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An Overview of Methods for Applied Decision Analysis

Author

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  • Craig W. Kirkwood

    (Department of Decision and Information Systems, Arizona State University, Tempe, Arizona 85287-4206)

Abstract

Decision analysis is not just trees anymore. Influence diagrams improve communication among managers and analysts about key dependencies in a decision under uncertainty. Algebraic formulation methods allow compact representation of decision models that are too complex to handle with decision trees. Utility functions model attitude toward risk taking and trade-offs among conflicting objectives in a way that is both practical and conceptually sound. Behavioral research has shown how to correctly elicit judgmental information about uncertainties, and accurate approximations are available to summarize these judgments. Recently developed computer tools use these approaches to model real-world decisions efficiently.

Suggested Citation

  • Craig W. Kirkwood, 1992. "An Overview of Methods for Applied Decision Analysis," Interfaces, INFORMS, vol. 22(6), pages 28-39, December.
  • Handle: RePEc:inm:orinte:v:22:y:1992:i:6:p:28-39
    DOI: 10.1287/inte.22.6.28
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    Citations

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    Cited by:

    1. Donald L. Keefer & Craig W. Kirkwood & James L. Corner, 2004. "Perspective on Decision Analysis Applications, 1990–2001," Decision Analysis, INFORMS, vol. 1(1), pages 4-22, March.
    2. Guo, Rui & Shenoy, Prakash P., 1996. "A note on Kirkwood's algebraic method for decision problems," European Journal of Operational Research, Elsevier, vol. 93(3), pages 628-638, September.

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