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AI technology specialization and national competitiveness

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  • Youngsam Chun
  • Jisoo Hur
  • Junseok Hwang

Abstract

This study investigates the factors influencing specialization in artificial intelligence (AI) technology, a critical element of national competitiveness. We utilized a revealed comparative advantage matrix to evaluate technological specialization across countries and employed a three-way fixed-effect panel logit model to examine the relationship between AI specialization and its determinants. The results indicate that the development of AI technology is strongly contingent on a nation’s pre-existing technological capabilities, which significantly affect AI specialization in emerging domains. Additionally, this study reveals that scientific knowledge has a positive impact on technological specialization, highlighting the necessity of integrating scientific advancements with technological sectors. Although complex technologies positively influence AI specialization, their effect is less pronounced than that of scientific knowledge. This suggests that in rapidly advancing fields, such as AI, incorporating new scientific knowledge into related industries may be more advantageous than simply advancing existing technologies to outpace competitors. This insight points nations toward enhancing AI competitiveness in new areas, emphasizing the vital importance of both scientific and technological capabilities, and the integration of novel AI knowledge with established sectors. This research offers critical guidance for policymakers in less technologically and economically developed countries, as these nations may not have the technological infrastructure required to foster AI specialization through increased technical complexity.

Suggested Citation

  • Youngsam Chun & Jisoo Hur & Junseok Hwang, 2024. "AI technology specialization and national competitiveness," PLOS ONE, Public Library of Science, vol. 19(4), pages 1-26, April.
  • Handle: RePEc:plo:pone00:0301091
    DOI: 10.1371/journal.pone.0301091
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    1. Bruce Kogut & Udo Zander, 1992. "Knowledge of the Firm, Combinative Capabilities, and the Replication of Technology," Organization Science, INFORMS, vol. 3(3), pages 383-397, August.
    2. Adam B. Jaffe & Manuel Trajtenberg & Rebecca Henderson, 1993. "Geographic Localization of Knowledge Spillovers as Evidenced by Patent Citations," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 108(3), pages 577-598.
    3. Arthur, W Brian, 1989. "Competing Technologies, Increasing Returns, and Lock-In by Historical Events," Economic Journal, Royal Economic Society, vol. 99(394), pages 116-131, March.
    4. Gloria Cicerone & Alessandra Faggian & Sandro Montresor & Francesco Rentocchini, 2023. "Regional artificial intelligence and the geography of environmental technologies: does local AI knowledge help regional green-tech specialization?," Regional Studies, Taylor & Francis Journals, vol. 57(2), pages 330-343, February.
    5. Liu, Jun & Chang, Huihong & Forrest, Jeffrey Yi-Lin & Yang, Baohua, 2020. "Influence of artificial intelligence on technological innovation: Evidence from the panel data of china's manufacturing sectors," Technological Forecasting and Social Change, Elsevier, vol. 158(C).
    6. Deborah Strumsky & José Lobo & Sander van der Leeuw, 2012. "Using patent technology codes to study technological change," Economics of Innovation and New Technology, Taylor & Francis Journals, vol. 21(3), pages 267-286, April.
    7. Bianchini, Stefano & Müller, Moritz & Pelletier, Pierre, 2022. "Artificial intelligence in science: An emerging general method of invention," Research Policy, Elsevier, vol. 51(10).
    8. Bronwyn H. Hall & Adam B. Jaffe & Manuel Trajtenberg, 2001. "The NBER Patent Citation Data File: Lessons, Insights and Methodological Tools," NBER Working Papers 8498, National Bureau of Economic Research, Inc.
    9. Stefano Bianchini & Moritz Müller & Pierre Pelletier, 2022. "Artificial intelligence in science: An emerging general method of invention," Post-Print hal-03958025, HAL.
    10. Roberto Antonietti & Sandro Montresor, 2021. "Going beyond Relatedness: Regional Diversification Trajectories and Key Enabling Technologies (KETs) in Italian Regions," Economic Geography, Taylor & Francis Journals, vol. 97(2), pages 187-207, March.
    11. Julie Callaert & Maikel Pellens & Bart Looy, 2014. "Sources of inspiration? Making sense of scientific references in patents," Scientometrics, Springer;Akadémiai Kiadó, vol. 98(3), pages 1617-1629, March.
    12. Neil Savage, 2020. "The race to the top among the world’s leaders in artificial intelligence," Nature, Nature, vol. 588(7837), pages 102-104, December.
    13. Sandro Montresor & Francesco Quatraro, 2020. "Green technologies and Smart Specialisation Strategies: a European patent-based analysis of the intertwining of technological relatedness and key enabling technologies," Regional Studies, Taylor & Francis Journals, vol. 54(10), pages 1354-1365, October.
    14. Patel, Pari & Pavitt, Keith, 1997. "The technological competencies of the world's largest firms: Complex and path-dependent, but not much variety," Research Policy, Elsevier, vol. 26(2), pages 141-156, May.
    15. Joel Klinger & Juan Mateos-Garcia & Konstantinos Stathoulopoulos, 2021. "Deep learning, deep change? Mapping the evolution and geography of a general purpose technology," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(7), pages 5589-5621, July.
    16. Stuart, Toby & Sorenson, Olav, 2003. "The geography of opportunity: spatial heterogeneity in founding rates and the performance of biotechnology firms," Research Policy, Elsevier, vol. 32(2), pages 229-253, February.
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