IDEAS home Printed from https://ideas.repec.org/p/hal/wpaper/hal-03336520.html
   My bibliography  Save this paper

Competition Between Strategic Data Intermediaries with Implications for Merger Policy

Author

Listed:
  • David Bounie

    (IP Paris - Institut Polytechnique de Paris, SES - Département Sciences Economiques et Sociales - Télécom ParisTech, ECO-Télécom Paris - Equipe Eco Economie - I3 SES - Institut interdisciplinaire de l’innovation de Telecom Paris - Télécom ParisTech - I3 - Institut interdisciplinaire de l’innovation - CNRS - Centre National de la Recherche Scientifique)

  • Antoine Dubus

    (ETH Zürich - Eidgenössische Technische Hochschule - Swiss Federal Institute of Technology [Zürich])

  • Patrick Waelbroeck

    (IP Paris - Institut Polytechnique de Paris, SES - Département Sciences Economiques et Sociales - Télécom ParisTech, ECO-Télécom Paris - Equipe Eco Economie - I3 SES - Institut interdisciplinaire de l’innovation de Telecom Paris - Télécom ParisTech - I3 - Institut interdisciplinaire de l’innovation - CNRS - Centre National de la Recherche Scientifique)

Abstract

We build a model of competition between strategic data intermediaries collecting consumer information that they sell to firms competing in a product market. Each intermediary has access to exclusive information on a group of consumers and competes with other intermediaries on a common group of consumers. Information allows firms to distinguish different segments of the consumer demand, and an equilibrium has the following properties. (i.) The largest intermediary collects the highest number of segments and sells information in the competitive market. (ii.) The incentives of the largest intermediary to collect data increase with the competitive pressure exerted by smaller intermediaries through an escape-competition effect. (iii.) Intermediaries sell information on a larger group of consumers in the competitive market than in the monopoly markets, increasing the intensity of competition among firms. (iv.) Competition reduces the incentives of intermediaries to collect data, thus increasing consumer surplus. These results have important implications for merger policy. Indeed, mergers increase the amount of data collected by intermediaries, which reduces consumer surplus due to enhanced price discrimination. This effect takes place in the market where the merging intermediaries operate, and also in other related markets through a ripple effect.

Suggested Citation

  • David Bounie & Antoine Dubus & Patrick Waelbroeck, 2023. "Competition Between Strategic Data Intermediaries with Implications for Merger Policy," Working Papers hal-03336520, HAL.
  • Handle: RePEc:hal:wpaper:hal-03336520
    Note: View the original document on HAL open archive server: https://hal.science/hal-03336520v3
    as

