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Optimal Discoverability on Platforms

Author

Listed:
  • Andrei Hagiu

    (Boston University Questrom School of Business, Boston, Massachusetts 02215)

  • Julian Wright

    (Department of Economics, National University of Singapore, Singapore 117568)

Abstract

Choosing how easy to make it for buyers to discover new sellers is a key design decision for platforms. On one hand, enabling more discoverability generates more transactions and can be more attractive for sellers because they anticipate being discovered by new buyers. On the other hand, discoverability can make sellers more reluctant to participate because they anticipate their existing buyers will discover and purchase from other sellers. We model this fundamental trade-off and study how a platform’s optimal level of discoverability depends on various factors: the degree of substitutability between the sellers’ products; the standalone value of the platform’s tools; the size of the platform’s installed base of buyers; the nature of the platform’s fees, including its ability to charge differential fees depending on whether a transaction is with a seller’s existing buyers or not; the number of sellers; and asymmetries between sellers’ sizes.

Suggested Citation

  • Andrei Hagiu & Julian Wright, 2024. "Optimal Discoverability on Platforms," Management Science, INFORMS, vol. 70(11), pages 7770-7790, November.
    • Handle: RePEc:inm:ormnsc:v:70:y:2024:i:11:p:7770-7790
    DOI: 10.1287/mnsc.2023.02362
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