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Consumer Online Search with Partially Revealed Information

Author

Listed:
  • Chris Gu

    (Scheller College of Business, Georgia Institute of Technology, Atlanta, Georgia 30308)

  • Yike Wang

    (Department of Economics, London School of Economics and Political Science, London WC2A 2AE, United Kingdom)

Abstract

Modern-day search platforms generally have two layers of information presentation. The outer layer displays the collection of search results with attributes selected by platforms, and consumers click on a product to reveal all its attributes in the inner layer. The information revealed in the outer layer affects the search costs and the probability of finding a match. To address the managerial question of optimal information layout, we create an information complexity measure of the outer layer, namely orderedness entropy, and study the consumer search process for information at the expense of time and cognitive costs. We first conduct online random experiments to show that consumers respond to and actively reduce cognitive cost for which our information complexity measure provides a representation. Then, using a unique and rich panel tracking consumer search behaviors at a large online travel agency (OTA), we specify a novel sequential search model that jointly describes the refinement search and product clicking decisions. We find that cognitive cost is a major component of search cost, while loading time cost has a much smaller share. By varying the information revealed in the outer layer, we propose information layouts that Pareto-improve both revenue and consumer welfare for our OTA.

Suggested Citation

  • Chris Gu & Yike Wang, 2022. "Consumer Online Search with Partially Revealed Information," Management Science, INFORMS, vol. 68(6), pages 4215-4235, June.
    • Handle: RePEc:inm:ormnsc:v:68:y:2022:i:6:p:4215-4235
    DOI: 10.1287/mnsc.2021.4104
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    References listed on IDEAS

    as
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    Cited by:

    1. Li, Baoku & Nan, Yafeng & Yao, Ruoxi, 2024. "The inverted U-shaped relationship between information entropy of keyword combinations and sales of digital products: Evidence from China Tmall," Journal of Retailing and Consumer Services, Elsevier, vol. 79(C).
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    3. Giovanni Compiani & Gregory Lewis & Sida Peng & Peichun Wang, 2024. "Online Search and Optimal Product Rankings: An Empirical Framework," Marketing Science, INFORMS, vol. 43(3), pages 615-636, May.

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