The Decision Analysis Special Recognition Award is given annually for the paper most worthy of recognition published in the Decision Analysis journal for the current year. The winner is announced by March of the following year and awarded a plaque by the award committee. We are pleased to announce the following awardees for 2020:
2020 Winner
Jeffery L. Guyse, L. Robin Keller, Candice H. Huynh
Valuing Sequences of Lives Lost or Saved Over Time: Preference for Uniform Sequences
Volume 17, Issue 1, March 2020
https://doi.org/10.1287/deca.2019.0397
Many policy decisions are based on the valuation of loss of lives over multi-period horizons. The winning paper provides an important contribution on this front by identifying behavioral anomalies that deviate from the normative standard discounting model. It uses laboratory experiments to show that individuals prefer uniform sequences of lives lost, rather than conforming to standard time discounting which is agnostic of such uniformity or other trends. This discovery has important implications for future decision analysis theory development and applications in medicine, public health, and environmental policies. First, it shows that alternative discounting models are required to assess alternatives with different sequences of loss of life. Second, more descriptive research is needed to better understand how individuals assess fatality rates. We congratulate the authors for this excellent paper, both for its rigor and its important practical implications.
2020 Finalist
Jay Simon, Donald Saari, L. Robin Keller
Interdependent Altruistic Preference Models
Volume 17, Issue 3, September 2020
https://doi.org/10.1287/deca.2020.0411
In many social settings, individuals seek to accommodate others' preferences and welfare when assessing alternatives, the representation of altruistic behavior in the DA literature so far has lacked a full axiomatization and is complicated by possibly interdependent preferences. The runner up paper provides a technical development to represent these altruistic preferences. This development has several strengths. It provides for tractable value functions which would enable other researchers to adopt them in various domains and contexts. Furthermore, these functions can be elicited using previously known DA protocols. Illustrated examples in the paper also provide exemplars for other researchers to use these value functions. Our congratulations to the authors on the development of this elegant theory and in doing that resolving a long-standing hurdle in the decision analysis literature.
2020 Award Selection Committee:
Saurabh Bansal (chair), Andrea Hupman, and Gilberto Montibeller
For more information about the award, and for past awardees: Decision Analysis Special Recognition Award
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Vicki Bier
Professor Emerita
University of Wisconsin
Madison WI
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