    Download full text from publisher

    File URL: https://hal.science/hal-03336520v3/document
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Zhijun Chen & Chongwoo Choe & Jiajia Cong & Noriaki Matsushima, 2022. "Data‐driven mergers and personalization," RAND Journal of Economics, RAND Corporation, vol. 53(1), pages 3-31, March.
    2. Dirk Bergemann & Alessandro Bonatti & Tan Gan, 2022. "The economics of social data," RAND Journal of Economics, RAND Corporation, vol. 53(2), pages 263-296, June.
    3. Qihong Liu & Konstantinos Serfes, 2004. "Quality of Information and Oligopolistic Price Discrimination," Journal of Economics & Management Strategy, Wiley Blackwell, vol. 13(4), pages 671-702, December.
    4. Grossman, Sanford J & Stiglitz, Joseph E, 1980. "On the Impossibility of Informationally Efficient Markets," American Economic Review, American Economic Association, vol. 70(3), pages 393-408, June.
    5. Hal Varian, 2018. "Artificial Intelligence, Economics, and Industrial Organization," NBER Chapters, in: The Economics of Artificial Intelligence: An Agenda, pages 399-419, National Bureau of Economic Research, Inc.
    6. Dirk Bergemann & Alessandro Bonatti, 2015. "Selling Cookies," American Economic Journal: Microeconomics, American Economic Association, vol. 7(3), pages 259-294, August.
    7. Alessandro Acquisti & Hal R. Varian, 2005. "Conditioning Prices on Purchase History," Marketing Science, INFORMS, vol. 24(3), pages 367-381, May.
    8. Paul Belleflamme & Wing Man Wynne Lam, & Wouter Vergote, 2020. "Competitive Imperfect Price Discrimination and Market Power," Marketing Science, INFORMS, vol. 39(5), pages 996-1015, September.
    9. Charles I. Jones & Christopher Tonetti, 2020. "Nonrivalry and the Economics of Data," American Economic Review, American Economic Association, vol. 110(9), pages 2819-2858, September.
    10. Dirk Bergemann & Alessandro Bonatti & Alex Smolin, 2018. "The Design and Price of Information," American Economic Review, American Economic Association, vol. 108(1), pages 1-48, January.
    11. David Bounie & Antoine Dubus & Patrick Waelbroeck, 2021. "Selling strategic information in digital competitive markets," RAND Journal of Economics, RAND Corporation, vol. 52(2), pages 283-313, June.
    12. Philippe Aghion & Nick Bloom & Richard Blundell & Rachel Griffith & Peter Howitt, 2005. "Competition and Innovation: an Inverted-U Relationship," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 120(2), pages 701-728.
    13. Jan De Loecker & Jan Eeckhout & Gabriel Unger, 2020. "The Rise of Market Power and the Macroeconomic Implications [“Econometric Tools for Analyzing Market Outcomes”]," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 135(2), pages 561-644.
    14. Jentzsch, Nicola & Sapi, Geza & Suleymanova, Irina, 2013. "Targeted pricing and customer data sharing among rivals," International Journal of Industrial Organization, Elsevier, vol. 31(2), pages 131-144.
    15. Zhijun Chen & pch346 & Chongwoo Choe & Jiajia Cong & Noriaki Matsushima, 2020. "Data-Driven Mergers and Personalization," Monash Economics Working Papers 16-20, Monash University, Department of Economics.
    16. Dirk Bergemann & Alessandro Bonatti, 2019. "The Economics of Social Data: An Introduction," Cowles Foundation Discussion Papers 2171R, Cowles Foundation for Research in Economics, Yale University, revised Sep 2019.
    17. Chongwoo Choe & Stephen King & Noriaki Matsushima, 2018. "Pricing with Cookies: Behavior-Based Price Discrimination and Spatial Competition," Management Science, INFORMS, vol. 64(12), pages 5669-5687, December.
    18. Diamond, Peter A., 1971. "A model of price adjustment," Journal of Economic Theory, Elsevier, vol. 3(2), pages 156-168, June.
    19. Geoffrey Parker & Georgios Petropoulos & Marshall Van Alstyne, 2021. "Platform mergers and antitrust," Working Papers 43276, Bruegel.
    20. Geoffrey Parker & Georgios Petropoulos & Marshall Van Alstyne, 2021. "Platform mergers and antitrust," Working Papers 40796, Bruegel.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. David Bounie & Antoine Dubus & Patrick Waelbroeck, 2021. "Competition and Mergers with Strategic Data Intermediaries," CESifo Working Paper Series 9339, CESifo.
    2. Flavio Pino, 2022. "The microeconomics of data – a survey," Economia e Politica Industriale: Journal of Industrial and Business Economics, Springer;Associazione Amici di Economia e Politica Industriale, vol. 49(3), pages 635-665, September.
    3. Choe, Chongwoo & Matsushima, Noriaki & Tremblay, Mark J., 2022. "Behavior-based personalized pricing: When firms can share customer information," International Journal of Industrial Organization, Elsevier, vol. 82(C).
    4. Yiquan Gu & Leonardo Madio & Carlo Reggiani, 2022. "Data brokers co-opetition [The impact of big data on firm performance: an empirical investigation]," Oxford Economic Papers, Oxford University Press, vol. 74(3), pages 820-839.
    5. David Bounie & Antoine Dubus & Patrick Waelbroeck, 2022. "Market for Information and Selling Mechanisms," CER-ETH Economics working paper series 22/367, CER-ETH - Center of Economic Research (CER-ETH) at ETH Zurich.
    6. David Bounies & Antoine Dubus & Patrick Waelbroeck, 2020. "Market for Information and Selling Mechanisms," Working Papers ECARES 2020-07, ULB -- Universite Libre de Bruxelles.
    7. David Bounie & Antoine Dubus & Patrick Waelbroeck, 2020. "Market for Information and Selling Mechanisms," CESifo Working Paper Series 8307, CESifo.
    8. DELBONO Flavio & REGGIANI Carlo & SANDRINI Luca, 2021. "Strategic data sales to competing firms," JRC Working Papers on Digital Economy 2021-05, Joint Research Centre.
    9. Alessandro Bonatti, 2023. "The Platform Dimension of Digital Privacy," NBER Chapters, in: The Economics of Privacy, National Bureau of Economic Research, Inc.
    10. Antoine Dubus, 2023. "Behavior-Based Algorithmic Pricing," Working Papers hal-03269586, HAL.
    11. S. Nageeb Ali & Greg Lewis & Shoshana Vasserman, 2019. "Voluntary Disclosure and Personalized Pricing," Papers 1912.04774, arXiv.org, revised Aug 2020.
    12. Daron Acemoglu & Ali Makhdoumi & Azarakhsh Malekian & Asu Ozdaglar, 2022. "Too Much Data: Prices and Inefficiencies in Data Markets," American Economic Journal: Microeconomics, American Economic Association, vol. 14(4), pages 218-256, November.
    13. Shuran Zheng & Yiling Chen, 2020. "Optimal Advertising for Information Products," Papers 2002.10045, arXiv.org, revised Sep 2021.
    14. Ronen Gradwohl & Moshe Tennenholtz, 2022. "Pareto-Improving Data-Sharing," Papers 2205.11295, arXiv.org.
    15. Dengler, Sebastian & Prüfer, Jens, 2021. "Consumers' privacy choices in the era of big data," Games and Economic Behavior, Elsevier, vol. 130(C), pages 499-520.
    16. Mert Demirer & Diego Jimenez-Hernandez & Dean Li & Sida Peng, 2024. "Data, Privacy Laws and Firm Production: Evidence from the GDPR," Working Paper Series WP 2024-02, Federal Reserve Bank of Chicago.
    17. Chongwoo Choe & Jiajia Cong & Chengsi Wang, 2024. "Softening Competition Through Unilateral Sharing of Customer Data," Management Science, INFORMS, vol. 70(1), pages 526-543, January.
    18. Yiquan Gu & Leonardo Madio & Carlo Reggiani, 2019. "Exclusive Data, Price Manipulation and Market Leadership," CESifo Working Paper Series 7853, CESifo.
    19. Ronen Gradwohl & Moshe Tennenholtz, 2023. "Selling Data to a Competitor (Extended Abstract)," Papers 2307.05078, arXiv.org.
    20. Zhijun Chen & Chongwoo Choe & Noriaki Matsushima, 2020. "Competitive Personalized Pricing," Management Science, INFORMS, vol. 66(9), pages 4003-4023, September.

    More about this item

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:hal:wpaper:hal-03336520. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: CCSD (email available below). General contact details of provider: https://hal.archives-ouvertes.fr/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.