IDEAS home Printed from https://ideas.repec.org/p/eca/wpaper/2013-403154.html

Make or Buy Decisions and Data Sharing

Author

Listed:
  • Antoine Dubus
  • Patrick Legros

Abstract

Firms may share data to discover potential synergies between their data sets and algorithms,eventually leading to more efficient mergers and acquisitions (M&A) decisions. However,data sharing also modifies the competitive balance when firms do not merge, and a companymay be reluctant to share data with potential rivals. Under general conditions, we show thatfirms benefit from (partially) sharing data. By doing so, they can merge conditionally basedon high synergies. Compared to a laissez-faire situation, the presence of a regulator allowingor refusing the M&A may increase or decrease data sharing, with a concomitant increaseor decrease in consumer surplus. Hence, regulation can lower the surplus of consumers it iswilling to protect. We revisit the Google/Fitbit acquisition through the lens of this interplaybetween strategic data sharing and antitrust policy.

Suggested Citation

  • Antoine Dubus & Patrick Legros, 2026. "Make or Buy Decisions and Data Sharing," Working Papers ECARES 2026-05, ULB -- Universite Libre de Bruxelles.
    • Handle: RePEc:eca:wpaper:2013/403154
    as

    Download full text from publisher

    File URL: https://dipot.ulb.ac.be/dspace/bitstream/2013/403154/3/WP-ECARES-2026-05-Makeorbuydecisions.pdf
    File Function: Œuvre complète ou partie de l'œuvre
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. David Bounie & Antoine Dubus & Patrick Waelbroeck, 2023. "Competition Between Strategic Data Intermediaries with Implications for Merger Policy," Working Papers hal-03336520, HAL.
    2. Jullien, Bruno & Sand-Zantman, Wilfried, 2021. "The Economics of Platforms: A Theory Guide for Competition Policy," Information Economics and Policy, Elsevier, vol. 54(C).
    3. James J. Anton & Dennis A. Yao, 2002. "The Sale of Ideas: Strategic Disclosure, Property Rights, and Contracting," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 69(3), pages 513-531.
    4. Schaefer, Maximilian & Sapi, Geza, 2023. "Complementarities in learning from data: Insights from general search," Information Economics and Policy, Elsevier, vol. 65(C).
    5. Axel Gautier & Robert Maitry, 2024. "Big Tech Acquisitions and Product Discontinuation," Journal of Competition Law and Economics, Oxford University Press, vol. 20(3), pages 246-263.
    6. Myerson, Roger B, 1979. "Incentive Compatibility and the Bargaining Problem," Econometrica, Econometric Society, vol. 47(1), pages 61-73, January.
    7. Samuelson, William F, 1984. "Bargaining under Asymmetric Information," Econometrica, Econometric Society, vol. 52(4), pages 995-1005, July.
    8. Liu, Qihong & Serfes, Konstantinos, 2006. "Customer information sharing among rival firms," European Economic Review, Elsevier, vol. 50(6), pages 1571-1600, August.
    9. John C. Harsanyi & Reinhard Selten, 1972. "A Generalized Nash Solution for Two-Person Bargaining Games with Incomplete Information," Management Science, INFORMS, vol. 18(5-Part-2), pages 80-106, January.
    10. 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.
    11. Jean Tirole, 2023. "Competition and the Industrial Challenge for the Digital Age," Annual Review of Economics, Annual Reviews, vol. 15(1), pages 573-605, September.
    12. Jean Tirole, 2023. "Competition and the Industrial Challenge for the Digital Age," Post-Print hal-04464905, HAL.
    13. Hal R. Varian, 2014. "Big Data: New Tricks for Econometrics," Journal of Economic Perspectives, American Economic Association, vol. 28(2), pages 3-28, Spring.
    14. 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.
    15. In-Koo Cho & David M. Kreps, 1987. "Signaling Games and Stable Equilibria," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 102(2), pages 179-221.
    16. 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.
    17. Yuxin Chen & Chakravarthi Narasimhan & Z. John Zhang, 2001. "Individual Marketing with Imperfect Targetability," Marketing Science, INFORMS, vol. 20(1), pages 23-41, November.
    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. 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).
