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The determinants of AI innovation across European firms

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  • Igna, Ioana

    (CIRCLE, Lund University)

  • Venturini, Francesco

    (University of Perugia)

Abstract

Using patent data for a panel sample of European companies between 1995 and 2016 we explore whether the innovative success in Artificial Intelligence (AI) is related to earlier firms’ research in the area of Information and Communication Technology (ICT), and identify which company characteristics and external factors shape this performance. We show that AI innovation has been developed by the most prolific firms in the field of ICT, presents strong dynamic returns (learning effects), and benefits from complementaries with knowledge developed in network and communication technologies, high-speed computing and data analysis, and more recently in cognition and imaging. AI patent productivity increases with the scale of research but is lower in presence of narrow and mature technological competencies of the firm. AI innovating companies are found to benefit from spillovers associated with innovations developed in the field of ICT by the business sector; this effect, however, is confined to frontier firms. Our findings suggest that, with the take-off of the new technology, the technological lead of top AI innovators has increased mainly due to the accumulation of internal competencies and the expanding knowledge base. These trends help explain the concentration process of the world’s data market.

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  • Igna, Ioana & Venturini, Francesco, 2022. "The determinants of AI innovation across European firms," Papers in Innovation Studies 2022/3, Lund University, CIRCLE - Centre for Innovation Research.
    • Handle: RePEc:hhs:lucirc:2022_003
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    1. Erik Brynjolfsson & Daniel Rock & Chad Syverson, 2021. "The Productivity J-Curve: How Intangibles Complement General Purpose Technologies," American Economic Journal: Macroeconomics, American Economic Association, vol. 13(1), pages 333-372, January.
    2. Martin Beraja & David Y Yang & Noam Yuchtman, 2023. "Data-intensive Innovation and the State: Evidence from AI Firms in China," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 90(4), pages 1701-1723.
    3. Madsen, Jakob B. & Saxena, Shishir & Ang, James B., 2010. "The Indian growth miracle and endogenous growth," Journal of Development Economics, Elsevier, vol. 93(1), pages 37-48, September.
    4. Georg Graetz & Guy Michaels, 2018. "Robots at Work," The Review of Economics and Statistics, MIT Press, vol. 100(5), pages 753-768, December.
    5. Sergio Petralia, 2020. "Mapping General Purpose Technologies with Patent Data," Papers in Evolutionary Economic Geography (PEEG) 2027, Utrecht University, Department of Human Geography and Spatial Planning, Group Economic Geography, revised Jul 2020.
    6. James B. Ang & Jakob B. Madsen, 2011. "Can Second-Generation Endogenous Growth Models Explain the Productivity Trends and Knowledge Production in the Asian Miracle Economies?," The Review of Economics and Statistics, MIT Press, vol. 93(4), pages 1360-1373, November.
    7. Nicholas Bloom & Mark Schankerman & John Van Reenen, 2013. "Identifying Technology Spillovers and Product Market Rivalry," Econometrica, Econometric Society, vol. 81(4), pages 1347-1393, July.
    8. Hingley, Peter & Park, Walter G., 2017. "Do business cycles affect patenting? Evidence from European Patent Office filings," Technological Forecasting and Social Change, Elsevier, vol. 116(C), pages 76-86.
    9. David Autor & David Dorn & Lawrence F Katz & Christina Patterson & John Van Reenen, 2020. "The Fall of the Labor Share and the Rise of Superstar Firms [“Automation and New Tasks: How Technology Displaces and Reinstates Labor”]," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 135(2), pages 645-709.
    10. Haefner, Naomi & Wincent, Joakim & Parida, Vinit & Gassmann, Oliver, 2021. "Artificial intelligence and innovation management: A review, framework, and research agenda✰," Technological Forecasting and Social Change, Elsevier, vol. 162(C).
