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Experimental evidence on case-based decision theory

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  • Wolfgang Ossadnik
  • Dirk Wilmsmann
  • Benedikt Niemann

Abstract

This paper starts out from the proposition that case-based decision theory (CBDT) is an appropriate tool to explain human decision behavior in situations of structural ignorance. Although the developers of CBDT suggest its reality adequacy, CBDT has not yet been tested empirically very often, especially not in repetitive decision situations. Therefore, our main objective is to analyse the decision behavior of subjects in a repeated-choice experiment by comparing the explanation power of CBDT to reinforcement learning and to classical decision criteria under uncertainty namely maximin, maximax, and pessimism-optimism. Our findings substantiate a predominant significantly higher validity of CBDT compared to the classical criteria and to reinforcement learning. For this reason, the experimental results confirm the suggested reality adequacy of CBDT in repetitive decision situations of structural ignorance. Copyright Springer Science+Business Media New York 2013

Suggested Citation

  • Wolfgang Ossadnik & Dirk Wilmsmann & Benedikt Niemann, 2013. "Experimental evidence on case-based decision theory," Theory and Decision, Springer, vol. 75(2), pages 211-232, August.
    • Handle: RePEc:kap:theord:v:75:y:2013:i:2:p:211-232
    DOI: 10.1007/s11238-012-9333-4
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    1. Abebe Rorissa, 2007. "Relationships between perceived features and similarity of images: A test of Tversky's contrast model," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 58(10), pages 1401-1418, August.
    2. Gilboa, Itzhak & Schmeidler, David, 1996. "Case-Based Optimization," Games and Economic Behavior, Elsevier, vol. 15(1), pages 1-26, July.
    3. Roth, Alvin E. & Erev, Ido, 1995. "Learning in extensive-form games: Experimental data and simple dynamic models in the intermediate term," Games and Economic Behavior, Elsevier, vol. 8(1), pages 164-212.
    4. Itzhak Gilboa & David Schmeidler, 1995. "Case-Based Decision Theory," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 110(3), pages 605-639.
    5. Gilboa,Itzhak & Schmeidler,David, 2001. "A Theory of Case-Based Decisions," Cambridge Books, Cambridge University Press, number 9780521802345, January.
    6. Reb, Jochen & Connolly, Terry, 2009. "Myopic regret avoidance: Feedback avoidance and learning in repeated decision making," Organizational Behavior and Human Decision Processes, Elsevier, vol. 109(2), pages 182-189, July.
    7. Itzhak Gilboa & Offer Lieberman & David Schmeidler, 2012. "Empirical Similarity," World Scientific Book Chapters, in: Case-Based Predictions An Axiomatic Approach to Prediction, Classification and Statistical Learning, chapter 9, pages 211-243, World Scientific Publishing Co. Pte. Ltd..
    8. Matsui, Akihiko, 2000. "Expected utility and case-based reasoning," Mathematical Social Sciences, Elsevier, vol. 39(1), pages 1-12, January.
    9. Antoine Billot & Itzhak Gilboa & David Schmeidler, 2012. "Axiomatization of an Exponential Similarity Function," World Scientific Book Chapters, in: Case-Based Predictions An Axiomatic Approach to Prediction, Classification and Statistical Learning, chapter 10, pages 245-257, World Scientific Publishing Co. Pte. Ltd..
    10. Erev, Ido & Roth, Alvin E, 1998. "Predicting How People Play Games: Reinforcement Learning in Experimental Games with Unique, Mixed Strategy Equilibria," American Economic Review, American Economic Association, vol. 88(4), pages 848-881, September.
    11. Gilboa, Itzhak & Schmeidler, David, 1997. "Cumulative Utility and Consumer Theory," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 38(4), pages 737-761, November.
    12. 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.
    13. Svenson, Ola, 1996. "Decision Making and the Search for Fundamental Psychological Regularities: What Can Be Learned from a Process Perspective?," Organizational Behavior and Human Decision Processes, Elsevier, vol. 65(3), pages 252-267, March.
    14. Daniel Ellsberg, 1961. "Risk, Ambiguity, and the Savage Axioms," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 75(4), pages 643-669.
    15. Reb, Jochen & Connolly, Terry, 2009. "Erratum to "Myopic regret avoidance: Feedback avoidance and learning in repeated decision making" [Organizational Behavior and Human Decision Processes 109 (2009) 182-189]," Organizational Behavior and Human Decision Processes, Elsevier, vol. 110(1), pages 65-65, September.
    16. Blonski, Matthias, 1999. "Social learning with case-based decisions," Journal of Economic Behavior & Organization, Elsevier, vol. 38(1), pages 59-77, January.
    17. Heath, Chip & Tversky, Amos, 1991. "Preference and Belief: Ambiguity and Competence in Choice under Uncertainty," Journal of Risk and Uncertainty, Springer, vol. 4(1), pages 5-28, January.
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    3. Benjamin Radoc & Robert Sugden & Theodore L. Turocy, 2019. "Correlation neglect and case-based decisions," Journal of Risk and Uncertainty, Springer, vol. 59(1), pages 23-49, August.
    4. Han Bleichrodt & Martin Filko & Amit Kothiyal & Peter P. Wakker, 2017. "Making Case-Based Decision Theory Directly Observable," American Economic Journal: Microeconomics, American Economic Association, vol. 9(1), pages 123-151, February.
    5. Ilke Aydogan & Yu Gao, 2020. "Experience and rationality under risk: re-examining the impact of sampling experience," Experimental Economics, Springer;Economic Science Association, vol. 23(4), pages 1100-1128, December.
    6. Benjamin Radoc, 2020. "Bandit with similarity information," Department of Economics, Ateneo de Manila University, Working Paper Series 202002, Department of Economics, Ateneo de Manila University.

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