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Nonlinear Utility Models Arising from Unmodelled Small World Intercorrelations

Author

Listed:
  • Robert F. Bordley

    (DRMS Program, National Science Foundation, 1800 G Street, NW, Washington, D.C., 20550)

  • Gordon Hazen

    (Operating Sciences Department, General Motors Research Labs, Warren, Michigan 48090 and Department of Industrial Engineering and Management Sciences, Northwestern University, Evanston, Illinois 60208)

Abstract

Savage's axioms show the rationality of maximizing expected utility when all uncertainties are explicitly modelled. But individuals actually make decisions in bounded contexts called small worlds. Savage's axioms do not imply the optimality of maximizing expected utility in small worlds unless lotteries in different small worlds are probabilistically independent. Relaxing this independence assumption causes Savage's axioms to imply the optimality of maximizing a nonlinear utility model which includes, as special cases, the Chew weighted linear utility model, the Bell elation/disappointment model and the Allais mean/variance model in utility-independent small worlds.

Suggested Citation

  • Robert F. Bordley & Gordon Hazen, 1992. "Nonlinear Utility Models Arising from Unmodelled Small World Intercorrelations," Management Science, INFORMS, vol. 38(7), pages 1010-1017, July.
    • Handle: RePEc:inm:ormnsc:v:38:y:1992:i:7:p:1010-1017
    DOI: 10.1287/mnsc.38.7.1010
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    Citations

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    Cited by:

    1. Simon Grant & John Quiggin, 2008. "Bounded rationality and small worlds," Risk & Uncertainty Working Papers WPR08_2, Risk and Sustainable Management Group, University of Queensland.
    2. Stewart, Theodor J. & French, Simon & Rios, Jesus, 2013. "Integrating multicriteria decision analysis and scenario planning—Review and extension," Omega, Elsevier, vol. 41(4), pages 679-688.
    3. Erio Castagnoli & Marco LiCalzi, 2005. "Expected utility without utility," Game Theory and Information 0508004, University Library of Munich, Germany.
    4. Gerald G. Brown & Louis Anthony (Tony) Cox, Jr., 2011. "How Probabilistic Risk Assessment Can Mislead Terrorism Risk Analysts," Risk Analysis, John Wiley & Sons, vol. 31(2), pages 196-204, February.

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