2015 Informs Annual Meeting

MA61

INFORMS Philadelphia – 2015

MA60 60-Room 111A, CC Enabling Business Students to Use OR Sponsor: INFORM-ED Sponsored Session

2 - Big Data in the Energy Industry Margery Connor, Chevron, 6001 Bollinger Canyon, F-2080, San Ramon, CA, 94583, MHCO@chevron.com This presentation will discuss our internal efforts to build a big data platform. It will include a couple of use cases. It will also include challenges and lessons learned. 3 - Emerging Applications of Optimization in the Energy Industry Haraldur Haraldsson, Aimms Optimization Specialist, AIMMS, 500 108th Avenue NE, Ste. #1780, Suite 1780, Bellevue, WA,

Chair: Thomas Grossman, Professor, University of San Francisco, School of Management, 101 Howard St., Suite 500, San Francisco, CA, 94105, United States of America, tagrossman@usfca.edu 1 - Teaching Modeling to Business Students Wendy Roth, Assistant Professor, Georgia State University, 6230 Forest Park Dr, Signal Mountain, TN, 37377, United States of America, wroth@gsu.edu Due to the popularity of business analytics, interest in business modeling classes appears to be increasing. When considering the student skill level as compared to a few years ago, this has resulted in a broader variety of student backgrounds, not necessarily self- selected based on a strong math background. This session will discuss some of those differences and modifications made to the classroom to help address these differences. 2 - Teaching Distribution Planning: A PBL Approach Alex Grasas, Associate Professor, EADA Business School, Arago 204, Barcelona, Spain, agrasas@eada.edu, Helena Ramalhinho This work presents a problem-based learning (PBL) activity that uses a decision support system (DSS) to teach one of the most fundamental topics in distribution planning: vehicle routing. This pedagogical activity, employed in a logistics and supply chain management course, also seeks to create awareness among students on the importance of DSS for complex problems. The paper is written as a teaching guide for other instructors, detailing how the activity may be carried out in class. 3 - Spreadsheet Engineering: The Foundation for OR/MS Applications by Business Students Vijay Mehrotra, Professor, University of San Francisco, School of Management, 101 Howard St., Suite 500, San Francisco, CA, 94105, United States of America, vmehrotra@usfca.edu, Thomas Grossman, Mouwafac Sidaoui To access the power of OR/MS on non-trivial models, business students must first learn to apply software engineering principles to develop high quality spreadsheets. We have developed a methodology for teaching this skill to business students, many of whom have little or no relevant technical experience prior to our course. This talk describes how we successfully teach business students to build complex spreadsheet models that then serve as the foundation for OR/MS applications. MA61 61-Room 111B, CC Transmission and Generation Expansion Planning Sponsor: ENRE – Energy I – Electricity Sponsored Session Chair: Enzo Sauma, Pontificia Universidad Catolica de Chile, Santiago, Chile, esauma@ing.puc.cl 1 - Risk-averse Transmission and Generation Planning: A WECC Case Study Harry Van Der Weijde, University of Edinburgh, The King’s Buildings, Mayfield Road, Edinburgh, EH9 3JL, United Kingdom, h.vanderweijde@ed.ac.uk, Francisco Munoz, Benjamin Hobbs, Jean-paul Watson We investigate the effects of risk aversion on optimal transmission and generation expansion planning. To do so, we formulate a stochastic model in which transmission and generation planners minimize a weighted average of expected costs and their conditional values at risk. This model is then applied to a 240-bus representation of the Western Electricity Coordinating Council, in which we examine the impact of risk aversion on levels and spatial patterns of investment, costs, and prices. 2 - Robust Transmission Expansion Planning Antonio Conejo, Prof., The Ohio State University, 286 Baker Systems Engineering, 1971 Neil Avenue, Columbus, OH, 43210, United States of America, conejonavarro.1@osu.edu This presentation discusses a number of critical issues to successfully design and implement transmission expansion planning algorithms using an adaptive robust optimization approach. These issues include formulation format, selection of robust sets, sensitivity analysis, and out-of-sample simulation.

98004, United States of America, haraldur.haraldsson@aimms.com

With data analytics and optimization gathering focus in many organizations, there is an increased opportunity to leverage advanced analytics. We will share some examples on potential use of advanced analytics in the energy industry for future cases.

MA59 59-Room 110B, CC Strategy, Innovation, and Entry Cluster: Strategy Science Invited Session

Chair: Hart Posen, University of Wisconsin, 4263 Grainger Hall, 975 University Avenue, Madison, WI, 53705, United States of America, hposen@bus.wisc.edu 1 - Spinout Formation and Parent Firm Performance: A Multi-industry Examination Seth Carnahan, University of Michigan, 701 Tappan St., R4460 Ross School of Business, Ann Arbor, MI, 48104, United States of America, scarnaha@umich.edu, Benjamin Campbell, Rajshree Agarwal Some scholars find an increase in firm performance when former employees create startup organizations (“spinouts”), while others find a decrease. We articulate the competing mechanisms that underlie these positive and negative results, and we argue that conflicting findings are driven largely by industry differences. We utilize a multi-industry sample based on US Census microdata that allows us to identify and test the competing mechanisms. 2 - Spinout Formation: Do Opportunities and Constraints Benefit High Human Capital Founders? Natarajan Balasubramanian, Syracuse University, 721 University Ave, Syracuse, NY, United States of America, nabalasu@syr.edu, Mariko Sakakibara Using a large sample of individuals who formed spinouts and their co-workers who did not, we how industry contexts affect the relative advantage of high human capital founders. We find that such individuals are less likely to form spinouts in capital-intensive and R&D-intensive industries. This suggests that in capital intensive industries, high human capital founders face greater constraints while R&D intensive industries offer opportunities for both high and low human capital founders. 3 - Entrepreneurial Joiners Michael Roach, Cornell University, Dyson School, Ithaca, NY, 14853, United States of America, michael.roach@cornell.edu, Henry Sauermann Startups rely not only on founders, but also on “joiners”–individuals attracted to entrepreneurship as an employee rather than a founder. We find that individuals with joiner interests share preferences for entrepreneurial job attributes often considered unique to founders, but differ with respect to contextual factors. This study reveals that preferences and context interrelate in unique ways to shape entrepreneurial interests and highlights joiners as a distinct type of entrepreneurial actor. 4 - (how) Do Individual Characteristics Influence Resource Allocation and Competitive Advantage? Michael Leiblein, Ohio State University, Fisher College of Business, Columbus, OH, 43220, United States of America, leiblein.1@osu.edu, Barclay Burns, Sheen Levine A fundamental issue in the field of strategic management regards the identification of sources of competitive advantage. Why do firms differ and how do managers influence firm behavior? If individuals matter and theories of competitive advantage are correct, then unique individuals should differ in their resource allocation decisions and outcomes. This proposal promises to report emerging evidence associating individual characteristics, resource allocation decisions, and competitive advantage.

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