2015 Informs Annual Meeting

SA63

INFORMS Philadelphia – 2015

SA63 63-Room 112B, CC

SA65 65-Room 113B, CC

Nicholson Student Paper Competition Cluster: Nicholson Student Paper Competition Invited Session Chair: Illya Hicks, Rice University, 6100 Main MS-134, Houston, TX, 77005, United States of America, ivhicks@rice.edu 1 - Nicholson Student Paper Competition Illya Hicks, Rice University, 6100 Main MS-134, Houston, TX, 77005, United States of America, ivhicks@rice.edu This session highlights the finalists for the 2015 George Nicholson Student Paper Competition. Experts & Algorithms Sponsor: Decision Analysis Sponsored Session Chair: Jason Merrick, Professor, Virginia Commonwealth University, P.O. Box 843083, 1015 Floyd Avenue, Richmond, VA, 23284, United States of America, jrmerric@vcu.edu 1 - Experts & Algorithms: Lessons in Blending Analytics with Subjective Judgment Cade Massey, Practice Professor, University of Pennsylvania, 3730 Walnut St., Huntsman 554, Philadelphia, PA, 19104, United States of America, cadem@wharton.upenn.edu, Jason Merrick We share insights and tools gleaned from an 18-month project implementing an analytics-based decision model for the admissions process at a large graduate school. Issues include preference elicitation, forecasting, optimization and group decision-making. We address both the theoretical and practical challenges involved. 2 - Technology Implementation Decisions: A Multi-objective, Multi- Stakeholder Case Study Ed Cook, Capital One, ed.cook@capitalone.com, Jason Merrick Major corporate technology adoption decisions are based on the financial case and take an organization-wide viewpoint. However, technology implementation decisions are different in nature and affect various stakeholders across the organization with multiple, conflicting objectives. Our case study examines how to implement a major technology change across a thousand branches of a national bank and to avoid the costly delays and problems that afflicted other banks implementing this technology. 3 - Overcoming Algorithm Aversion Berkeley Dietvorst, Doctoral Student, The Wharton School, 3730 Walnut St, Suite 500, Philadelphia, PA, 19104, United States of America, diet@wharton.upenn.edu, Joe Simmons, Cade Massey How can we get forecasters to use algorithms instead of human judgment? In four experiments, participants decided whether to use an algorithm’s forecasts or their own to complete a forecasting task. In the treatment conditions we gave participants the option to modify the algorithm’s forecasts if they chose to use it. Participants chose to use the algorithm much more often when they could modify its forecasts, even when the amount that they could modify its forecasts was severely restricted. 4 - Failure to Replicate Hyperbolic Discounting in Large-scale Studies Yael Grushka-Cockayne, Assistant Professor, Darden School of Business, University ot Virginia, FOB 163,100 Darden Blvd, Charlottesville, VA, United States of America, grushkay@darden.virginia.edu, Daniel Read, Casey Lichtendahl We propose a simple model in which future income risk can explain hyperbolic and anti-hyperbolic discounting. We present results from multiple experimental studies involving thousands of participants, some of whom were asked Gallup- type questions about future income. Overall, we fail to replicate hyperbolic discounting. Instead, we find that anti-hyperbolic discounting effects are large and reliable across studies, with little dependency on income expectations. SA64 64-Room 113A, CC

Joint Session DAS/ENRE: Panel Discussion: Climate Assessment and Decision Analysis Sponsor: Decision Analysis & ENRE Sponsored Session

Moderator: Melissa Kenney, Research Assistant Professor, University of Maryland, 5825 University Research Court, Suite 4001, College Park, MD, 20740, United States of America, kenney@umd.edu 1 - Decision Analysis in the IPCC and National Climate Assessment Robert Lempert, Senior Scientist, RAND, 1776 Main St, Santa Monica, CA, 90407, United States of America, lempert@rand.org Decision and risk analysis is playing an increasingly important role in scientific assessments of climate change. This talk will describe this role, drawing on the speaker’s experience as a lead author of the decision support chapters of both the US National Climate Assessment and Intergovernmental Panel on Climate Change (IPCC) Working Group II Fifth Assessment Report. 2 - Climate Change Decision Support Systems: Validation Required Richard Moss, Senior Scientist, Pacific Northwest National Lab, Joint Global Change Research Institute, 5825 University Research Ct. Ste. 3500, College Park, MD, 20740, United States of America, rhm@pnnl.gov An increasing number of climate change decision support systems are being offered for use. Overall, little is known about the effectiveness of many of these tools. Failure to assess existing tools and practices is setting the research community up for a loss of trust. This paper describes aspects of climate-related decision support that require evaluation and argues that the decision analysis community has a leadership role to play in this process through the US National Climate Assessment. 3 - Climate Indicators: Do They Help or Hinder Decision Processes? Melissa Kenney, Research Assistant Professor, University of Maryland, 5825 University Research Court, Suite 4001, College Park, MD, 20740, United States of America, kenney@umd.edu Though in Decision Analysis indicators measure objectives, in practice indicators may not be linked to specific decision contexts. I will describe an effort to develop recommendations to the U.S. Global Change Research Program for a wide- reaching indicator system to inform decision about climate changes and impacts. I will discuss preliminary work to determine if these kinds of indicators are useful for decision structuring or as attributes in different decision processes. 4 - Discussant Robert O’Connor, roconnor@nsf.gov 5 - Risk and Resilience for Climate Change Igor Linkov, Risk and Decision Science Team Lead, US Army Corps of Engineers, Engineer R&D Center, 696 Virginia Rd, Concord, MA, United States of America, Igor.Linkov@usace.army.mil, Catherine Fox-lennt An urgent need exists to complement the existing knowledge-base of climate change risk by further developing frameworks enabling system-wide analysis. A promising lens is resilience, a system property that can be planned for and managed irrespective of adverse impact or system vulnerability. This presentation will summarize our ideas and case study on the use of risk-based decision making and decision-driven resilience management. SA66 66-Room 113C, CC Airlines Network Planning and Scheduling Applications Sponsor: Aviation Applications Sponsored Session Chair: Ahmed Abdelghany, Associate Professor, Embry-Riddle Aeronautical University, 600 S. Clyde Morris blvd, Daytona Beach, United States of America, abdel776@erau.edu 1 - Stochastic Fleeting with Itinerary Attractiveness in MapReduce Diego Klabjan, Professor, Northwestern University, Evanston IL, United States of America, d-klabjan@northwestern.edu Stochastic fleeting models with discrete choice based on attractiveness are computationally challenging. Parallel computing via Hadoop and MapReduce have become ubiquitous. We study algorithms under the MapReduce parallel framework for stochastic fleeting with attractiveness.

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