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Data-driven mergers and personalization

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  • Zhijun Chen
  • Chongwoo Choe
  • Jiajia Cong
  • Noriaki Matsushima

Abstract

This paper studies tech mergers that involve a large volume of consumer data. The merger links the markets for data collection and data application through a consumption synergy. The merger-specific efficiency gains exist in the market for data application due to the consumption synergy and data-enabled personalization. Prices fall in the market for data collection due to the merged firm's incentives to expand its outreach in the market for data application. But in the market for data application, prices generally rise as the efficiency gains are extracted away through personalized pricing, rather than being passed on to consumers. When the consumption synergy is large enough, the merger can result in monopolization of both markets, with further consumer harm when stand-alone competitors exit in the long run. We discuss policy implications including various merger remedies.

Suggested Citation

  • Zhijun Chen & Chongwoo Choe & Jiajia Cong & Noriaki Matsushima, 2021. "Data-driven mergers and personalization," ISER Discussion Paper 1108r, Institute of Social and Economic Research, Osaka University, revised Aug 2021.
  • Handle: RePEc:dpr:wpaper:1108r
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    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. Avi Goldfarb & Catherine Tucker, 2019. "Digital Economics," Journal of Economic Literature, American Economic Association, vol. 57(1), pages 3-43, March.
    3. Greg Shaffer & Z. John Zhang, 2002. "Competitive One-to-One Promotions," Management Science, INFORMS, vol. 48(9), pages 1143-1160, September.
    4. Motta, Massimo & Peitz, Martin, 2021. "Big tech mergers," Information Economics and Policy, Elsevier, vol. 54(C).
    5. Jullien, Bruno & Sand-Zantman, Wilfried, 2021. "The Economics of Platforms: A Theory Guide for Competition Policy," Information Economics and Policy, Elsevier, vol. 54(C).
    6. Massimo Motta & Martin Peitz, 2020. "Big Tech Mergers," CRC TR 224 Discussion Paper Series crctr224_2020_147, University of Bonn and University of Mannheim, Germany.
    7. Yuxin Chen & Ganesh Iyer, 2002. "Research Note Consumer Addressability and Customized Pricing," Marketing Science, INFORMS, vol. 21(2), pages 197-208, November.
    8. Drew Fudenberg & Jean Tirole, 2000. "Customer Poaching and Brand Switching," RAND Journal of Economics, The RAND Corporation, vol. 31(4), pages 634-657, Winter.
    9. Cabral, Luis, 2020. "Merger Policy in Digital Industries," CEPR Discussion Papers 14785, C.E.P.R. Discussion Papers.
    10. Zhijun Chen & Chongwoo Choe & Noriaki Matsushima, 2020. "Competitive Personalized Pricing," Management Science, INFORMS, vol. 66(9), pages 4003-4023, September.
    11. Mark Armstrong & John Vickers, 2010. "Competitive Non-linear Pricing and Bundling," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 77(1), pages 30-60.
    12. Thisse, Jacques-Francois & Vives, Xavier, 1988. "On the Strategic Choice of Spatial Price Policy," American Economic Review, American Economic Association, vol. 78(1), pages 122-137, March.
    13. Emilio Calvano & Giacomo Calzolari & Vincenzo Denicolò & Sergio Pastorello, 2020. "Artificial Intelligence, Algorithmic Pricing, and Collusion," American Economic Review, American Economic Association, vol. 110(10), pages 3267-3297, October.
    14. Sai Krishna Kamepalli & Raghuram Rajan & Luigi Zingales, 2020. "Kill Zone," NBER Working Papers 27146, National Bureau of Economic Research, Inc.
      • Sai Krishna Kamepalli & Raghuram G. Rajan & Luigi Zingales, 2020. "Kill Zone," Working Papers 2020-19, Becker Friedman Institute for Research In Economics.
      • Zingales, Luigi & Kamepalli, Sai Krishna & Rajan, Raghuram, 2020. "Kill Zone," CEPR Discussion Papers 14709, C.E.P.R. Discussion Papers.
      • Kamepalli, Sai Krishna & Rajan, Raghuram G. & Zingales, Luigi, 2020. "Kill Zone," Working Papers 294, The University of Chicago Booth School of Business, George J. Stigler Center for the Study of the Economy and the State.
    15. Olivella, Pau & Vera-Hernandez, Marcos, 2007. "Competition among differentiated health plans under adverse selection," Journal of Health Economics, Elsevier, vol. 26(2), pages 233-250, March.
    16. de Cornière, Alexandre & Taylor, Greg, 2020. "Data and Competition: a General Framework with Applications to Mergers, Market Structure, and Privacy Policy," TSE Working Papers 20-1076, Toulouse School of Economics (TSE).