    11. David H. Autor & Frank Levy & Richard J. Murnane, 2003. "The skill content of recent technological change: an empirical exploration," Proceedings, Federal Reserve Bank of San Francisco, issue Nov.
    12. Mario Benassi & Elena Grinza & Francesco Rentocchini, 2020. "The rush for patents in the Fourth Industrial Revolution," Economia e Politica Industriale: Journal of Industrial and Business Economics, Springer;Associazione Amici di Economia e Politica Industriale, vol. 47(4), pages 559-588, December.
    13. Benjamin Haibe-Kains & George Alexandru Adam & Ahmed Hosny & Farnoosh Khodakarami & Levi Waldron & Bo Wang & Chris McIntosh & Anna Goldenberg & Anshul Kundaje & Casey S. Greene & Tamara Broderick & Mi, 2020. "Transparency and reproducibility in artificial intelligence," Nature, Nature, vol. 586(7829), pages 14-16, October.
    14. Hall, B. & Jaffe, A. & Trajtenberg, M., 2001. "The NBER Patent Citations Data File: Lessons, Insights and Methodological Tools," Papers 2001-29, Tel Aviv.
    15. Maria Savona, 2019. "The Value of Data:Towards a Framework to Redistribute It," SPRU Working Paper Series 2019-21, SPRU - Science Policy Research Unit, University of Sussex Business School.
    16. Bronwyn H. Hall & Manuel Trajtenberg, 2006. "Uncovering General Purpose Technologies with Patent Data," Chapters, in: Cristiano Antonelli & Dominique Foray & Bronwyn H. Hall & W. Edward Steinmueller (ed.), New Frontiers in the Economics of Innovation and New Technology, chapter 14, Edward Elgar Publishing.
    17. Bronwyn H. Hall & Manuel Trajtenberg, 2004. "Uncovering GPTS with Patent Data," NBER Working Papers 10901, National Bureau of Economic Research, Inc.
    18. Kaiser, Ulrich & Kongsted, Hans Christian & Rønde, Thomas, 2015. "Does the mobility of R&D labor increase innovation?," Journal of Economic Behavior & Organization, Elsevier, vol. 110(C), pages 91-105.
    19. Mario Benassi & Elena Grinza & Francesco Rentocchini, 2019. "The Rush for Patents in the Fourth Industrial Revolution: An Exploration of Patenting Activity at the European Patent Office," SPRU Working Paper Series 2019-12, SPRU - Science Policy Research Unit, University of Sussex Business School.
    20. Arianna Martinelli & Andrea Mina & Massimo Moggi, 2021. "The enabling technologies of industry 4.0: examining the seeds of the fourth industrial revolution [Mapping innovation dynamics in the Internet of Things domain: evidence from patent analysis]," Industrial and Corporate Change, Oxford University Press and the Associazione ICC, vol. 30(1), pages 161-188.
    21. Mariagrazia Squicciarini & Heike Nachtigall, 2021. "Demand for AI skills in jobs: Evidence from online job postings," OECD Science, Technology and Industry Working Papers 2021/03, OECD Publishing.
    22. Erik Brynjolfsson & Tom Mitchell & Daniel Rock, 2018. "What Can Machines Learn, and What Does It Mean for Occupations and the Economy?," AEA Papers and Proceedings, American Economic Association, vol. 108, pages 43-47, May.
    23. Takashi Inaba & Mariagrazia Squicciarini, 2017. "ICT: A new taxonomy based on the international patent classification," OECD Science, Technology and Industry Working Papers 2017/1, OECD Publishing.
    24. Sergey Lychagin & Joris Pinkse & Margaret E. Slade & John Van Reenen, 2016. "Spillovers in Space: Does Geography Matter?," Journal of Industrial Economics, Wiley Blackwell, vol. 64(2), pages 295-335, June.
    25. Zoltan J. Acs & Luc Anselin & Attila Varga, 2008. "Patents and Innovation Counts as Measures of Regional Production of New Knowledge," Chapters, in: Entrepreneurship, Growth and Public Policy, chapter 11, pages 135-151, Edward Elgar Publishing.
    26. Helene Dernis & Petros Gkotsis & Nicola Grassano & Shohei Nakazato & Mariagrazia Squicciarini & Brigitte van Beuzekom & Antonio Vezzani, 2019. "World Corporate Top R&D investors: Shaping the Future of Technologies and of AI," JRC Research Reports JRC117068, Joint Research Centre.
    27. Schettino, Francesco & Sterlacchini, Alessandro & Venturini, Francesco, 2013. "Inventive productivity and patent quality: Evidence from Italian inventors," Journal of Policy Modeling, Elsevier, vol. 35(6), pages 1043-1056.
