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Risk Preferences for Gains and Losses in Multiple Objective Decision Making


  • Gregory W. Fischer

    (Department of Social and Decision Sciences, Carnegie-Mellon University, Pittsburgh, Pennsylvania 15213)

  • Mark S. Kamlet

    (Department of Social and Decision Sciences, Carnegie-Mellon University, Pittsburgh, Pennsylvania 15213)

  • Stephen E. Fienberg

    (Department of Social and Decision Sciences, Carnegie-Mellon University, Pittsburgh, Pennsylvania 15213)

  • David Schkade

    (College of Business Administration, University of Texas, Austin, Texas 78712)


Payne, Laughhunn, and Crum (Payne, J. W., D. J. Laughhunn, R. Crum. 1984. An experimental study of multiattribute risky choice. Management Sci. 30 1350--1361.) found that managers were multiattribute risk averse for gains, but multiattribute risk prone for losses, a pattern that is inconsistent with both the additive and the multiplicative multiattribute utility models. In this paper we develop the reference risk-value (RRV) model, which is simple in structure yet capable of representing the kinds of multiattribute reference effects observed by Payne et al. We also report the results of two experiments that compare the descriptive validity of the RRV model with that of the additive and multiplicative utility models. Experiment 1 involved choices between risky multiperiod cash flows; Experiment 2 choices between risky job alternatives described by change in salary and change in type of work. In Experiment 1, subjects were multiattribute risk averse for gains, but multiattribute risk neutral for losses. In Experiment 2, subjects were multiattribute risk averse for both gains and losses, but significantly more so for losses. Because both experiments produced significantly different multiattribute risk preferences for gains than losses, both favor the RRV model over the widely used additive and multiplicative models. However, because the patterns of multiattribute risk preferences for gains and losses were strikingly different in the two experiments, these results argue against any direct generalization of the "reflection effect" to a multiattribute context.

Suggested Citation

  • Gregory W. Fischer & Mark S. Kamlet & Stephen E. Fienberg & David Schkade, 1986. "Risk Preferences for Gains and Losses in Multiple Objective Decision Making," Management Science, INFORMS, vol. 32(9), pages 1065-1086, September.
  • Handle: RePEc:inm:ormnsc:v:32:y:1986:i:9:p:1065-1086

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    Cited by:

    1. Kuhberger, Anton, 1998. "The Influence of Framing on Risky Decisions: A Meta-analysis," Organizational Behavior and Human Decision Processes, Elsevier, vol. 75(1), pages 23-55, July.
    2. Maximilian Rüdisser & Raphael Flepp & Egon Franck, 2017. "Do casinos pay their customers to become risk-averse? Revising the house money effect in a field experiment," Experimental Economics, Springer;Economic Science Association, vol. 20(3), pages 736-754, September.
    3. Wilson, Kevin J. & Quigley, John, 2016. "Allocation of tasks for reliability growth using multi-attribute utility," European Journal of Operational Research, Elsevier, vol. 255(1), pages 259-271.
    4. Han Bleichrodt & Ulrich Schmidt & Horst Zank, 2009. "Additive Utility in Prospect Theory," Management Science, INFORMS, vol. 55(5), pages 863-873, May.
    5. Han Bleichrodt & Jose Luis Pinto & Peter P. Wakker, 2001. "Making Descriptive Use of Prospect Theory to Improve the Prescriptive Use of Expected Utility," Management Science, INFORMS, vol. 47(11), pages 1498-1514, November.
    6. Matos, Manuel A., 2007. "Decision under risk as a multicriteria problem," European Journal of Operational Research, Elsevier, vol. 181(3), pages 1516-1529, September.
    7. repec:eee:jobhdp:v:140:y:2017:i:c:p:1-13 is not listed on IDEAS
    8. Peter P. Wakker & Daniëlle R. M. Timmermans & Irma Machielse, 2007. "The Effects of Statistical Information on Risk and Ambiguity Attitudes, and on Rational Insurance Decisions," Management Science, INFORMS, vol. 53(11), pages 1770-1784, November.


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