JOURNAL ARTICLE

Technological Innovation and Industrial Development in China.

  • Published In: Tijdschrift voor Economische en Sociale Geografie (Journal of Economic & Social Geography), 2025, v. 116, n. 3. P. 297 1 of 3

  • Database: Academic Search Ultimate 2 of 3

  • Authored By: Li, Dandan; Wei, Yehua Dennis 3 of 3

Abstract

This paper analyzes the impact of technological innovation on industrial development through a study of patent‐intensive industry (PII) in the Yangtze River Delta, China, with the following findings: (1) Technological innovation in PII has greatly improved and has evolved from agglomeration to dispersion. Moreover, the spatial inequality of technological innovation in PII is significant, with Suzhou replacing Shanghai as the core. (2) The development of PII is the synergetic result of local technology agglomeration and diversification, and their relationship exhibits a nonlinear inverted U‐shaped pattern. The effect of technology specialization on PII development is negative. The enhancement of marketability in the local and neighbouring areas has a significant positive impact on the development of PII. (3) Administrative boundaries have little effect on technology spillover, but a negative neighbourhood effect on KIBS spillover. Technology accumulation in adjacent areas has a significant positive spatial spillover effect on local PII development. [ABSTRACT FROM AUTHOR]

Additional Information

  • Source:Tijdschrift voor Economische en Sociale Geografie (Journal of Economic & Social Geography). 2025/07, Vol. 116, Issue 3, p297
  • Document Type:Article
  • Subject Area:Geography and Cartography
  • Publication Date:2025
  • ISSN:0040-747X
  • DOI:10.1111/tesg.70004
  • Accession Number:186252485
  • Copyright Statement:Copyright of Tijdschrift voor Economische en Sociale Geografie (Journal of Economic & Social Geography) is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

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