IDEAS home Printed from
   My bibliography  Save this article

Approximating Risk Aversion in Decision Analysis Applications


  • Craig W. Kirkwood

    () (Department of Supply Chain Management, Arizona State University Tempe, Arizona 85287-4706)


This paper investigates the impact of risk aversion in decision analyses under uncertainty with a single evaluation measure and presents a simple procedure for approximately addressing risk aversion in a way that is defensible for many decisions. Specifically, a simulation study is presented that leads to guidelines for determining when an expected utility analysis should be conducted for a decision, rather than simply an expected value analysis, and what form of utility function should be used for this expected utility analysis. The simulation study shows that a sensitivity analysis using an exponential utility function should be conducted for most decision analyses, but that this sensitivity analysis can often establish, without requiring utility information from the decision maker , that no further utility analysis is required. In addition, when further utility analysis is required, the simulation study shows that this can be done in a simple way using an exponential utility function that will be accurate for many decision analyses. However, in situations where there is equal or greater downside risk than upside potential, a more detailed study of the decision maker's utility function may be necessary.

Suggested Citation

  • Craig W. Kirkwood, 2004. "Approximating Risk Aversion in Decision Analysis Applications," Decision Analysis, INFORMS, vol. 1(1), pages 51-67, March.
  • Handle: RePEc:inm:ordeca:v:1:y:2004:i:1:p:51-67
    DOI: 10.1287/deca.1030.0007

    Download full text from publisher

    File URL:
    Download Restriction: no

    References listed on IDEAS

    1. Peter H. Farquhar & Yutaka Nakamura, 1987. "Constant Exchange Risk Properties," Operations Research, INFORMS, vol. 35(2), pages 206-214, April.
    2. Patrick L. Brockett & Linda L. Golden, 1987. "A Class of Utility Functions Containing all the Common Utility Functions," Management Science, INFORMS, vol. 33(8), pages 955-964, August.
    3. Donald L. Keefer, 1991. "Resource Allocation Models with Risk Aversion and Probabilistic Dependence: Offshore Oil and Gas Bidding," Management Science, INFORMS, vol. 37(4), pages 377-395, April.
    4. David E. Bell, 1988. "One-Switch Utility Functions and a Measure of Risk," Management Science, INFORMS, vol. 34(12), pages 1416-1424, December.
    5. David E. Bell, 1995. "A Contextual Uncertainty Condition for Behavior Under Risk," Management Science, INFORMS, vol. 41(7), pages 1145-1150, July.
    6. Dan J. Laughhunn & John W. Payne & Roy Crum, 1980. "Managerial Risk Preferences for Below-Target Returns," Management Science, INFORMS, vol. 26(12), pages 1238-1249, December.
    7. Ronald A. Howard, 1988. "Decision Analysis: Practice and Promise," Management Science, INFORMS, vol. 34(6), pages 679-695, June.
    8. Jianmin Jia & James S. Dyer, 1996. "A Standard Measure of Risk and Risk-Value Models," Management Science, INFORMS, vol. 42(12), pages 1691-1705, December.
    9. Dana R. Clyman & Michael R. Walls & James S. Dyer, 1999. "Too Much of a Good Thing?," Operations Research, INFORMS, vol. 47(6), pages 957-965, December.
    10. Markowitz, Harry M, 1991. "Foundations of Portfolio Theory," Journal of Finance, American Finance Association, vol. 46(2), pages 469-477, June.
    11. James L. Corner & Craig W. Kirkwood, 1991. "Decision Analysis Applications in the Operations Research Literature, 1970–1989," Operations Research, INFORMS, vol. 39(2), pages 206-219, April.
    12. Peter H. Farquhar & Yutaka Nakamura, 1988. "Utility assessment procedures for polynomial‐exponential functions," Naval Research Logistics (NRL), John Wiley & Sons, vol. 35(6), pages 597-613, December.
    13. Charles M. Harvey, 1990. "Structured Prescriptive Models of Risk Attitudes," Management Science, INFORMS, vol. 36(12), pages 1479-1501, December.
    Full references (including those not matched with items on IDEAS)


    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.

    Cited by:

    1. Sascha Hokamp & Michael Pickhardt, 2010. "Income Tax Evasion in a Society of Heterogeneous Agents - Evidence from an Agent-based Model," International Economic Journal, Taylor & Francis Journals, vol. 24(4), pages 541-553.
    2. J. Eric Bickel, 2008. "The Relationship Between Perfect and Imperfect Information in a Two-Action Risk-Sensitive Problem," Decision Analysis, INFORMS, vol. 5(3), pages 116-128, September.
    3. Xin Chen & Melvyn Sim & David Simchi-Levi & Peng Sun, 2007. "Risk Aversion in Inventory Management," Operations Research, INFORMS, vol. 55(5), pages 828-842, October.
    4. L. Robin Keller & Ali Abbas & J. Eric Bickel & Vicki M. Bier & David V. Budescu & John C. Butler & Enrico Diecidue & Robin L. Dillon-Merrill & Raimo P. Hämäläinen & Kenneth C. Lichtendahl & Jason R. W, 2012. "From the Editors ---Brainstorming, Multiplicative Utilities, Partial Information on Probabilities or Outcomes, and Regulatory Focus," Decision Analysis, INFORMS, vol. 9(4), pages 297-302, December.
    5. Steven A. Lippman & Kevin F. McCardle, 2012. "Embedded Nash Bargaining: Risk Aversion and Impatience," Decision Analysis, INFORMS, vol. 9(1), pages 31-40, March.
    6. J. Eric Bickel, 2007. "Some Comparisons among Quadratic, Spherical, and Logarithmic Scoring Rules," Decision Analysis, INFORMS, vol. 4(2), pages 49-65, June.
    7. Doumpos, Michael & Hasan, Iftekhar & Pasiouras, Fotios, 2017. "Bank overall financial strength: Islamic versus conventional banks," Economic Modelling, Elsevier, vol. 64(C), pages 513-523.
    8. L. Robin Keller, 2008. "From the Editor..," Decision Analysis, INFORMS, vol. 5(1), pages 1-4, March.
    9. Philippe Delquié, 2008. "Interpretation of the Risk Tolerance Coefficient in Terms of Maximum Acceptable Loss," Decision Analysis, INFORMS, vol. 5(1), pages 5-9, March.
    10. L. Robin Keller, 2010. "From the Editor..," Decision Analysis, INFORMS, vol. 7(3), pages 235-237, September.
    11. Schosser, Josef, 2019. "Consistency between principal and agent with differing time horizons: Computing incentives under risk," European Journal of Operational Research, Elsevier, vol. 277(3), pages 1113-1123.
    12. Philippe Delquié, 2008. "The Value of Information and Intensity of Preference," Decision Analysis, INFORMS, vol. 5(3), pages 129-139, September.
    13. Ender Su & John Bilson, 2011. "Trading asymmetric trend and volatility by leverage trend GARCH in Taiwan stock index," Applied Economics, Taylor & Francis Journals, vol. 43(26), pages 3891-3905.
    14. Michael Doumpos & Chrysovalantis Gaganis & Fotios Pasiouras, 2016. "Bank Diversification and Overall Financial Strength: International Evidence," Working Papers 1602, University of Crete, Department of Economics.


    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:inm:ordeca:v:1:y:2004:i:1:p:51-67. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Matthew Walls). General contact details of provider: .

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.