. We validate all the methodology on the classic newsvendor problem where we apply GRIP and ELECTRE^GKMS methods to recommend a solution respecting preferences of the decision maker.

MA63 Cumberland 5- Omni Continuous Space Location Modeling Sponsored: Location Analysis Sponsored Session Chair: John Gunnar Carlsson, University of Southern California, 3715 McClintock Ave, Los Angeles, CA, 90089, United States, spajcarlsso@usc.edu 1 - On The Dual And Rectangular Bounds For Continuous Facility Location Problem Nadere Mansouri, SMU, nmansouri@mail.smu.edu Halit Uster Lagrangian dual and Rectangular bounds (a rectangular distance location problem specifically devised) are two of the lower bounding techniques for a continuous facility location problem. We present results comparing these bounds at any Weiszfeld iteration and upon convergence. 2 - Delivering Packages Jointly With A Truck And A Drone John Gunnar Carlsson, University of Southern California, jcarlsso@usc.edu One of the most talked-about developments in transportation and logistics in recent years has been the potential use of drones for transporting packages. We use a continuous approximation analysis to study a hybrid system in which Lawrence V Snyder, Associate Professor, Lehigh University, 200 West Packer Ave., Mohler Lab, Bethlehem, PA, 18015, United States, lvs2@lehigh.edu, Ying Zhang, Ted K Ralphs Two players sequentially locate facilities, competing to capture market share. Facilities face disruption risks, and each customer seeks the nearest operational facility for service, regardless of who operates it. The problem combines competitive location and location with disruptions, an important combination that has been absent from the literature. We model the problem as a Stackelberg game, and formulate the leader’s decision problem as a binary bilevel optimization problem. We propose a branch-and-cut algorithm and a variable neighborhood decomposition search heuristic. Computational results suggest that high quality solutions can be found quickly. MCDA Methods and Applications Sponsored: Multiple Criteria Decision Making Sponsored Session Chair: Roman Slowinski, Poznan University of Technology, Poland, roman.slowinski@cs.put.poznan.pl 1 - Context Matters: Effects Of Product Type And Information Overload On Choice Accuracy Jyrki Wallenius, Professor, Aalto University School of Business, Helsinki, Finland, jyrki.wallenius@aalto.fi Pekka J Korhonen, Pekka Malo, Tommi Juhani Pajala, Niklas Ravaja, Outi Somervuori We report on the results of an experiment, which utilizes a new method for generating many similar choice problems, enabling the objective measurement of choice accuracy.We show that the product type matters for choice accuracy. Moreover, we show that information overload is a relevant phenomenon in MCDM experiments. However, what matters is the quality of information, not just the quantity. When we add information that does not change the dominance relations between products, choice accuracy is not degraded. 2 - Decision Under Risk And Uncertainty As A Multi-quantile Decision Problem Roman Slowinski, Poznan University of Technology, Poznan, Poland, roman.slowinski@cs.put.poznan.pl Salvatore Corrente, Salvatorend,&nbGreco, Benedetto Matarazzo We formulate the problem of decision under risk & uncertainty as a multiple criteria decision problem, where criteria are some quantiles of the outcome distribution, which are meaningful for the decision maker. To solve the multiple MA64 Cumberland 6- Omni delivery trucks act as a mobile “base” for launching drones. 3 - The Competitive Facility Location Problem Under Disruption Risks

MA65 Mockingbird 1- Omni Gamification and User Engagement Sponsored: Information Systems Sponsored Session Chair: Lei Wang, Pennsylvania State University, University Park, PA, 16801, AssigUnited States, luw21@smeal.psu.edu 1 - Measuring The Impact Of Crowdsourcing On Mobile App User Engagement And Retention: A Randomized Field Experiment Zhuojun Gu, Pennsylvania State University, zqg5077@psu.edu Ravi Bapna, Jason Chan, AlokcustomGupta In this paper, we propose a new strategy for enhancing mobile app user engagement and retention by introducing crowdsourcing features that involve users through the design of the app itself. We measure the causal impact of crowdsourcing by conducting a randomized field experiment on a social mobile game platform. We find higher user retention level could be achieved by allowing users to submit content and customize their products. And sustained user engagement and retention are enhanced most when both submission and access options are available. 2 - Cultivate Consumer Engagement With Mobile And Gamification Lei Wang, Pennsylvania State University, State College, PA, 16802, United States, Lxluw21@smeal.psu.edu, Siyuan Liu Despite the growing popularity of gamification and its potentials on customer engagement, we still have very little knowledge about gamification and its impact on customer engagement. In this research, we conduct a large-scale randomized field experiment in a shopping mall in Asia to investigate the impact of gamification on cultivating customer engagement. Our results will allow us to effectively measure the causal impact of gamification and provide insights on quantifying and improving the impacts of gamification on customer engagement and mobile advertising. This study also provides important implications on how firms could benefit from gamification. 3 - What Do Mobile Applications Bring a Longer Tail? An Empirical Study Of Sales Concentration In Online Cchannels Shahryar Doosti, University of Washington, Foster School of Business, Mackenzie Hall, Seattle, WA, 98195, United States, shahryar@uw.edu, Yong Tan, Youwei Wang This work uses a dataset from a leading e-retailer which offers two online channels, the desktop channel and mobile applications, to study the effect of long tail on product sales in each channel. Our findings show that the long tail effect exists in mobile application channel. In other words, there is more product variation and less sales concentration on mobile app compared to desktop channel. MA66 Mockingbird 2- Omni Model Calibration Sponsored: Quality, Statistics and Reliability Sponsored Session Chair: Matthew Plumlee, University of Michigan, Ann Arbor, MI, United States, mplumlee@umich.edu 1 - Bayesian Calibration Of Inexact Computer Models Matthew Plumlee, University of Michigan, mplumlee@umich.edu Bayesian calibration is used to study computer models in the presence of both a calibration parameter and model bias. The parameter in the predominant methodology is left undefined. Among other problems, this results in an issue where the posterior of the parameter is sub-optimally broad. To date, there has been no generally accepted alternatives. This paper proposes using Bayesian calibration where the prior distribution on the bias is orthogonal to the gradient of the computer model. Problems associated with Bayesian calibration are shown to be mitigated through analytic results in addition to numerical and real examples.

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