    17. Axel Gautier & Joe Lamesch, 2020. "Mergers in the Digital Economy," CESifo Working Paper Series 8056, CESifo.
    18. Katz, Michael L., 2021. "Big Tech mergers: Innovation, competition for the market, and the acquisition of emerging competitors," Information Economics and Policy, Elsevier, vol. 54(C).
    19. Zach Y. Brown & Alexander MacKay, 2023. "Competition in Pricing Algorithms," American Economic Journal: Microeconomics, American Economic Association, vol. 15(2), pages 109-156, May.
    20. Motta, Massimo & Peitz, Martin, 2021. "Big tech mergers," Information Economics and Policy, Elsevier, vol. 54(C).
    21. Juanjuan Zhang, 2011. "The Perils of Behavior-Based Personalization," Marketing Science, INFORMS, vol. 30(1), pages 170-186, 01-02.
    22. Vidyanand Choudhary & Anindya Ghose & Tridas Mukhopadhyay & Uday Rajan, 2005. "Personalized Pricing and Quality Differentiation," Management Science, INFORMS, vol. 51(7), pages 1120-1130, July.
    23. Katz Michael L, 2011. "Insurance, Consumer Choice, and the Equilibrium Price and Quality of Hospital Care," The B.E. Journal of Economic Analysis & Policy, De Gruyter, vol. 11(2), pages 1-44, January.
    24. de Cornière, Alexandre & Taylor, Greg, 2022. "Data and Competition: a Simple Framework with Applications to Mergers and Market Structure," CEPR Discussion Papers 14446, C.E.P.R. Discussion Papers.
    25. Biglaiser, Gary & Ma, Ching-to Albert, 2003. "Price and Quality Competition under Adverse Selection: Market Organization and Efficiency," RAND Journal of Economics, The RAND Corporation, vol. 34(2), pages 266-286, Summer.
    26. Dennis W. Carlton & Michael Waldman, 2002. "The Strategic Use of Tying to Preserve and Create Market Power in Evolving Industries," RAND Journal of Economics, The RAND Corporation, vol. 33(2), pages 194-220, Summer.
    27. Argentesi, Elena & Buccirossi, Paolo & Calvano, Emilio & Duso, Tomaso & Marrazzo, Alessia & Nava, Salvatore, 2021. "Merger Policy in Digital Markets: An Ex Post Assessment," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 17(1), pages 95-140.
    28. 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.
    29. Armstrong, Mark & Vickers, John, 2001. "Competitive Price Discrimination," RAND Journal of Economics, The RAND Corporation, vol. 32(4), pages 579-605, Winter.
    30. Maryam Farboodi & Roxana Mihet & Thomas Philippon & Laura Veldkamp, 2019. "Big Data and Firm Dynamics," AEA Papers and Proceedings, American Economic Association, vol. 109, pages 38-42, May.
    31. 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.
    32. Toshihiro Matsumura & Noriaki Matsushima, 2015. "Should Firms Employ Personalized Pricing?," Journal of Economics & Management Strategy, Wiley Blackwell, vol. 24(4), pages 887-903, October.
    33. Cabral, Luís, 2021. "Merger policy in digital industries," Information Economics and Policy, Elsevier, vol. 54(C).
    34. Choi, Jay Pil & Jeon, Doh-Shin & Kim, Byung-Cheol, 2019. "Privacy and personal data collection with information externalities," Journal of Public Economics, Elsevier, vol. 173(C), pages 113-124.
    35. Neeraj Arora & Xavier Dreze & Anindya Ghose & James Hess & Raghuram Iyengar & Bing Jing & Yogesh Joshi & V. Kumar & Nicholas Lurie & Scott Neslin & S. Sajeesh & Meng Su & Niladri Syam & Jacquelyn Thom, 2008. "Putting one-to-one marketing to work: Personalization, customization, and choice," Marketing Letters, Springer, vol. 19(3), pages 305-321, December.
    36. Xuelin Li & Andrew W. Lo & Richard T. Thakor, 2021. "Paying off the Competition: Contracting, Market Power, and Innovation Incentives," NBER Working Papers 28964, National Bureau of Economic Research, Inc.
    37. Choi, Jay Pil & Stefanadis, Christodoulos, 2001. "Tying, Investment, and the Dynamic Leverage Theory," RAND Journal of Economics, The RAND Corporation, vol. 32(1), pages 52-71, Spring.
    38. Calvano, Emilio & Polo, Michele, 2021. "Market power, competition and innovation in digital markets: A survey," Information Economics and Policy, Elsevier, vol. 54(C).
    39. Anindya Ghose & Ke‐Wei Huang, 2009. "Personalized Pricing and Quality Customization," Journal of Economics & Management Strategy, Wiley Blackwell, vol. 18(4), pages 1095-1135, December.
    40. Peitz, Martin & Waldfogel, Joel, 2012. "The Oxford Handbook of the Digital Economy," OUP Catalogue, Oxford University Press, number 9780195397840.
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    Cited by:

