IDEAS home Printed from https://ideas.repec.org/p/atv/wpaper/2201.html
   My bibliography  Save this paper

The Development of Al in Multinational Enterprises - Effects upon Technological Trajectories and Innovation Performance

Author

Listed:
  • Matheus Eduardo Leusin

Abstract

This paper investigates how the development of AI-related inventions by Multinational Enterprises (MNEs) affects their technological trajectories and innovative performance. I combine a matched-pair analysis with an extension of the Difference-in-Difference method to analyse these effects over a novel panel dataset of MNEs. This dataset links over 30 thousand MNEs to more than 10 million patents that these companies owned directly or indirectly (i.e., through their subsidiaries) in the period from 2011 to 2019. The results indicate that MNEs introducing AI-related inventions increase the relatedness of subsequent inventions by about 10 per cent compared to a control group. These results are robust when accounting for a self-selection bias. AI is thus being used to reinforce the existing technological trajectories, rather than to disrupt them. The results also suggest that the number of subsequent inventions is about 40 per cent higher for MNEs that introduce AI during the observation period compared to the control group, without significant effects on the intensity of R&D expenditures per invention. It is argued that this increase in innovative performance is linked not only to knowledge dynamics created by learning about AI but also by AI's technical potential to be used for learning.

Suggested Citation

  • Matheus Eduardo Leusin, 2022. "The Development of Al in Multinational Enterprises - Effects upon Technological Trajectories and Innovation Performance," Bremen Papers on Economics & Innovation 2201, University of Bremen, Faculty of Business Studies and Economics.
    • Handle: RePEc:atv:wpaper:2201
    DOI: https://doi.org/10.26092/elib/1443
    as

