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Decision Uncertainty from Strict Preferences in Sequential Search Scenarios with Multiple Criteria

Author

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  • Debora Di Caprio

    (Department of Economics and Management, University of Trento, 38122 Trento, Italy)

  • Yolanda Durán Durán

    (Departamento de Economía Financiera y Actuarial y Estadística, Universidad Complutense de Madrid, 28003 Madrid, Spain)

  • Francisco Javier Santos-Arteaga

    (Departamento de Economía Financiera y Actuarial y Estadística, Universidad Complutense de Madrid, 28003 Madrid, Spain)

Abstract

The standard expected utility model applied by economists and decision scientists assumes both that decision makers (DMs) are rational and that their information retrieval behavior and choices are determined by the observed and potential values of the multiple characteristics defining the alternatives. In this regard, if DMs can formalize the information acquisition structures determined by the main postulates of expected utility theory, they should also be able to perform standard operations regarding the potential combinatorial outcomes that may be obtained when evaluating the alternatives. We define an information retrieval scenario where DMs account for the different combinatorial possibilities arising among the realizations of the characteristics defining the alternatives before evaluating them. We demonstrate the indifference that arises among risk-neutral DMs endowed with standard expected utilities within sequential information acquisition environments such as those defined by online search engines. We also illustrate the reticence of DMs to acquire information on new alternatives when increasing their aversion to risk or modifying the relative importance assigned to the different characteristics defining the alternatives. The main strategic consequences that follow from the enhanced information retrieval scenario proposed are also analyzed.

Suggested Citation

  • Debora Di Caprio & Yolanda Durán Durán & Francisco Javier Santos-Arteaga, 2025. "Decision Uncertainty from Strict Preferences in Sequential Search Scenarios with Multiple Criteria," Mathematics, MDPI, vol. 13(9), pages 1-13, April.
  • Handle: RePEc:gam:jmathe:v:13:y:2025:i:9:p:1368-:d:1640013
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    References listed on IDEAS

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    1. Gu, Chris & Wang, Yike, 2022. "Consumer online search with partially revealed information," LSE Research Online Documents on Economics 109871, London School of Economics and Political Science, LSE Library.
    2. Zan Zhang & Guofang Nan & Minqiang Li & Yong Tan, 2022. "Competitive Entry of Information Goods Under Quality Uncertainty," Management Science, INFORMS, vol. 68(4), pages 2869-2888, April.
    3. Bearden, J. Neil & Connolly, Terry, 2007. "Multi-attribute sequential search," Organizational Behavior and Human Decision Processes, Elsevier, vol. 103(1), pages 147-158, May.
    4. Chris Gu & Yike Wang, 2022. "Consumer Online Search with Partially Revealed Information," Management Science, INFORMS, vol. 68(6), pages 4215-4235, June.
    5. Pedro M. Gardete & Megan Hunter, 2024. "Multiattribute Search: Empirical Evidence and Information Design," Marketing Science, INFORMS, vol. 43(5), pages 1052-1080, September.
    Full references (including those not matched with items on IDEAS)

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