2015 Informs Annual Meeting

SC56

INFORMS Philadelphia – 2015

4 - Contract or Trust? An Experimental Study Based on VMI Setting Dezhen Si, Tsinghua University, Shunde Building, Beijing, China, sidezhen@126.com, Zuo-jun Max Shen, Xiaobo Zhao We conduct experiments to study decision behaviors in trust game and contract game under a VMI setting. We recruit both strangers and acquaintances as subjects to participate in our experiments. The results show that preferences such as reciprocity and fairness exist in the games, and as a result, acquaintances in the trust game perform the best. We also develop behavioral models to explain the findings. SC54 54-Room 108A, CC Uncertainty in Demand Response – Identification, Estimation, and Learning Chair: Josh Taylor, Assistant Professor, University of Toronto, 10 King’s College Rd., SF 1021C, Toronto, ON, M5S3G4, Canada, josh.taylor@utoronto.ca 1 - Uncertainty in Demand Response – Identification, Estimation, and Learning Josh Taylor, Assistant Professor, University of Toronto, 10 King’s College Rd., SF 1021C, Toronto, ON, M5S3G4, Canada, josh.taylor@utoronto.ca, Johanna Mathieu Demand response from flexible electric loads such as electric vehicles, air conditioners and smart home appliances represents a vast, clean and potentially high-performance resource for the electric power system, but loads are highly uncertain. In this tutorial, we survey techniques for managing load uncertainty in demand response for three problem types: identifying load models, estimating load states and learning these features in conjunction with deploying the loads for demand response. SC55 55-Room 108B, CC Applications of DEA Cluster: Data Envelopment Analysis Invited Session Chair: Kankana Mukherjee, Babson College, Wellesley, Massachusetts, kmukherjee@babson.edu 1 - Analysis of Technological Gap of Agricultural Productivity among Sub-Saharan African Countries Olajide Abraham Ajao, PhD, Ladoke Akintola University of Technology, Agricultural Economics Department, Ogbomos, Nigeria, oaajao57@lautech.edu.ng, Ogunniyi Laudia Titilola, Abdulrasheed Mutolib The study compared the productivity differences of technical efficiency and technological gap ratios in SSA agriculture by adapting metafrontier DEA approach using cross-country panel input-output data obtained from the FAO. It was found that the metafrontier scores varied widely among the countries and also, the regional differences in the production technologies was observed 2 - Capacity Utilization and Energy Efficiency in Indian Manufacturing This study uses Data Envelopment Analysis and data from the Annual Survey of Industries, India, to measure capacity utilization and explores the relationship between an energy efficiency index and a capacity utilization index for each of the energy intensive industries in India over the period 1998-99 through 2007- 08. 3 - The Analysis of Productivity Pattern of Cereals in Nigeria (1995 - 2006) Cluster: Tutorials Invited Session Kankana Mukherjee, Babson College, Wellesley, MA, United States of America, kmukherjee@babson.edu Ogunniyi Laudia Titilola, Ladoke Akintola University of Technology, Agricultural Economics Department, Ogbomos, Nigeria, titiogunniyi@yahoo.com, Olajide Abraham Ajao, Gbenga Fanifosi This study analysed the productivity pattern of cereals in Nigeria between the periods of 1995-2006 using Data Envelopment Analysis to estimate total factor productivity(TFP)index. A decomposition of TFP measures revealed that productivity is due largely to technological change over the reference period and the technical efficiency indexes showed Taraba state and the Federal Capital Territory(FCT) to be consistently efficient and lie on the best - practice frontier.

4 - Economic Measures of Capacity Utilization: A Nonparametric Cost Function Analysis John Walden, Economist, NOAA/NMFS/NEFSC, 166 Water St., Woods Hole, MA, 02543, United States of America, john.walden@noaa.gov, Subhash Ray Capacity utilization (CU) is an important economic metric which conveys information about a firm’s output level. We adopt the methods proposed by Ray (2014) to estimate cost based CU using DEA for a group of commercial fishing vessels which are characterized by a multi-input, multi-output technology. Results show the cost minimizing output level and CU for vessels operating in the years 2007-2012, and how these have changed in the light of recent regulatory shifts. 5 - Technical Efficiency Gains from Two Land Management Options in Maize Farming, Southwestern Nigeria Luke Olarinde, Dr, Ladoke Akintola University of Technology, Department of Agricultural Economics, PMB 4000, Ogbomoso, Oy, 210001, Nigeria, loolarinde@lautech.edu.ng This study investigated the contribution of two Land management (LM) options (crop protection and crop management practices) to technical efficiencies (TEs) in Maize farming in Southwestern Nigeria. Data Envelopment Analysis (DEA) results (for the TE gains) indicate slight differences in the TEs of farms in the two LM options. 105 St.George Street, M5S 3E6, Canada, Krass@rotman.utoronto.ca 1 - The Big Tetrahedron Small Tetrahedron Method for Three Dimensional Location Problems Rina Nakayama, Nanzan University, 18 Yamazato-cho, Showa- ku, Nagoya, Japan, m14ss007@nanzan-u.ac.jp, Zvi Drezner, Atsuo Suzuki, Tammy Drezner We extend the Big Triangle Small Triangle method to three dimensions. We call it the Big Tetrahedron Small Tetrahedron method. We apply it to three dimensional location problems such as three dimensional Weber problem with Attraction and Repulsion (WAR) and time space location problems. 2 - Locating a New Facility to Maximize its Voronoi Region Dmitry Krass, Rotman School of Management, 105 St.George Street, M5S 3E6, Canada, Krass@rotman.utoronto.ca, Jonathan Lorraine Consider a set of competing facilities in a planar region where demand is continuously distributed and the trading area of each facility is its Voronoi cell (all points closest to the facility). We wish to add a new facility that will capture as much demand as possible. We develop a fast solution method based on Big Triangle-Small Triangle approach. The method is applicable to both uniform and non-uniform demand distributions. Applications to real-life facility sets will be demonstrated. 3 - Planning Service Maintenance under Disruption Threats Mozart Menezes, Associate Professor, Kedge Business School- Bordeaux, 680 Cours de la Libération, Bordeaux, 33405, France, mozart.menezes@me.com, Dmitry Krass We investigate the situation where facilities serving nodes may have service disrupted forcing nodes to be served by facilities providing service at higher cost. Disruption threats can be reduced when facilities undergo maintenance at a cost. The decision maker also incurs cost for repairing facilities and for maintaining facilities. We focus on the trade-off between planned maintenance versus allowing facilities to continue operation but risking a much higher cost when disruption happens. SC56 56-Room 109A, CC New Directions in Locational Analysis Sponsor: Location Analysis Sponsored Session Chair: Dmitry Krass, Rotman School of Management,

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