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Parametrically Dependent Preferences for Multiattributed Consequences

Author

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  • Craig W. Kirkwood

    (University of Michigan, Ann Arbor, Michigan)

Abstract

The assessment of multiattribute cardinal utility functions can be a difficult experimental problem. To aid in this assessment, we define the concept of parametric dependence of preferences for multiattributed consequences. We show the usefulness of this concept for the assessment of multiattribute utility functions by proving several representation theorems that simplify the assessment problem when parametric dependence holds.

Suggested Citation

  • Craig W. Kirkwood, 1976. "Parametrically Dependent Preferences for Multiattributed Consequences," Operations Research, INFORMS, vol. 24(1), pages 92-103, February.
    • Handle: RePEc:inm:oropre:v:24:y:1976:i:1:p:92-103
    DOI: 10.1287/opre.24.1.92
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    Cited by:

    1. Jiehua Xie & Zhengyong Zhou, 2022. "Patchwork Constructions of Multiattribute Utility Functions," Decision Analysis, INFORMS, vol. 19(2), pages 141-169, June.
    2. Thomas W. Keelin & Bradford W. Powley, 2011. "Quantile-Parameterized Distributions," Decision Analysis, INFORMS, vol. 8(3), pages 206-219, September.
    3. Ali E. Abbas & Ronald A. Howard, 2005. "Attribute Dominance Utility," Decision Analysis, INFORMS, vol. 2(4), pages 185-206, December.
    4. Ali E. Abbas & David E. Bell, 2011. "One-Switch Independence for Multiattribute Utility Functions," Operations Research, INFORMS, vol. 59(3), pages 764-771, June.
    5. Ali E. Abbas, 2009. "Multiattribute Utility Copulas," Operations Research, INFORMS, vol. 57(6), pages 1367-1383, December.
    6. Abdildin, Yerkin G. & Abbas, Ali E., 2016. "Analysis of decision alternatives of the deep borehole filter restoration problem," Energy, Elsevier, vol. 114(C), pages 1306-1321.
    7. Ali E. Abbas, 2013. "Utility Copula Functions Matching All Boundary Assessments," Operations Research, INFORMS, vol. 61(2), pages 359-371, April.

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