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Information Sale and Competition

Author

Listed:
  • Kostas Bimpikis

    (Graduate School of Business, Stanford University, Stanford, California 94305)

  • Davide Crapis

    (Lyft, San Francisco, California 94107)

  • Alireza Tahbaz-Salehi

    (Kellogg School of Management, Northwestern University, Evanston, Illinois 60208)

Abstract

This paper studies the strategic interaction between a monopolistic seller of an information product and a set of potential buyers that compete in a downstream market. The setting is motivated by information markets in which (i) sellers have the ability to offer information products of different qualities and (ii) the information product provides potential buyers not only with more precise information about the fundamentals, but also with a coordination device that can be used in their strategic interactions with their competitors. Our results illustrate that the nature and intensity of competition among the information provider’s customers play first-order roles in determining the information provider’s optimal strategy. We show that when the customers view their actions as strategic complements, the provider finds it optimal to offer the most accurate information at the provider’s disposal to all potential customers. In contrast, when buyers view their actions as strategic substitutes, the provider maximizes the provider’s profits by either (i) restricting the overall supply of the information product or (ii) distorting its content by offering a product of inferior quality. We also establish that the provider’s incentive to restrict the supply or quality of information provided to the downstream market intensifies in the presence of information leakage. The online appendix is available at https://doi.org/10.1287/mnsc.2018.3068 . This paper was accepted by Gad Allon, operations management.

Suggested Citation

  • Kostas Bimpikis & Davide Crapis & Alireza Tahbaz-Salehi, 2019. "Information Sale and Competition," Management Science, INFORMS, vol. 67(6), pages 2646-2664, June.
  • Handle: RePEc:inm:ormnsc:v:65:y:2019:i:6:p:2646-2664
    DOI: 10.1287/mnsc.2018.3068
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    References listed on IDEAS

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    2. Liyang Han & Jalal Kazempour & Pierre Pinson, 2020. "Monetizing Customer Load Data for an Energy Retailer: A Cooperative Game Approach," Papers 2012.05519, arXiv.org, revised Aug 2021.
    3. Sameer Mehta & Milind Dawande & Ganesh Janakiraman & Vijay Mookerjee, 2022. "An Approximation Scheme for Data Monetization," Production and Operations Management, Production and Operations Management Society, vol. 31(6), pages 2412-2428, June.
    4. Padilla, Jorge & Piccolo, Salvatore & Vasconcelos, Helder, 2021. "Should vertically integrated platforms be mandated to share information with their rivals?," Economics Letters, Elsevier, vol. 203(C).
    5. Huseyin Gurkan & Francis de Véricourt, 2020. "Contracting, pricing, and data collection under the AI flywheel effect," ESMT Research Working Papers ESMT-20-01_R3, ESMT European School of Management and Technology, revised 17 Aug 2021.
    6. Alessandro Bonatti & Munther Dahleh & Thibaut Horel & Amir Nouripour, 2023. "Coordination via Selling Information," Papers 2302.12223, arXiv.org.
    7. Sarah Spiekermann & Hanna Krasnova & Oliver Hinz & Annika Baumann & Alexander Benlian & Henner Gimpel & Irina Heimbach & Antonia Köster & Alexander Maedche & Björn Niehaves & Marten Risius & Manuel Tr, 2022. "Values and Ethics in Information Systems," Business & Information Systems Engineering: The International Journal of WIRTSCHAFTSINFORMATIK, Springer;Gesellschaft für Informatik e.V. (GI), vol. 64(2), pages 247-264, April.
    8. Huseyin Gurkan & Francis de Véricourt, 2020. "Contracting, pricing, and data collection under the AI flywheel effect," ESMT Research Working Papers ESMT-20-01_R1, ESMT European School of Management and Technology, revised 19 Oct 2020.
    9. Francis de Véricourt, & Huseyin Gurkan,, 2020. "Contracting, pricing, and data collection under the AI flywheel effect," ESMT Research Working Papers ESMT-20-01, ESMT European School of Management and Technology.
    10. Xing, Wei & Li, Qiankun & Zhao, Xuan & Li, Jialu, 2020. "Information sale and contract selection under downstream competition," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 136(C).
    11. Huseyin Gurkan & Francis de Véricourt, 2020. "Contracting, pricing, and data collection under the AI flywheel effect," ESMT Research Working Papers ESMT-20-01_R2, ESMT European School of Management and Technology, revised 17 May 2021.
    12. Zhiyuan Wang & Zhiqiang (Eric) Zheng & Wei Jiang & Shaojie Tang, 2021. "Blockchain‐Enabled Data Sharing in Supply Chains: Model, Operationalization, and Tutorial," Production and Operations Management, Production and Operations Management Society, vol. 30(7), pages 1965-1985, July.
    13. Shota Ichihashi, 2020. "Non-competing Data Intermediaries," Staff Working Papers 20-28, Bank of Canada.
    14. Liu, Lu & Feng, Lipan & Jiang, Tao & Zhang, Qian, 2021. "The impact of supply chain competition on the introduction of clean development mechanisms," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 155(C).

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