IDEAS home Printed from https://ideas.repec.org/a/oup/indcch/v30y2021i1p251-267..html
   My bibliography  Save this article

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.
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1093/icc/dtaa063
    Download Restriction: Access to full text is restricted to subscribers.
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    Citations

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


    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: the impact of Google’s withdrawal from China on scientific research," Industry and Innovation, Taylor & Francis Journals, vol. 31(6), pages 753-783, July.
    5. 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

    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:oup:indcch:v:30:y:2021:i:1:p:251-267.. 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.

    We have no bibliographic references for this item. You can help adding them by using 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: Oxford University Press (email available below). General contact details of provider: https://academic.oup.com/icc .

    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.