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A Perspective on Modeling in Decision Analysis

Author

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  • Steven N. Tani

    (SRI International, Menlo Park, California)

Abstract

We use mathematical modeling in decision analysis to help us obtain a profit lottery that is "better" than the one we can assess directly. The "goodness" of the profit lottery is defined by the concept of authenticity of probabilities. The role of modeling is to simplify our assessment task through decomposition of the profit lottery. However, budgetary constraints force us to make approximations in the modeling process and thereby force us to misstate the profit lottery. When dealing with our dissatisfactions about the modeling in a decision analysis, we regard models as subjective expressions of our uncertainty rather than as objective descriptions of the real-world.

Suggested Citation

  • Steven N. Tani, 1978. "A Perspective on Modeling in Decision Analysis," Management Science, INFORMS, vol. 24(14), pages 1500-1506, October.
    • Handle: RePEc:inm:ormnsc:v:24:y:1978:i:14:p:1500-1506
    DOI: 10.1287/mnsc.24.14.1500
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    Cited by:

    1. Baldwin, Katherine L. & Foster, Ken & Jones, Keithly, 2011. "A stochastic approach to evaluating livestock marketing policy initiatives," African Journal of Agricultural and Resource Economics, African Association of Agricultural Economists, vol. 6(2), pages 1-14, September.
    2. James E. Smith & Robert L. Winkler, 2006. "The Optimizer's Curse: Skepticism and Postdecision Surprise in Decision Analysis," Management Science, INFORMS, vol. 52(3), pages 311-322, March.

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