Robert Bordley

About

Robert Bordley is a Professor of Practice and the Director of Systems Engineering and Design (SED) Master's Program at the University of Michigan's Industrial & Operations Engineering department. He joined the university part-time in 2002 and became a full-time faculty member in 2016. Bordley's professional background includes work at Booz-Allen-Hamilton on Army procurement decisions, serving as director of the Decision, Risk and Management Sciences Program at the National Science Foundation, and holding multiple roles at General Motors. At GM, he led innovations in revenue management, cost and profit analysis, dealer satisfaction driver analysis, product segmentation, and systems engineering practices in vehicle design. He is an officer of the International Council of Systems Engineers and has held leadership roles in the Risk Section of the American Statistical Association, the Production and Operations Management Society, and INFORMS, where he is a Fellow. His research focuses on systems engineering with an emphasis on decision analysis, including target-oriented utility, experiment-dependent probabilities, forecast combination, project management volatility targets, interproduct similarity measurement, quantum probabilities, and graphical decision analysis. Bordley's educational background includes a PhD, MS, and MBA from the University of California, Berkeley, and a BS and BA from Michigan State University. His professional memberships include IEEE, INFORMS, and the…

Research topics

• Computer science
• Economics
• Econometrics
• Mathematical economics
• Mathematics

Selected publications

• Managing projects with uncertain deadlines

  European Journal of Operational Research · 2018-10-08 · 27 citations

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• Using incentives to address cannibalization

  Long Range Planning · 2017-04-23 · 13 citations

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• A Target-Based Foundation for the “Hard-Easy Effect” Bias

  Eurasian studies in business and economics · 2016-11-10 · 6 citations

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• Expected information of noisy attribute forecasts for probabilistic forecasts

  European Journal of Operational Research · 2024-12-20 · 1 citations

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• Benchmark-Based Preferences Make Investors Loss Averse in Bull Markets and Gain Seeking in Bear Markets

  International Journal of Business and Management · 2017-12-18 · 1 citations

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  Recent empirical studies have shown that investors are far more likely to be loss averse during bull markets than during bear ones. The aim of this short note is to give solid foundations to this empirical evidence. Using the benchmark-based preference method we establish a direct connection between the individual perception of the market trend and the individual risk preferences. Then we develop a novel definition of loss aversion and gain seeking which intuitively captures the human attitudes…

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Frequent coauthors

• Luisa Tibiletti

  University of Turin

  15 shared

• Gordon B. Hazen

  Northwestern University

  12 shared

• Mariacristina Uberti

  University of Turin

  7 shared

• Jeffrey M. Keisler

  University of Massachusetts Boston

  4 shared

• Francesca Culasso

  University of Turin

  3 shared

• James Matheson

  3 shared

• James B. McDonald

  Brigham Young University

  3 shared

• Elisa Giacosa

  University of Turin

  3 shared

Education

• PhD, industrial Engineering and Operations Research

  University of California Berkeley

Awards & honors

• Tom Sawyer Teaching Award, University of Michigan, 2023
• Ramsey Medal for Distinguished Contributions in Decision Ana…
• Best Publication Award, Decision Analysis Society, 2006
• Distinguished Educator Award, Industrial Engineering and Ope…
• Gold Award, Engineering Society of Detroit, 2023

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