    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. Bruno Carballa Smichowski & Yassine Lefouili & Andrea Mantovani & Carlo Reggiani, 2025. "Data Sharing or Analytics Sharing ?," Working Papers hal-04956937, HAL.
    4. Carballa-Smichowski, Bruno & Duch-Brown, Néstor & Höcük, Seyit & Kumar, Pradeep & Martens, Bertin & Mulder, Joris & Prüfer, Patricia, 2025. "Economies of scope in data aggregation: Evidence from health data," Information Economics and Policy, Elsevier, vol. 71(C).
    5. Kjell Hausken, 1997. "Game-theoretic and Behavioral Negotiation Theory," Group Decision and Negotiation, Springer, vol. 6(6), pages 511-528, December.
    6. 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.
    7. repec:dpr:wpaper:1083r is not listed on IDEAS
    8. Okada, Akira, 2016. "A non-cooperative bargaining theory with incomplete information: Verifiable types," Journal of Economic Theory, Elsevier, vol. 163(C), pages 318-341.
    9. Frédéric Marty & Thierry Warin, 2025. "Data and Computing Power: The New Frontiers of Competition in Generative AI," Working Papers halshs-05295270, HAL.
    10. 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.
    11. Bergemann, Dirk & Castro, Francisco & Weintraub, Gabriel Y., 2020. "The scope of sequential screening with ex post participation constraints," Journal of Economic Theory, Elsevier, vol. 188(C).
    12. de Clippel, Geoffroy & Pérez-Castrillo, David & Wettstein, David, 2012. "Egalitarian equivalence under asymmetric information," Games and Economic Behavior, Elsevier, vol. 75(1), pages 413-423.
    13. Bester, H., 1991. "Bargaining V.S. Price Competition in a Market with Quality Uncertainty," Papers 9113, Tilburg - Center for Economic Research.
    14. Maximilian Schaefer, 2025. "When Should we Expect Non-Decreasing Returns from Data in Prediction Tasks?," Papers 2503.03602, arXiv.org.
    15. van Damme, Eric & Lang, Xu, 2025. "Two-person bargaining when the disagreement point is private information," Games and Economic Behavior, Elsevier, vol. 150(C), pages 387-400.
    16. Seyed Mohammadreza Davoodalhosseini, 2020. "Adverse Selection With Heterogeneously Informed Agents," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 61(3), pages 1307-1358, August.
    17. Jiadong Gu, 2024. "Data Trade and Consumer Privacy," Papers 2406.12457, arXiv.org, revised Jan 2026.
    18. Jiayang Xu & Jian Cao & Sanjay Kumar & Sisi Wu, 2023. "Optimal government and manufacturer incentive contracts for green production with asymmetric information," PLOS ONE, Public Library of Science, vol. 18(8), pages 1-28, August.
    19. Dubus, Antoine & Legros, Patrick, 2022. "The Sale of Data: Learning Synergies Before M&As," CEPR Discussion Papers 17404, C.E.P.R. Discussion Papers.
    20. David Bounie & Antoine Dubus & Patrick Waelbroeck, 2021. "Competition and Mergers with Strategic Data Intermediaries," CESifo Working Paper Series 9339, CESifo.
    21. Colin F. Camerer & Gideon Nave & Alec Smith, 2019. "Dynamic Unstructured Bargaining with Private Information: Theory, Experiment, and Outcome Prediction via Machine Learning," Management Science, INFORMS, vol. 65(4), pages 1867-1890, April.

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;

    JEL classification:

    • G34 - Financial Economics - - Corporate Finance and Governance - - - Mergers; Acquisitions; Restructuring; Corporate Governance
    • K21 - Law and Economics - - Regulation and Business Law - - - Antitrust Law
    • L10 - Industrial Organization - - Market Structure, Firm Strategy, and Market Performance - - - General
    • L21 - Industrial Organization - - Firm Objectives, Organization, and Behavior - - - Business Objectives of the Firm
    • L24 - Industrial Organization - - Firm Objectives, Organization, and Behavior - - - Contracting Out; Joint Ventures
    • L50 - Industrial Organization - - Regulation and Industrial Policy - - - General
    • L86 - Industrial Organization - - Industry Studies: Services - - - Information and Internet Services; Computer Software

    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:eca:wpaper:2013/403154. 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: Benoit Pauwels (email available below). General contact details of provider: https://edirc.repec.org/data/arulbbe.html .

    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.