Crowdsourcing Market Information from Competitors

Joann F. de Zegher,Irene Lo

Published 2020 in Social Science Research Network

ABSTRACT

Market price information is not widely available to many firms in the developing world. In these settings, information sharing agreements among competing firms can create significant benefits. However, such agreements may be difficult to implement, because a firm might fear that sharing its information will benefit competitors, allowing them to steal its market share. We show that an appropriately designed information-sharing platform can disclose partial information that will benefit all firms. By eliminating business stealing concerns, our information disclosure policy creates a Pareto improvement and is implementable if the information shared by the platform is sufficiently valuable. The model requires minimal assumptions and can account for general market dynamics. The interpretability of our results allows us to propose a heuristic for use in practice by an Indonesia-based information-sharing platform we collaborate with.

PUBLICATION RECORD

  • Publication year

    2020

  • Venue

    Social Science Research Network

  • Publication date

    2020-02-13

  • Fields of study

    Business, Economics, Computer Science

  • Identifiers
  • External record

    Open on Semantic Scholar

  • Source metadata

    Semantic Scholar

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