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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 boundaries]

Author

Listed:
  • Zhen Yu
  • Zheng Liang
  • Peiyi Wu

Abstract

With the rise of artificial intelligence (AI), data are widely viewed as the “new oil”. However, data substantially differ from conventional resources in the sense that they are important not only for production but also for knowledge development and public policymaking. This article explores whether and how data reshape government–industry–university relations in the era of AI. Taking China’s AI innovation system as a case, this article investigates the dynamics of actor relations in the business subsystem, knowledge subsystem, and regulatory subsystem. The change of the fundamental input from physical resources to virtual data in AI innovation systems has significantly transformed the relations among industry, state, and academia, and digital platforms are playing an increasingly important role in business value creation, knowledge generation, and regulation formation due to their control of valuable data and frontier expertise in the context of uncertainty.

Suggested Citation

  • 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.
  • Handle: RePEc:oup:indcch:v:30:y:2021:i:1:p:251-267.
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    File URL: http://hdl.handle.net/10.1093/icc/dtaa063
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    Citations

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    Cited by:

    1. Igna, Ioana & Venturini, Francesco, 2023. "The determinants of AI innovation across European firms," Research Policy, Elsevier, vol. 52(2).
    2. Andrea Borsato & André Lorentz, 2023. "Data production and the coevolving AI trajectories: an attempted evolutionary model," Journal of Evolutionary Economics, Springer, vol. 33(5), pages 1427-1472, November.
    3. Gherhes, Cristian & Yu, Zhen & Vorley, Tim & Xue, Lan, 2023. "Technological trajectories as an outcome of the structure-agency interplay at the national level: Insights from emerging varieties of AI," World Development, Elsevier, vol. 168(C).
    4. Katrin Hussinger & Lorenzo Palladini, 2024. "Information accessibility and knowledge creation: impact of Google’s withdrawal from China on scientific research," DEM Discussion Paper Series 24-05, Department of Economics at the University of Luxembourg.
    5. Katrin Hussinger & Lorenzo Palladini, 2024. "Information accessibility and knowledge creation: the impact of Google’s withdrawal from China on scientific research," Industry and Innovation, Taylor & Francis Journals, vol. 31(6), pages 753-783, July.
    6. Li, Daitian & Malerba, Franco, 2024. "Technological change and the evolution of the links across sectoral systems: The case of mobile communications," Technovation, Elsevier, vol. 130(C).

    More about this item

    JEL classification:

    • L50 - Industrial Organization - - Regulation and Industrial Policy - - - General
    • O30 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - General

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