A data-driven global innovation system approach and the rise of China’s artificial intelligence industry
Zhen Yu,
Zheng Liang and
Lan Xue
Regional Studies, 2022, vol. 56, issue 4, 619-629
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.
Date: 2022
References: Add references at CitEc
Citations: View citations in EconPapers (2)
Downloads: (external link)
http://hdl.handle.net/10.1080/00343404.2021.1954610 (text/html)
Access to full text is restricted to subscribers.
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:taf:regstd:v:56:y:2022:i:4:p:619-629
Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/CRES20
DOI: 10.1080/00343404.2021.1954610
Access Statistics for this article
Regional Studies is currently edited by Ivan Turok
More articles in Regional Studies from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().