    Download full text from publisher

    File URL: https://media.suub.uni-bremen.de/bitstream/elib/5820/3/The%20Development%20of%20Al%20in%20Multinational%20Enterprises_Leusin%2c%20ierp.pdf
    Download Restriction: no
    File URL: https://libkey.io/https://doi.org/10.26092/elib/1443?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Dosi, Giovanni, 1993. "Technological paradigms and technological trajectories : A suggested interpretation of the determinants and directions of technical change," Research Policy, Elsevier, vol. 22(2), pages 102-103, April.
    2. Teece, David J., 2018. "Profiting from innovation in the digital economy: Enabling technologies, standards, and licensing models in the wireless world," Research Policy, Elsevier, vol. 47(8), pages 1367-1387.
    3. Carolina Castaldi & Koen Frenken & Bart Los, 2015. "Related Variety, Unrelated Variety and Technological Breakthroughs: An analysis of US State-Level Patenting," Regional Studies, Taylor & Francis Journals, vol. 49(5), pages 767-781, May.
    4. Fujii, Hidemichi & Managi, Shunsuke, 2018. "Trends and priority shifts in artificial intelligence technology invention: A global patent analysis," Economic Analysis and Policy, Elsevier, vol. 58(C), pages 60-69.
    5. Antonelli, Cristiano & Krafft, Jackie & Quatraro, Francesco, 2010. "Recombinant knowledge and growth: The case of ICTs," Structural Change and Economic Dynamics, Elsevier, vol. 21(1), pages 50-69, March.
    6. 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.
    7. Solheim, Marte C.W. & Boschma, Ron & Herstad, Sverre J., 2020. "Collected worker experiences and the novelty content of innovation," Research Policy, Elsevier, vol. 49(1).
    8. Callaway, Brantly & Sant’Anna, Pedro H.C., 2021. "Difference-in-Differences with multiple time periods," Journal of Econometrics, Elsevier, vol. 225(2), pages 200-230.
    9. Colombelli, Alessandra & Krafft, Jackie & Quatraro, Francesco, 2013. "Properties of knowledge base and firm survival: Evidence from a sample of French manufacturing firms," Technological Forecasting and Social Change, Elsevier, vol. 80(8), pages 1469-1483.
    10. Breschi, Stefano & Lissoni, Francesco & Malerba, Franco, 2003. "Knowledge-relatedness in firm technological diversification," Research Policy, Elsevier, vol. 32(1), pages 69-87, January.
    11. Aarstad, Jarle & Kvitastein, Olav A. & Jakobsen, Stig-Erik, 2016. "Related and unrelated variety as regional drivers of enterprise productivity and innovation: A multilevel study," Research Policy, Elsevier, vol. 45(4), pages 844-856.
    12. C. A. Hidalgo & B. Klinger & A. -L. Barabasi & R. Hausmann, 2007. "The Product Space Conditions the Development of Nations," Papers 0708.2090, arXiv.org.
    13. John Cantwell & Birgitte Andersen, 1996. "A Statistical Analysis of Corporate Technological Leadership Historically," Economics of Innovation and New Technology, Taylor & Francis Journals, vol. 4(3), pages 211-234.
    14. Iain M. Cockburn & Rebecca Henderson & Scott Stern, 2018. "The Impact of Artificial Intelligence on Innovation," NBER Working Papers 24449, National Bureau of Economic Research, Inc.
    15. Dieter F. Kogler & David L. Rigby & Isaac Tucker, 2013. "Mapping Knowledge Space and Technological Relatedness in US Cities," European Planning Studies, Taylor & Francis Journals, vol. 21(9), pages 1374-1391, September.
    16. Genz, Sabrina & Gregory, Terry & Janser, Markus & Lehmer, Florian & Matthes, Britta, 2021. "How do workers adjust when firms adopt new technologies?," ZEW Discussion Papers 21-073, ZEW - Leibniz Centre for European Economic Research.
    17. Christian Rammer & Gastón P Fernández & Dirk Czarnitzki, 2021. "Artificial Intelligence and Industrial Innovation: Evidence from Firm-Level Data," Working Papers of Department of Management, Strategy and Innovation, Leuven 674605, KU Leuven, Faculty of Economics and Business (FEB), Department of Management, Strategy and Innovation, Leuven.
