2016 INFORMS Annual Meeting Program

SA66

INFORMS Nashville – 2016

SA64 Cumberland 6- Omni Spatial Multicriteria Decision Making: Challenges and Current Developments Sponsored: Multiple Criteria Decision Making Sponsored Session Chair: Valentina Ferretti, London School of Economics and Political Science, Houghton Street, London, WC2A 2AE, United Kingdom, V.Ferretti@lse.ac.uk 1 - Geographically Weighted Multi-attribute Decision Making For Taxi Assignment Ali Esmaeeli, University of California, Irvine, Irvine, CA, United States, esmaeeli@uci.edu, L Robin Keller Taxi assignment problem is usually considered as one part of the more general vehicle routing problem (VRP) with a known value function. In this work, we extend this viewpoint to match the problem more with the real world conditions. We consider a map with weighted regions and propose a method to find the best option for each taxi request based on two different attributes. These attributes are the average response time for each region and the rate of accepted requests for each region. We show how to combine these attributes and how to include the region weights into the main value function. Moreover, we present a method for finding the best assignment option based on our defined value function. 2 - Spatial Multi Criteria Decision Analysis In The Energy Sector: A Preliminary Application To Deep Geothermal Energy Systems Matteo Spada, Risk Analyst, Paul Scherrer Institut, OHSA/D19, Villigen PSI, 5232, Switzerland, matteo.spada@psi.ch Peter Burgherr This study presents the preliminary application of a spatial MCDA to the energy sector. In particular, Deep Geothermal Energy (DGE) systems are considered in the analysis. DGE is gaining quite some interest as new renewable energy system, since it offers the prospect of supplying base-load power in a decentralize fashion and a theoretically large resource potential. The proposed approach will combine spatial information from both explicit data (e.g., heat flow) and calculated ones (e.g., risk indicators, environmental impact indicators, etc.) for specific a priori defined capacity plants. The results will be presented for different hypothetical stakeholders for the case study of Switzerland. 3 - Case Studies With Gear, A New Tool For Geospatial Multi-Criteria Decision Analysis Matthew Bates, Research Engineer, US Army Corps of Engineers, Concord, MA, United States, matthew.e.bates@usace.army.mil Michelle Hamilton, Jeffrey Cegan, Cate Fox-Lent, John Nedza GEAR (the Geospatial Environment for Analysis and Reasoning) is a new, state- of-the-art geospatial multi-criteria decision analysis (GIS-MCDA) tool developed by the Engineer Research & Development Center of the US Army Corps of Engineers. GEAR has a friendly and intuitive user interface, accepts diverse web- service and file data inputs, and guides users through data exploration, criteria development, value function and weight specification, and running the analysis. It is designed for both practiced analysts and non-expert users. In this presentation, we introduce the GEAR functionality through a series of spatial decision case studies. 4 - Behavioural Issues In Spatial Decision-making Processes Valentina Ferretti, London School of Economics and Political Science, V.Ferretti@lse.ac.uk Behavioral decision research has demonstrated that judgments and decisions of ordinary people and experts are subject to numerous biases. While these biases have already been extensively discussed in several disciplines, e.g. economics, game theory, finance, and risk analysis, to name the most relevant, there is now a need to pay more attention to behavioral and cognitive effects in spatial environmental decision-making processes. Within this context, this talk explores which biases are relevant in the field and proposes a first behavioral experiment focusing on the weights elicitation step 5 - Landscape Multi-methodological Evaluations: Approaches For The paper, starting from the evolution of the landscape’s concept and related evaluative approaches, focuses on the management of its complexity in transformation processes included in the dynamic context of landscape’s values and in its local development strategies. A multi-methodological synergistic evaluations framework for a Collaborative Spatial Decision-Making Process has been tested in some case-studies for context-aware planning strategies and scenarios of local sustainable policies, combining Multi-Criteria Analysis (MCA), Multi-Group Analysis (MGA) and Geographic Information Systems (GIS). Collaborative Spatial Decision-making Processes Maria Cerreta, University of Naples,, cerreta@unina.it

SA65 Mockingbird 1- Omni Economics of Information Systems Sponsored: Information Systems Sponsored Session

Chair: Marius Florin Niculescu, Georgia Institute of Technology, Georgia Institute of Technology, Atlanta, GA, 30332, United States, marius.niculescu@scheller.gatech.edu 1 - E-commerce In The Manufacturing Supply Chain: An Empirical Analysis Patricia Angle, Georgia Institute of Technology, Patricia.Angle@scheller.gatech.edu, Christopher M Forman, Kristina Steffenson McElheran In this paper, we explore the value of e-commerce technologies on the total factor productivity (TFP) of manufacturing plants. We find that, on average, e-selling adoption is associated with a 1.4% increase in TFP. However, these returns differ significantly between small and large plants. For large plants, those above the 25th percentile in number of employees, the increase in TFP is 2%. For plants below that size threshold, the returns to e-selling are statistically indistinguishable from zero. We further find that plants with prior experience with enterprise IT realize greater productivity gains from their e-selling investments. 2 - Piracy-induced Competition In Information-good Supply Chains Antino Kim, Indiana University, Bloomington, IN, United States, antino@iu.edu, Debabrata Dey, Atanu Lahiri In an otherwise monopolistic information goods market, piracy presents itself as a “shadow competition” to the legal product by providing consumers with other means to use the product, albeit at a lower quality. In this work, we analyze the effect of this shadow competition by comparing it to competition in a manufacturer-retailer setting. 3 - Impact Of Promoting Free Wi-fi On Mobile Data Usage: Evidence From A Field Experiment Karthik Babu Nattamai Kannan, Georgia Institute of Technology, KarthikBabu.NK@scheller.gatech.edu, Jeffrey Hu, Sridhar Narasimhan With the rapid proliferation of free Wi-Fi hotspots in public locations such as restaurants, shopping malls, airports etc., mobile users have the choice of accessing Internet either via paid mobile data plans or through the free Wi-Fi hotspots. We conduct a field experiment in July 2015 to study the impact of promoting free Wi-Fi service on mobile data usage. We work with a leading national mobile carrier in the USA to randomly choose 500,000 subscribers who receive a promotional text message about the availability of free Wi-Fi hotspots and compare them with a control group made of 500,000 customers who do not receive any promotional message. 4 - Strategic Intellectual Property Sharing: Competition on an OpenTechnology Platform Under Network Effects Marius Niculescu, Georgia Institute of Technology, marius.niculescu@scheller.gatech.edu, D. j. Wu, Lizhen Xu This study explores when an incumbent software developer might find it optimal to utilize the open business model to share its intellectual property with entrants in markets for software products with network effects. SA66 Mockingbird 2- Omni High-Dimensional Functional Data Analysis Sponsored: Quality, Statistics and Reliability Sponsored Session Chair: Hao Yan, Georgia Institute of Technology, yanhao@gatech.edu Co-Chair: Kamran Paynabar, kpaynabar3@gatech.edu 1 - Difference Detection Between Two Images For Image Monitoring Peihua Qiu, University of Florida, pqiu@ufl.edu Comparison of images is a fundamental task in image-based quality control. This problem, however, is complicated because 1) observed images often contain noise, and 2) the related images need to be geometrically matched up first because images of different products could be geometrically mismatched. In this paper, we propose effective methods for detecting difference between two images of products, and our proposed methods can accommodate both noise and geometric mismatch mentioned above.

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