    1. 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.
    2. 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).
    3. 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.
    4. David Bounie & Antoine Dubus & Patrick Waelbroeck, 2021. "Competition and Mergers with Strategic Data Intermediaries," CESifo Working Paper Series 9339, CESifo.
    5. 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.
    6. Qiuyu Lu & Noriaki Matsushima, 2023. "Personalized pricing when consumers can purchase multiple items," ISER Discussion Paper 1192, Institute of Social and Economic Research, Osaka University.
    7. 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.
    8. Nakagawa, Akihiko & Matsushima, Noriaki, 2023. "A note on conglomerate mergers: The Google/Fitbit case," Japan and the World Economy, Elsevier, vol. 67(C).
    9. DELBONO Flavio & REGGIANI Carlo & SANDRINI Luca, 2021. "Strategic data sales to competing firms," JRC Working Papers on Digital Economy 2021-05, Joint Research Centre.
    10. Alessandro Bonatti, 2023. "The Platform Dimension of Digital Privacy," NBER Chapters, in: The Economics of Privacy, National Bureau of Economic Research, Inc.
    11. David Bounie & Antoine Dubus & Patrick Waelbroeck, 2023. "Competition Between Strategic Data Intermediaries with Implications for Merger Policy," Working Papers hal-03336520, HAL.
    12. CARBALLA SMICHOWSKI Bruno & DUCH BROWN Nestor & GOMEZ LOSADA Alvaro & MARTENS Bertin, 2021. "When ‘the’ market loses its relevance: an empirical analysis of demand-side linkages in platform ecosystems," JRC Working Papers on Digital Economy 2021-07, Joint Research Centre.

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    More about this item

    JEL classification:

    • D43 - Microeconomics - - Market Structure, Pricing, and Design - - - Oligopoly and Other Forms of Market Imperfection
    • L13 - Industrial Organization - - Market Structure, Firm Strategy, and Market Performance - - - Oligopoly and Other Imperfect Markets
    • L41 - Industrial Organization - - Antitrust Issues and Policies - - - Monopolization; Horizontal Anticompetitive Practices
    • K21 - Law and Economics - - Regulation and Business Law - - - Antitrust Law

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