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Why Big Data Can Make Creative Destruction More Creative – But Less Destructive

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Abstract

The application of machine learning (ML) to big data has become increasingly important. We propose a model where firms have access to the same ML, but incumbents have access to historical data. We show that big data raises entrepreneurial barriers making the creative destruction process less destructive (less business-stealing) if the entrepreneur has weak access to the incumbent’s data. It is also shown that this induces entrepreneurs to take on more risk and be more creative. Policies making data generally available may therefore be suboptimal. Supporting entrepreneurs’ access to ML might be preferable since it stimulates creative entrepreneurship.

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  • Norbäck, Pehr-Johan & Persson, Lars, 2023. "Why Big Data Can Make Creative Destruction More Creative – But Less Destructive," Working Paper Series 1454, Research Institute of Industrial Economics.
    • Handle: RePEc:hhs:iuiwop:1454
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    References listed on IDEAS

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    1. Richard J. Rosen, 1991. "Research and Development with Asymmetric Firm Sizes," RAND Journal of Economics, The RAND Corporation, vol. 22(3), pages 411-429, Autumn.
    2. Haufler, Andreas & Norbäck, Pehr-Johan & Persson, Lars, 2014. "Entrepreneurial innovations and taxation," Journal of Public Economics, Elsevier, vol. 113(C), pages 13-31.
    3. 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.
    4. Erika Färnstrand Damsgaard & Per Hjertstrand & Pehr‐Johan Norbäck & Lars Persson & Helder Vasconcelos, 2017. "Why Entrepreneurs Choose Risky R&D Projects – But Still Not Risky Enough," Economic Journal, Royal Economic Society, vol. 127(605), pages 164-199, October.
    5. Patrick Bajari & Victor Chernozhukov & Ali Hortaçsu & Junichi Suzuki, 2019. "The Impact of Big Data on Firm Performance: An Empirical Investigation," AEA Papers and Proceedings, American Economic Association, vol. 109, pages 33-37, May.
    6. Alessandro Acquisti & Curtis Taylor & Liad Wagman, 2016. "The Economics of Privacy," Journal of Economic Literature, American Economic Association, vol. 54(2), pages 442-492, June.
    7. Luís M. B. Cabral, 2003. "R&D Competition when firms Choose Variance," Journal of Economics & Management Strategy, Wiley Blackwell, vol. 12(1), pages 139-150, March.
    8. Bertin Martens, 2018. "The impact of data access regimes on artificial intelligence and machine learning," JRC Working Papers on Digital Economy 2018-09, Joint Research Centre.
    9. Richard Gilbert, 2006. "Looking for Mr. Schumpeter: Where Are We in the Competition-Innovation Debate?," NBER Chapters, in: Innovation Policy and the Economy, Volume 6, pages 159-215, National Bureau of Economic Research, Inc.
    10. Erika Färnstrand Damsgaard & Per Hjertstrand & Pehr‐Johan Norbäck & Lars Persson & Helder Vasconcelos, 2017. "Why Entrepreneurs Choose Risky R&D Projects – But Still Not Risky Enough," Economic Journal, Royal Economic Society, vol. 127(605), pages 164-199, October.
    11. Bertin Martens, 2018. "The impact of data access regimes on artificial intelligence and machine learning," JRC Working Papers on Digital Economy 2019-05, Joint Research Centre (Seville site).
    12. Kretschmer, Tobias & Peukert, Christian & Bechtold, Stefan & Batikas, Michail, 2020. "European Privacy Law and Global Markets for Data," CEPR Discussion Papers 14475, C.E.P.R. Discussion Papers.
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    More about this item

    Keywords

    Machine Learning; Big Data; Creative Destruction; Entrepreneurship; Operational Data;
    All these keywords.

    JEL classification:

    • L10 - Industrial Organization - - Market Structure, Firm Strategy, and Market Performance - - - General
    • L20 - Industrial Organization - - Firm Objectives, Organization, and Behavior - - - General
    • M13 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Business Administration - - - New Firms; Startups
    • O30 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - General

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