    28. Alessandro Sterlacchini, 2022. "AI Patenting and Employment: Evidence from the World's Top R&D Investors," Working Papers 462, Universita' Politecnica delle Marche (I), Dipartimento di Scienze Economiche e Sociali.
    29. Arntz, Melanie & Gregory, Terry & Zierahn, Ulrich, 2017. "Revisiting the risk of automation," Economics Letters, Elsevier, vol. 159(C), pages 157-160.
    30. Stefano Baruffaldi & Brigitte van Beuzekom & Hélène Dernis & Dietmar Harhoff & Nandan Rao & David Rosenfeld & Mariagrazia Squicciarini, 2020. "Identifying and measuring developments in artificial intelligence: Making the impossible possible," OECD Science, Technology and Industry Working Papers 2020/05, OECD Publishing.
    31. Germán Gutiérrez & Thomas Philippon, 2019. "Fading Stars," AEA Papers and Proceedings, American Economic Association, vol. 109, pages 312-316, May.
    32. Charles M. A. Clark & Aleksandr V. Gevorkyan, 2020. "Artificial Intelligence and Human Flourishing," American Journal of Economics and Sociology, Wiley Blackwell, vol. 79(4), pages 1307-1344, September.
    33. Shohei Nakazato & Mariagrazia Squicciarini, 2021. "Artificial intelligence companies, goods and services: A trademark-based analysis," OECD Science, Technology and Industry Working Papers 2021/06, OECD Publishing.
    34. Wendy C. Y. Li & Bronwyn H. Hall, 2020. "Depreciation of Business R&D Capital," Review of Income and Wealth, International Association for Research in Income and Wealth, vol. 66(1), pages 161-180, March.
    35. De Ridder, M., 2019. "Market Power and Innovation in the Intangible Economy," Cambridge Working Papers in Economics 1931, Faculty of Economics, University of Cambridge.
    36. Rammer, Christian & Fernández, Gastón P. & Czarnitzki, Dirk, 2022. "Artificial intelligence and industrial innovation: Evidence from German firm-level data," Research Policy, Elsevier, vol. 51(7).
    37. Clancy, Matthew S., 2018. "Inventing by combining pre-existing technologies: Patent evidence on learning and fishing out," Research Policy, Elsevier, vol. 47(1), pages 252-265.
    38. Breschi, Stefano & Lissoni, Francesco & Malerba, Franco, 2003. "Knowledge-relatedness in firm technological diversification," Research Policy, Elsevier, vol. 32(1), pages 69-87, January.
    39. Righi, Riccardo & Samoili, Sofia & López Cobo, Montserrat & Vázquez-Prada Baillet, Miguel & Cardona, Melisande & De Prato, Giuditta, 2020. "The AI techno-economic complex System: Worldwide landscape, thematic subdomains and technological collaborations," Telecommunications Policy, Elsevier, vol. 44(6).
    40. Petralia, Sergio, 2020. "Mapping general purpose technologies with patent data," Research Policy, Elsevier, vol. 49(7).
    41. P.A. Geroski, 2003. "Competition in Markets and Competition for Markets," Journal of Industry, Competition and Trade, Springer, vol. 3(3), pages 151-166, September.
    42. Venturini, Francesco, 2012. "Product variety, product quality, and evidence of endogenous growth," Economics Letters, Elsevier, vol. 117(1), pages 74-77.
    43. Carol Corrado & Chiara Criscuolo & Jonathan Haskel & Alexander Himbert & Cecilia Jona-Lasinio, 2021. "New evidence on intangibles, diffusion and productivity," OECD Science, Technology and Industry Working Papers 2021/10, OECD Publishing.
    44. Zhen Yu & Zheng Liang & Peiyi Wu, 2021. "How data shape actor relations in artificial intelligence innovation systems: an empirical observation from China [Linking vertically related industries: entry by employee spinouts across industry ," Industrial and Corporate Change, Oxford University Press and the Associazione ICC, vol. 30(1), pages 251-267.
    45. Hunt, Wil & Sarkar, Sudipa & Warhurst, Chris, 2022. "Measuring the impact of AI on jobs at the organization level: Lessons from a survey of UK business leaders," Research Policy, Elsevier, vol. 51(2).
    46. Ghasemaghaei, Maryam & Calic, Goran, 2019. "Does big data enhance firm innovation competency? The mediating role of data-driven insights," Journal of Business Research, Elsevier, vol. 104(C), pages 69-84.
    47. Mr. Federico J Diez & Mr. Daniel Leigh & Suchanan Tambunlertchai, 2018. "Global Market Power and its Macroeconomic Implications," IMF Working Papers 2018/137, International Monetary Fund.
