Informs Annual Meeting 2017

TA24

INFORMS Houston – 2017

TA24

2 - Economic and Environmentally Conscious Supply Chain Network Optimization for Determination of Potential Infrastructure and Production of Biogas Yong Shin Park, North Dakota State University/UGPTI, 1940 Dakota Drive N, Apt 203, Fargo, ND, 58102, United States, yong.park@ndsu.edu, Joseph Szmerekovsky Supply chain network design for the animal waste including biogas facility have not been addressed in the previous research. In response, we develop economic and environmentally conscious supply chain design of cattle manure to energy by incorporating carbon policy including carbon tax and cap and trade scheme. Mixed Integer Linear Programming (MILP) approach identify the optimal location of biogas plants and capacities to treat cattle waste from farm, and investigate the impact of the carbon policy on tactical and strategic supply chain decisions. A case study of North Dakota is adopted where there is high potential for biogas Cheng (Marshal) Wang, Economist, Environment and Climate Change Canada, 200 Sacré-Coeur Blvd., Office 1053, Gatineau, QC, J8X 4C6, Canada, cheng.uot@gmail.com Black Carbon is both a short-lived climate pollutant and an air pollutant linked to adverse health effects. Canada, as a member of an Arctic Council, so far has submitted black carbon inventories for 2013 and 2014 in the last two years to the Arctic Council following Convention on Long Range Transboundary Air Pollution guidelines. The objective of this presentation is to provide background information on black carbon and its relationship to climate change, explain the new BC reporting requirements, and provide a progress report on the development of black carbon projections, collective BC target and challenges. 4 - The Causality between Prices and Operating-equipment Costs in the Oil and Gas Industries Sergio Cabrales, Visiting Professor, Universidad de los Andes, Calle 19 A.no 1-37 Este, ML-758, Bogota, 111711, Colombia, s-cabral@uniandes.edu.co, Laura Herrera, Jesús Godoy Is there a bidirectional causal relationship between prices and costs in oil and gas markets? This paper studies the causality between prices and operating and equipment costs in oil and gas industries, using annual indexes (1976—2009). In oil market, we find a bidirectional Granger causality relationship between prices and operating costs. By contrast, in gas market, we observe the Granger causality only in one direction, indicating a causality of operating costs on gas prices. Finally, in contrast to operating costs, we do not find Granger causal relationship between prices and equipment costs in oil and gas industries. 350B Operational Implications of 3D Printing Sponsored: Manufacturing & Service Oper Mgmt Sponsored Session Chair: Lingxiu Dong, Washington University, Saint Louis, MO, 63130-4899, United States, dong@wustl.edu Co-Chair: Duo Shi, Olin Business School, Washington University- St Louis, St. Louis, MO, 63130, United States, dshi@wustl.edu 1 - Stock or Print? Impact of 3D Printing on Spare Parts Logistics Yue Zhang, Duke University, 5507 Butterfly Ln Apt 207, Durham, NC, 27707, United States, yueyue.zhang@duke.edu, Jing-Sheng Jeannette Song We present a general framework to analyze and quantify the impact of 3D printing on spare parts logistics. We consider multiple parts facing stochastic demands. To minimize long-run average system cost, our model determines which parts should be printed and which should be stocked and the corresponding base-stock levels. We derive various structural properties and characterize the optimal policy for several special systems, which lead to efficient near-optimal heuristic solutions for the general system. We demonstrate that adopting 3D technology can yield significant cost savings and this impact increases in part variety. 2 - Personal Fabrication as an Operational Strategy: Value of Delegating Production to Customer Nagarajan Sethuraman, PhD Candidate, University of North Carolina, Campus Box 3490, McColl Building, Chapel Hill, NC, 27599, United States, Nagarajan_Sethuraman@kenan-flagler.unc.edu, Ali Kemal Parlakturk, Jayashankar M.Swaminathan In this paper, we study an operational strategy enabled by 3D printing—- Personal Fabrication (PF) —-in which a firm focuses on product’s design and delegates its production to customers. We characterize the conditions under which, such a strategy benefits the firm. We study the implications of various roadblocks for such a strategy: high production costs of 3D printing, intellectual property concerns and product liability issues. production based on number of cattle inventory. 3 - Black Carbon Projection in Energy Model TA26

342F Mean Field Approaches and Applications Sponsored: Revenue Management & Pricing Sponsored Session

Chair: Gabriel Weintraub, Stanford Graduate School of Business, Stanford, CA, 94304, United States, gweintra@stanford.edu 1 - Pairwise Comparisons for Online Reputation Systems Nikhil Garg, 825 Menlo Avenue, Apt G, Menlo Park, CA, 94025, United States, nkgarg@stanford.edu, Ramesh Johari Modern online marketplaces rely on reputation systems to assess participants, and enable search and matching. Typically, these systems rely on cardinal ratings — e.g., the ubiquitous five star rating system. Inspired by a number of issues that these systems have encountered in practice, we suggest an alternative: reputation systems based on pairwise comparisons. We use a mean field model to compare and contrast such a rating system with cardinal ratings, and present theoretical results, simulations, and empirical analysis that suggest that such rankings can be significantly more informative than cardinals ratings. 2 - An Empirical Framework for Sequential Assignment Allocating Deceased Donor Kidneys Itai Ashlagi, Stanford University, Department of Management Sci. and Engr., Stanford, CA, 94305, United States, iashlagi@stanford.edu We provide an empirical framework for designing the allocation of cadaver organs. 3 - Transitional Market Dynamics in Complex Environments Gabriel Weintraub, Stanford Graduate School of Business, Knight Management Center, Stanford University, 655 Knight Way, E364, Stanford, CA, 94304, United States, gweintra@stanford.edu, Lanier Benkard, Przemek Jeziorski Recent work in dynamic oligopoly models uses mean-field approaches to approximate long-run Markov perfect industry dynamics. In several applications though, one is interested in the short-run dynamic behavior of an industry after a policy or environmental change. We introduce a mean-field approach for these settings and show that a “resolving” version provides accurate approximations even in concentrated industries. We illustrate our methods with several dynamic oligopoly models relevant to IO and also in a model of network effects. 4 - On Matching in Ridesharing Systems Amy R. Ward, University of Southern California, Marshall School of Business, Bridge Hall BR.I.401H, Los Angeles, CA, 90089-0809, United States, amyward@marshall.usc.edu, Erhun Ozkan In a ridesharing system such as Uber or Lyft, arriving customers must be matched with available drivers. These decisions affect the overall number of customers matched, because they impact whether or not future available drivers will be close to the locations of arriving customers. A common policy used in practice is the closest driver policy that offers an arriving customer the closest driver. This is an attractive policy because it is simple and easy to implement. However, we expect that a forward-looking parameter-based policy can achieve better performance. We prove asymptotic optimality of a matching policy based on a continuous linear program in a large market regime 350A Recent Advances in Oil and Gas I Invited: Energy Systems Management Invited Session Chair: Leah Kaffine, GE Energy Consulting, 16100 W 62nd Dr, Arvada, CO, 80403, United States, leah.kaffine@ge.com 1 - Integrated Gas Electric Modeling with GE MAPS and RBAC GPCM Leah Kaffine, GE Energy Consulting, 16100 W. 62nd Dr, Arvada, CO, 80403, United States, leah.kaffine@ge.com Examine the importance of a time varying price elasticity assumption of natural gas demand for power in RBAC’s GPCM model. By default, these assumptions are homogenous and independent of time. Coal retirements, renewables and increased gas fired generation are impacting the ability to respond to price signals. TA25

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