IDEAS home Printed from https://ideas.repec.org/a/taf/regstd/v56y2022i4p619-629.html
   My bibliography  Save this article

A data-driven global innovation system approach and the rise of China’s artificial intelligence industry

Author

Listed:
  • Zhen Yu
  • Zheng Liang
  • Lan Xue

Abstract

Building upon the global innovation system (GIS) framework, this paper develops an analytical approach to incorporate data as a foundation-level resource in data-driven innovation systems and to unravel how the interplay of system resources’ spatial characteristics, multi-scalar institutions and actor strategies leads to the emergence of China’s artificial intelligence industry. China’s loose institutional regime significantly facilitates the formation of the market, legitimacy and data, while entrepreneurs and digital platforms are the key actors coupling system resources to China’s innovation system. As data become a critical resource, actors controlling data develop institutional power to shape the formation of the data-driven industry.

Suggested Citation

  • Zhen Yu & Zheng Liang & Lan Xue, 2022. "A data-driven global innovation system approach and the rise of China’s artificial intelligence industry," Regional Studies, Taylor & Francis Journals, vol. 56(4), pages 619-629, April.
    • Handle: RePEc:taf:regstd:v:56:y:2022:i:4:p:619-629
    DOI: 10.1080/00343404.2021.1954610
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1080/00343404.2021.1954610
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1080/00343404.2021.1954610?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
    ---><---

    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. Liu, Min & Liu, Hong-Fei & Lee, Chien-Chiang, 2024. "An empirical study on the response of the energy market to the shock from the artificial intelligence industry," Energy, Elsevier, vol. 288(C).

    More about this item

    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:taf:regstd:v:56:y:2022:i:4:p:619-629. 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: Chris Longhurst (email available below). General contact details of provider: http://www.tandfonline.com/CRES20 .

    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.