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Effects of feedback and complexity on repeated decisions from description

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  • Lejarraga, Tomás
  • Gonzalez, Cleotilde

Abstract

Recent evidence from research in risky choice shows that decisions from experience differ significantly from decisions from description, particularly when problems include a small-probability event and when samples from experience are small. Little is known, however, about the cognitive processes behind repeated decisions where both descriptive and experiential information are available for the decision maker. While previous findings suggest that feedback makes choices “deviate” from the predictions of prospect theory (Jessup, Bishara, & Busemeyer, 2008), we find a stronger effect: Our results suggest that information from description is neglected in the presence of feedback. Moreover, we find that in the presence of feedback, descriptions are overlooked irrespective of the level of complexity of the decision scenario. We show that an instance-based learning model and a reinforcement learning model account for the observed decisions by solely relying on observed outcomes. We discuss our findings in the context of organizational behavior.

Suggested Citation

  • Lejarraga, Tomás & Gonzalez, Cleotilde, 2011. "Effects of feedback and complexity on repeated decisions from description," Organizational Behavior and Human Decision Processes, Elsevier, vol. 116(2), pages 286-295.
    • Handle: RePEc:eee:jobhdp:v:116:y:2011:i:2:p:286-295
    DOI: 10.1016/j.obhdp.2011.05.001
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    References listed on IDEAS

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    1. Barron, Greg & Leider, Stephen & Stack, Jennifer, 2008. "The effect of safe experience on a warnings' impact: Sex, drugs, and rock-n-roll," Organizational Behavior and Human Decision Processes, Elsevier, vol. 106(2), pages 125-142, July.
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    4. 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..
    5. Robin Hogarth & Emre Soyer, 2010. "Experiencing simulated outcomes," Economics Working Papers 1224, Department of Economics and Business, Universitat Pompeu Fabra.
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    Citations

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    Cited by:

    1. Eyal Ert & Stefan Trautmann, 2014. "Sampling experience reverses preferences for ambiguity," Journal of Risk and Uncertainty, Springer, vol. 49(1), pages 31-42, August.
    2. Lejarraga, Tomás & Lejarraga, José, 2020. "Confidence and the description–experience distinction," Organizational Behavior and Human Decision Processes, Elsevier, vol. 161(C), pages 201-212.
    3. repec:cup:judgdm:v:16:y:2021:i:2:p:267-289 is not listed on IDEAS
    4. Lukas, Moritz & Nöth, Markus, 2021. "Interest rate fixation periods and reference points," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 94(C).
    5. Kim, Younjun, 2015. "Essays on firm location decisions, regional development and choices under risk," ISU General Staff Papers 201501010800005579, Iowa State University, Department of Economics.
    6. Schurr, Amos & Rodensky, Dotan & Erev, Ido, 2014. "The effect of unpleasant experiences on evaluation and behavior," Journal of Economic Behavior & Organization, Elsevier, vol. 106(C), pages 1-9.
    7. Hogarth, Robin M. & Soyer, Emre, 2015. "Communicating forecasts: The simplicity of simulated experience," Journal of Business Research, Elsevier, vol. 68(8), pages 1800-1809.
    8. Tomás Lejarraga & Johannes Müller-Trede, 2017. "When Experience Meets Description: How Dyads Integrate Experiential and Descriptive Information in Risky Decisions," Management Science, INFORMS, vol. 63(6), pages 1953-1971, June.
    9. Pindard-Lejarraga, Maud & Lejarraga, José, 2024. "Information source and entrepreneurial performance expectations: Experience-based versus description-based opportunity evaluations," Journal of Business Research, Elsevier, vol. 172(C).
    10. Shereen J. Chaudhry & Michael Hand & Howard Kunreuther, 2020. "Broad bracketing for low probability events," Journal of Risk and Uncertainty, Springer, vol. 61(3), pages 211-244, December.
    11. Ori Plonsky & Yefim Roth & Ido Erev, 2021. "Underweighting of rare events in social interactions and its implications to the design of voluntary health applications," Judgment and Decision Making, Society for Judgment and Decision Making, vol. 16(2), pages 267-289, March.
    12. Camilleri, Adrian R. & Newell, Ben R., 2019. "Better calibration when predicting from experience (rather than description)," Organizational Behavior and Human Decision Processes, Elsevier, vol. 150(C), pages 62-82.
    13. Davide Marchiori & Sibilla Di Guida & Ido Erev, 2013. "Noisy retrievers and the four-fold reaction to rare events," Working Papers 3, Venice School of Management - Department of Management, Università Ca' Foscari Venezia.

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