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Asymmetric Effects of Favorable and Unfavorable Information on Decision Making Under Ambiguity

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  • Alexander Peysakhovich

    (Program for Evolutionary Dynamics, Harvard University, Cambridge, Massachusetts 02138)

  • Uma R. Karmarkar

    (Harvard Business School, Boston, Massachusetts 02163)

Abstract

Most daily decisions involve uncertainty about outcome probabilities arising from incomplete knowledge, i.e., ambiguity. We explore how the addition of partial information affects these types of choices using theoretical and empirical methods. Our experiments in both gain and loss domains demonstrate that when such information supports a favorable outcome, it strongly increases valuation of an ambiguous financial prospect. However, when information supports an unfavorable outcome, it has significantly less impact. We find that two mechanisms drive this asymmetry. First, unfavorable information decreases estimates of a good outcome occurring but also reduces aversive uncertainty. These factors act in opposition, minimizing the effects of unfavorable information. Second, when information can be subjectively interpreted, unfavorable information is less likely to be integrated into evaluations. Our findings reveal mechanisms not captured by traditional models of decision making under uncertainty and highlight the importance of increasing the salience of unfavorable information in uncertain contexts to promote unbiased decision making.Data, as supplemental material, are available at http://dx.doi.org/10.1287/mnsc.2015.2233 . This paper was accepted by Teck-Hua Ho, behavioral economics .

Suggested Citation

  • Alexander Peysakhovich & Uma R. Karmarkar, 2016. "Asymmetric Effects of Favorable and Unfavorable Information on Decision Making Under Ambiguity," Management Science, INFORMS, vol. 62(8), pages 2163-2178, August.
  • Handle: RePEc:inm:ormnsc:v:62:y:2016:i:8:p:2163-2178
    DOI: 10.1287/mnsc.2015.2233
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    Cited by:

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    2. Surajeet Chakravarty & Todd R. Kaplan & Navonil Mustafee, 2020. "Altering Wait Time Information to Reduce A&E Overcrowding," Discussion Papers 2003, University of Exeter, Department of Economics.
    3. Scott Duke Kominers & Xiaosheng Mu & Alexander Peysakhovich, 2019. "Paying for Attention: The Impact of Information Processing Costs on Bayesian Inference," Working Papers 2019-31, Princeton University. Economics Department..
    4. Balietti, Anca & Budjan, Angelika & Eymess, Tillmann & Soldà, Alice, 2023. "Strategic Ignorance and Perceived Control," Working Papers 0730, University of Heidelberg, Department of Economics.
    5. Ryan Oprea & Sevgi Yuksel, 2022. "Social Exchange of Motivated Beliefs," Journal of the European Economic Association, European Economic Association, vol. 20(2), pages 667-699.
    6. Stéphane Couture & Stéphane Lemarié & Sabrina Teyssier & Pascal Toquebeuf, 2024. "The value of information under ambiguity: a theoretical and experimental study on pest management in agriculture," Theory and Decision, Springer, vol. 96(1), pages 19-47, February.
    7. Richard J. Arend, 2020. "Strategic decision-making under ambiguity: a new problem space and a proposed optimization approach," Business Research, Springer;German Academic Association for Business Research, vol. 13(3), pages 1231-1251, November.
    8. Li, Jiangyan & Fairley, Kim & Fenneman, Achiel, 2024. "Does it matter how we produce ambiguity in experiments?," MPRA Paper 122336, University Library of Munich, Germany.
    9. Aljoscha Minnich & Hauke Roggenkamp & Andreas Lange, 2023. "Ambiguity Attitudes and Surprises: Experimental Evidence on Communicating New Information within a Large Population Sample," CESifo Working Paper Series 10783, CESifo.

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