    18. Paschen, Ulrich & Pitt, Christine & Kietzmann, Jan, 2020. "Artificial intelligence: Building blocks and an innovation typology," Business Horizons, Elsevier, vol. 63(2), pages 147-155.
    19. Juan Alcácer & John Cantwell & Lucia Piscitello, 2016. "Internationalization in the information age: A new era for places, firms, and international business networks?," Journal of International Business Studies, Palgrave Macmillan;Academy of International Business, vol. 47(5), pages 499-512, June.
    20. Ejdemo, Thomas & Örtqvist, Daniel, 2020. "Related variety as a driver of regional innovation and entrepreneurship: A moderated and mediated model with non-linear effects," Research Policy, Elsevier, vol. 49(7).
    21. David J. Teece & Richard Rumelt & Giovanni Dosi & Sidney Winter, 2000. "Understanding Corporate Coherence: Theory and Evidence," Chapters, in: Innovation, Organization and Economic Dynamics, chapter 9, pages 264-293, Edward Elgar Publishing.
    22. Youngjin Yoo & Richard J. Boland & Kalle Lyytinen & Ann Majchrzak, 2012. "Organizing for Innovation in the Digitized World," Organization Science, INFORMS, vol. 23(5), pages 1398-1408, October.
    23. Usai, A. & Fiano, F. & Messeni Petruzzelli, A. & Paoloni, P. & Farina Briamonte, M. & Orlando, B., 2021. "Unveiling the impact of the adoption of digital technologies on firms’ innovation performance," Journal of Business Research, Elsevier, vol. 133(C), pages 327-336.
    24. Brantly Callaway & Pedro H. C. Sant'Anna, 2018. "Difference-in-Differences with Multiple Time Periods and an Application on the Minimum Wage and Employment," DETU Working Papers 1804, Department of Economics, Temple University.
    25. Pierre-Alexandre Balland, 2016. "Relatedness and the geography of innovation," Chapters, in: Richard Shearmu & Christophe Carrincazeaux & David Doloreux (ed.), Handbook on the Geographies of Innovation, chapter 6, pages 127-141, Edward Elgar Publishing.
    26. Ho, Daniel & Imai, Kosuke & King, Gary & Stuart, Elizabeth A., 2011. "MatchIt: Nonparametric Preprocessing for Parametric Causal Inference," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 42(i08).
    27. Pierre-Alexandre Balland, 2017. "Economic Geography in R: Introduction to the EconGeo package," Papers in Evolutionary Economic Geography (PEEG) 1709, Utrecht University, Department of Human Geography and Spatial Planning, Group Economic Geography, revised May 2017.
    28. Bas, Christian Le & Sierra, Christophe, 2002. "'Location versus home country advantages' in R&D activities: some further results on multinationals' locational strategies," Research Policy, Elsevier, vol. 31(4), pages 589-609, May.
    29. Nees Jan van Eck & Ludo Waltman, 2009. "How to normalize cooccurrence data? An analysis of some well‐known similarity measures," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 60(8), pages 1635-1651, August.
    30. Iain M. Cockburn & Rebecca Henderson & Scott Stern, 2018. "The Impact of Artificial Intelligence on Innovation: An Exploratory Analysis," NBER Chapters, in: The Economics of Artificial Intelligence: An Agenda, pages 115-146, National Bureau of Economic Research, Inc.
    31. Marte C.W. Solheim & Ron Boschma & Sverre Herstad, 2018. "Related variety, unrelated variety and the novelty content of firm innovation in urban and non-urban locations," Papers in Evolutionary Economic Geography (PEEG) 1836, Utrecht University, Department of Human Geography and Spatial Planning, Group Economic Geography, revised Oct 2018.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Cantner, Uwe & Grashof, Nils & Grebel, Thomas & Zhang, Xijie, 2023. "When Excellence is not Excellent: The Impact of the Excellence Initiative on the Relative Productivity of German Universities," MPRA Paper 118139, University Library of Munich, Germany.

