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Explaining heterogeneity in utility functions by individual differences in preferred decision modes

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  • Schunk, Daniel
  • Betsch, Cornelia

Abstract

The curvature of utility functions varies between people. We suggest that there exists a relationship between the mode in which a person usually makes a decision and the curvature of the individual utility function. In a deliberate decision mode, a decision-maker tends to have a nearly linear utility function. In an intuitive decision mode, the utility function is more curved. In our experiment the utility function is assessed with a lottery-based utility elicitation method and related to a measure that assesses the habitual preference for intuition and deliberation (Betsch, submitted). Results confirm that for people that habitually use the deliberate decision mode, the utility function is more linear than for people that habitually use the intuitive decision mode. The finding and its implications for the research on individual decision behavior in economics and psychology are discussed.

Suggested Citation

  • Schunk, Daniel & Betsch, Cornelia, 2004. "Explaining heterogeneity in utility functions by individual differences in preferred decision modes," Papers 04-26, Sonderforschungsbreich 504.
    • Handle: RePEc:mnh:spaper:2718
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    References listed on IDEAS

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    1. Mano, Haim, 1994. "Risk-Taking, Framing Effects, and Affect," Organizational Behavior and Human Decision Processes, Elsevier, vol. 57(1), pages 38-58, January.
    2. Tversky, Amos & Kahneman, Daniel, 1992. "Advances in Prospect Theory: Cumulative Representation of Uncertainty," Journal of Risk and Uncertainty, Springer, vol. 5(4), pages 297-323, October.
    3. Schunk, Daniel & Winter, Joachim, 2009. "The relationship between risk attitudes and heuristics in search tasks: A laboratory experiment," Journal of Economic Behavior & Organization, Elsevier, vol. 71(2), pages 347-360, August.
    4. Peter Wakker & Daniel Deneffe, 1996. "Eliciting von Neumann-Morgenstern Utilities When Probabilities Are Distorted or Unknown," Management Science, INFORMS, vol. 42(8), pages 1131-1150, August.
    5. Daniel Kahneman & Amos Tversky, 2013. "Prospect Theory: An Analysis of Decision Under Risk," World Scientific Book Chapters, in: Leonard C MacLean & William T Ziemba (ed.), HANDBOOK OF THE FUNDAMENTALS OF FINANCIAL DECISION MAKING Part I, chapter 6, pages 99-127, World Scientific Publishing Co. Pte. Ltd..
    6. Chris Starmer, 2000. "Developments in Non-expected Utility Theory: The Hunt for a Descriptive Theory of Choice under Risk," Journal of Economic Literature, American Economic Association, vol. 38(2), pages 332-382, June.
    7. Peter H. Farquhar, 1984. "State of the Art---Utility Assessment Methods," Management Science, INFORMS, vol. 30(11), pages 1283-1300, November.
    8. Wright, William F. & Bower, Gordon H., 1992. "Mood effects on subjective probability assessment," Organizational Behavior and Human Decision Processes, Elsevier, vol. 52(2), pages 276-291, July.
    9. Camerer, Colin F, 1989. "An Experimental Test of Several Generalized Utility Theories," Journal of Risk and Uncertainty, Springer, vol. 2(1), pages 61-104, April.
    10. Mohammed Abdellaoui, 2000. "Parameter-Free Elicitation of Utility and Probability Weighting Functions," Management Science, INFORMS, vol. 46(11), pages 1497-1512, November.
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    Cited by:

    1. Lothar Essig, 2005. "Household Saving in Germany: Results from SAVE 2001-2003," MEA discussion paper series 05083, Munich Center for the Economics of Aging (MEA) at the Max Planck Institute for Social Law and Social Policy.
    2. Essig, Lothar, 2004. "Precautionary saving and old-age provisions: Do subjective saving motives measures work?," Sonderforschungsbereich 504 Publications 05-22, Sonderforschungsbereich 504, Universität Mannheim;Sonderforschungsbereich 504, University of Mannheim.
    3. Rahmani, Djamel & Loureiro, Maria & Escobar, Cristina & Gil, José M., 2021. "How Emotions Affect Choices: The Case of Wine," 2021 Conference, August 17-31, 2021, Virtual 314943, International Association of Agricultural Economists.
    4. Essig, Lothar, 2005. "Household saving in Germany : results from SAVE 2001 - 2003," Papers 05-23, Sonderforschungsbreich 504.
    5. Lothar Essig, 2005. "Precautionary saving and old-age provisions: Do subjective saving motive measures work?," MEA discussion paper series 05084, Munich Center for the Economics of Aging (MEA) at the Max Planck Institute for Social Law and Social Policy.
    6. Essig, Lothar, 2005. "Precautionary saving and old-age provisions : do subjective saving motives measures work?," Papers 05-22, Sonderforschungsbreich 504.

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    More about this item

    Keywords

    Utility function elicitation ; risky decisions ; intuition ; value function ; individual differences;
    All these keywords.

    JEL classification:

    • D81 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Criteria for Decision-Making under Risk and Uncertainty
    • C91 - Mathematical and Quantitative Methods - - Design of Experiments - - - Laboratory, Individual Behavior

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