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Consumer Search Costs and Preferences on the Internet

Author

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  • Grégory Jolivet
  • Hélène Turon

Abstract

We conduct an empirical analysis of consumer preferences and search costs on an Internet platform. Using data from a major French platform (PriceMinister), we show descriptive evidence of substantial price dispersion among adverts for the same product, of consumers often not choosing the cheapest advert and sometimes choosing an advert dominated in price and non-price characteristics by another available advert. We consider a sequential search model where consumers sample adverts in an endogenous order based on their preferences and search costs. We show that the optimal search-and-purchase strategy can be characterized by a set of inequalities which can feasibly be tested on transaction and advert data. This allows us to estimate, for each transaction, a set of preference and search cost parameter values, thus allowing for flexible consumer heterogeneity in preferences and search costs. The estimated model can then describe a wide range of consumer search and purchase behaviours. We find that the model can explain almost all transactions in the data and requires non-zero preferences and search costs for at least 50% and 22% (respectively) of observations. We also find evidence of heterogeneous and sometimes substantial search costs.

Suggested Citation

  • Grégory Jolivet & Hélène Turon, 2019. "Consumer Search Costs and Preferences on the Internet," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 86(3), pages 1258-1300.
  • Handle: RePEc:oup:restud:v:86:y:2019:i:3:p:1258-1300.
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    File URL: http://hdl.handle.net/10.1093/restud/rdy023
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    Cited by:

    1. Zhu, Qin & Zhou, Xiangxiang, 2025. "Digital trade and firm ESG performance: The perspective of finance development," Research in International Business and Finance, Elsevier, vol. 77(PA).
    2. Lindgren, Charlie & Daunfeldt, Sven-Olov & Rudholm, Niklas, 2021. "Pricing In Retail Markets With Low Search Costs: Evidence From A Price Comparison Website," HFI Working Papers 18, Institute of Retail Economics (Handelns Forskningsinstitut).
    3. Greminger, Rafael, 2019. "Optimal Search and Awareness Expansion," Other publications TiSEM ac47e6ff-42a4-4d70-addd-6, Tilburg University, School of Economics and Management.
    4. Meiling Li & Lijie Zhang & Zhuangzhuang Zhang, 2023. "Impact of Digital Economy on Inter-Regional Trade: An Empirical Analysis in China," Sustainability, MDPI, vol. 15(15), pages 1-22, August.
    5. Gibbard, Peter, 2023. "Search with two stages of information acquisition: A structural econometric model of online purchases," Information Economics and Policy, Elsevier, vol. 65(C).
    6. Rafael P. Greminger, 2019. "Optimal Search and Discovery," Papers 1911.07773, arXiv.org, revised Feb 2022.
    7. Banfi, Stefano & Choi, Sekyu & Villena-Roldán, Benjamín, 2022. "Sorting on-line and on-time," European Economic Review, Elsevier, vol. 146(C).
    8. Eugenia Andreasen & Patricio Valenzuela, 2018. "Investment Opportunities and Corporate Credit Risk," Documentos de Trabajo 336, Centro de Economía Aplicada, Universidad de Chile.
    9. Groh, Carl-Christian, 2023. "Search, Data, and Market Power," VfS Annual Conference 2023 (Regensburg): Growth and the "sociale Frage" 277701, Verein für Socialpolitik / German Economic Association.
    10. Hu, Cui & Li, Ben G., 2025. "Google and China's Trade," MPRA Paper 124177, University Library of Munich, Germany.
    11. Carl-Christian Groh, & Jonas von Wangenheim, 2024. "Pigou Meets Wolinsky: Search, Price Discrimination, and Consumer Sophistication," CRC TR 224 Discussion Paper Series crctr224_2024_527, University of Bonn and University of Mannheim, Germany.
    12. Rafael P. Greminger, 2022. "Optimal Search and Discovery," Management Science, INFORMS, vol. 68(5), pages 3904-3924, May.
    13. Daehyeon Park & Doojin Ryu, 2023. "E‐commerce retail and reverse factoring: A newsvendor approach," Managerial and Decision Economics, John Wiley & Sons, Ltd., vol. 44(1), pages 416-423, January.
    14. Greminger, Rafael, 2019. "Optimal Search and Awareness Expansion," Discussion Paper 2019-034, Tilburg University, Center for Economic Research.

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    Keywords

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    JEL classification:

    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • D12 - Microeconomics - - Household Behavior - - - Consumer Economics: Empirical Analysis
    • D81 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Criteria for Decision-Making under Risk and Uncertainty
    • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness
    • L13 - Industrial Organization - - Market Structure, Firm Strategy, and Market Performance - - - Oligopoly and Other Imperfect Markets

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