    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. Matheus E. Leusin & Bjoern Jindra & Daniel S. Hain, 2021. "An evolutionary view on the emergence of Artificial Intelligence," Papers 2102.00233, arXiv.org.
    2. Sándor Juhász & Tom Broekel & Ron Boschma, 2021. "Explaining the dynamics of relatedness: The role of co‐location and complexity," Papers in Regional Science, Wiley Blackwell, vol. 100(1), pages 3-21, February.
    3. Jackie Krafft & Francesco Quatraro & Pier Saviotti, 2014. "Knowledge characteristics and the dynamics of technological alliances in pharmaceuticals: empirical evidence from Europe, US and Japan," Journal of Evolutionary Economics, Springer, vol. 24(3), pages 587-622, July.
    4. van Meeteren, Michiel & Trincado-Munoz, Francisco & Rubin, Tzameret H. & Vorley, Tim, 2022. "Rethinking the digital transformation in knowledge-intensive services: A technology space analysis," Technological Forecasting and Social Change, Elsevier, vol. 179(C).
    5. Pierre-Alexandre Balland & David L. Rigby, 2015. "The geography and evolution of complex knowledge," Papers in Evolutionary Economic Geography (PEEG) 1502, Utrecht University, Department of Human Geography and Spatial Planning, Group Economic Geography, revised Jan 2015.
    6. Ron Boschma & Ernest Miguelez & Rosina Moreno & Diego B. Ocampo-Corrales, 2021. "Technological breakthroughs in European regions: the role of related and unrelated combinations," Papers in Evolutionary Economic Geography (PEEG) 2118, Utrecht University, Department of Human Geography and Spatial Planning, Group Economic Geography, revised Jun 2021.
    7. Martijn van den Berge & Anet Weterings, 2014. "Relatedness in eco-technological development in European regions," Papers in Evolutionary Economic Geography (PEEG) 1413, Utrecht University, Department of Human Geography and Spatial Planning, Group Economic Geography, revised Jun 2014.
    8. Nils Grashof & Alexander Kopka, 2023. "Artificial intelligence and radical innovation: an opportunity for all companies?," Small Business Economics, Springer, vol. 61(2), pages 771-797, August.
    9. Giacomo Damioli & Björn Jindra & Annette Kristiansen, 2024. "International inventor teams and technological variety in multinational enterprises," The Journal of Technology Transfer, Springer, vol. 49(5), pages 1660-1695, October.
    10. Ron Boschma & Pierre-Alexandre Balland & Dieter Franz Kogler, 2015. "Relatedness and technological change in cities: the rise and fall of technological knowledge in US metropolitan areas from 1981 to 2010," Industrial and Corporate Change, Oxford University Press and the Associazione ICC, vol. 24(1), pages 223-250.
    11. Krafft Jackie & Quatraro Francesco & Colombelli Alessandra, 2011. "High Growth Firms and Technological Knowledge: Do gazelles follow exploration or exploitation strategies?," Department of Economics and Statistics Cognetti de Martiis LEI & BRICK - Laboratory of Economics of Innovation "Franco Momigliano", Bureau of Research in Innovation, Complexity and Knowledge, Collegio 201114, University of Turin.
    12. Nils Grashof & Stefano Basilico, 2023. "The dark side of green innovation? Green transition and regional inequality in Europe," Papers in Evolutionary Economic Geography (PEEG) 2314, Utrecht University, Department of Human Geography and Spatial Planning, Group Economic Geography, revised Jun 2023.
    13. Stefano Basilico & Holger Graf, 2023. "Bridging technologies in the regional knowledge space: measurement and evolution," Journal of Evolutionary Economics, Springer, vol. 33(4), pages 1085-1124, September.
    14. Dieter F. Kogler & Ronald B. Davies & Changjun Lee & Keungoui Kim, 2023. "Regional knowledge spaces: the interplay of entry-relatedness and entry-potential for technological change and growth," The Journal of Technology Transfer, Springer, vol. 48(2), pages 645-668, April.
    15. Dieter F. Kogler & Jürgen Essletzbichler & David L. Rigby, 2017. "The evolution of specialization in the EU15 knowledge space," Journal of Economic Geography, Oxford University Press, vol. 17(2), pages 345-373.
    16. Kolja Hesse & Dirk Fornahl, 2020. "Essential ingredients for radical innovations? The role of (un‐)related variety and external linkages in Germany," Papers in Regional Science, Wiley Blackwell, vol. 99(5), pages 1165-1183, October.
    17. Abbasiharofteh, Milad & Kogler, Dieter F. & Lengyel, Balázs, 2023. "Atypical combinations of technologies in regional co-inventor networks," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 52(10), pages 1-1.
    18. Seung Hwan Kim & Bogang Jun & Jeong-Dong Lee, 2023. "Technological relatedness: how do firms diversify their technology?," Scientometrics, Springer;Akadémiai Kiadó, vol. 128(9), pages 4901-4931, September.
    19. Silvia Rocchetta & Andrea Mina & Changjun Lee & Dieter F Kogler, 2022. "Technological knowledge spaces and the resilience of European regions," Journal of Economic Geography, Oxford University Press, vol. 22(1), pages 27-51.
    20. Pierre-Alexandre Balland & Ron Boschma & Joan Crespo & David L. Rigby, 2017. "Smart Specialization policy in the EU: Relatedness, Knowledge Complexity and Regional Diversification," Papers in Evolutionary Economic Geography (PEEG) 1717, Utrecht University, Department of Human Geography and Spatial Planning, Group Economic Geography, revised Jul 2017.

    More about this item

    Keywords

    Technological trajectory; Relatedness; Artificial Intelligence; Innovative performance;
    All these keywords.

    JEL classification:

    • D22 - Microeconomics - - Production and Organizations - - - Firm Behavior: Empirical Analysis
    • O14 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development - - - Industrialization; Manufacturing and Service Industries; Choice of Technology
    • O33 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Technological Change: Choices and Consequences; Diffusion Processes
    • L25 - Industrial Organization - - Firm Objectives, Organization, and Behavior - - - Firm Performance

    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:atv:wpaper:2201. 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: Matheus Eduardo Leusin (email available below). General contact details of provider: https://edirc.repec.org/data/iibrede.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.