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The Multiattribute Utility Tree

Author

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  • Ali E. Abbas

    (Department of Industrial and Enterprise Systems Engineering, University of Illinois at Urbana--Champaign, Urbana, Illinois 61801)

Abstract

This paper introduces the notion of a multiattribute utility tree. This graphical representation decomposes the von Neumann--Morgenstern utility of a multiattribute consequence into a sum of products of indifference probability assessments of binary gambles. The utility tree displays the sequence of gambles required to elicit the utility value of a consequence. In addition, it enables the analyst to conduct consistency checks on the indifference assessments provided by the decision maker and to change the order of the assessments based on her comfort level. Once the indifference assessments are provided, the utility value of a consequence can be obtained by direct rollback analysis. On a continuous domain, the utility tree decomposes the functional form of a multiattribute utility function into a sum of products of normalized conditional utility functions. Each attribute in the expansion is conditioned on the boundary values of the attributes expanded before it. This formulation provides a general method for deriving the functional form of a multiattribute utility function under a wide variety of conditions. It also leads to several new independence concepts such as “boundary independence,” which is a weaker condition than utility independence, and “corner independence,” which makes higher-order independence assertions. Reversing the order of the nodes in the tree relates several widely used notions of utility independence found in the literature.

Suggested Citation

  • Ali E. Abbas, 2011. "The Multiattribute Utility Tree," Decision Analysis, INFORMS, vol. 8(3), pages 180-205, September.
  • Handle: RePEc:inm:ordeca:v:8:y:2011:i:3:p:180-205
    DOI: 10.1287/deca.1110.0211
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    References listed on IDEAS

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    1. Bordley R.F., 2002. "Representing Trees Using Microsoft Doughnut Charts," The American Statistician, American Statistical Association, vol. 56, pages 139-147, May.
    2. Ali E. Abbas & David E. Bell, 2011. "One-Switch Independence for Multiattribute Utility Functions," Operations Research, INFORMS, vol. 59(3), pages 764-771, June.
    3. Ali E. Abbas, 2009. "Multiattribute Utility Copulas," Operations Research, INFORMS, vol. 57(6), pages 1367-1383, December.
    4. Ali E. Abbas & Ronald A. Howard, 2005. "Attribute Dominance Utility," Decision Analysis, INFORMS, vol. 2(4), pages 185-206, December.
    5. Peter H. Farquhar, 1975. "A Fractional Hypercube Decomposition Theorem for Multiattribute Utility Functions," Operations Research, INFORMS, vol. 23(5), pages 941-967, October.
    6. David E. Bell, 1979. "Multiattribute Utility Functions: Decompositions Using Interpolation," Management Science, INFORMS, vol. 25(8), pages 744-753, August.
    7. Gordon B. Hazen & James M. Pellissier, 1996. "Recursive Utility for Stochastic Trees," Operations Research, INFORMS, vol. 44(5), pages 788-809, October.
    8. Gordon B. Hazen, 1993. "Factored Stochastic Trees," Medical Decision Making, , vol. 13(3), pages 227-236, August.
    9. Ali E. Abbas, 2011. "Decomposing the Cross Derivatives of a Multiattribute Utility Function into Risk Attitude and Value," Decision Analysis, INFORMS, vol. 8(2), pages 103-116, June.
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    Cited by:

    1. Ali E. Abbas & Zhengwei Sun, 2015. "Multiattribute Utility Functions Satisfying Mutual Preferential Independence," Operations Research, INFORMS, vol. 63(2), pages 378-393, April.
    2. Dogucan Mazicioglu & Jason R. W. Merrick, 2018. "Behavioral Modeling of Adversaries with Multiple Objectives in Counterterrorism," Risk Analysis, John Wiley & Sons, vol. 38(5), pages 962-977, May.
    3. Manuele Leonelli & Jim Q. Smith, 2017. "Directed Expected Utility Networks," Decision Analysis, INFORMS, vol. 14(2), pages 108-125, June.
    4. 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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