    48. Trajtenberg, Manuel, 2018. "AI as the next GPT: a Political-Economy Perspective," CEPR Discussion Papers 12721, C.E.P.R. Discussion Papers.
    49. Bessen, James & Impink, Stephen Michael & Reichensperger, Lydia & Seamans, Robert, 2022. "The role of data for AI startup growth," Research Policy, Elsevier, vol. 51(5).
    50. Venturini, Francesco, 2022. "Intelligent technologies and productivity spillovers: Evidence from the Fourth Industrial Revolution," Journal of Economic Behavior & Organization, Elsevier, vol. 194(C), pages 220-243.
    51. Joonkyung Ha & Peter Howitt, 2007. "Accounting for Trends in Productivity and R&D: A Schumpeterian Critique of Semi-Endogenous Growth Theory," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 39(4), pages 733-774, June.
    52. Davide Castellani, 2017. "The Changing Geography of Innovation and the Role of Multinational Enterprises," John H Dunning Centre for International Business Discussion Papers jhd-dp2017-02, Henley Business School, University of Reading.
    53. Stéphane Maraut & Hélène Dernis & Colin Webb & Vincenzo Spiezia & Dominique Guellec, 2008. "The OECD REGPAT Database: A Presentation," OECD Science, Technology and Industry Working Papers 2008/2, OECD Publishing.
    54. Corrocher, Nicoletta & Malerba, Franco & Montobbio, Fabio, 2007. "Schumpeterian patterns of innovative activity in the ICT field," Research Policy, Elsevier, vol. 36(3), pages 418-432, April.
    55. Simone Vannuccini & Ekaterina Prytkova, 2021. "Artificial Intelligence’s New Clothes? From General Purpose Technology to Large Technical System," SPRU Working Paper Series 2021-02, SPRU - Science Policy Research Unit, University of Sussex Business School.
    56. Rinaldo Evangelista & Valentina Meliciani & Antonio Vezzani, 2015. "The Specialisation of EU Regions in Fast Growing and Key Enabling Technologies," JRC Research Reports JRC98111, Joint Research Centre.
    57. Richard Blundell & Rachel Griffith & John van Reenen, 1999. "Market Share, Market Value and Innovation in a Panel of British Manufacturing Firms," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 66(3), pages 529-554.
    58. Jaana Rahko, 2014. "Market value of R&D, patents, and organizational capital: Finnish evidence," Economics of Innovation and New Technology, Taylor & Francis Journals, vol. 23(4), pages 353-377, June.
    59. Venturini, Francesco, 2015. "The modern drivers of productivity," Research Policy, Elsevier, vol. 44(2), pages 357-369.
    60. Hoisl, Karin & Stelzer, Tobias & Biala, Stefanie, 2015. "Forecasting technological discontinuities in the ICT industry," Research Policy, Elsevier, vol. 44(2), pages 522-532.
    61. Jongho Lee & Keun Lee, 2021. "Is the fourth industrial revolution a continuation of the third industrial revolution or something new under the sun? Analyzing technological regimes using US patent data [Vertical integration and ," Industrial and Corporate Change, Oxford University Press and the Associazione ICC, vol. 30(1), pages 137-159.
    62. Michael Webb & Nick Short & Nicholas Bloom & Josh Lerner, 2018. "Some Facts of High-Tech Patenting," NBER Working Papers 24793, National Bureau of Economic Research, Inc.
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    Cited by:

    1. A. Fronzetti Colladon & B. Guardabascio & F. Venturini, 2023. "A new mapping of technological interdependence," Papers 2308.00014, arXiv.org, revised Mar 2024.
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    3. Flavio Calvino & Luca Fontanelli, 2023. "Artificial intelligence, complementary assets and productivity: evidence from French firms," LEM Papers Series 2023/35, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.

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    More about this item

    Keywords

    AI; ICT; patenting; European firms;
    All these keywords.

    JEL classification:

    • O31 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Innovation and Invention: Processes and Incentives
    • O32 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Management of Technological Innovation and R&D
    • O34 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Intellectual Property and Intellectual Capital

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