Spatial mechanisms of regional innovation mobility in China

Xing GAO, Keyu ZHAI*

*Corresponding author for this work

Research output: Journal PublicationsJournal Article (refereed)peer-review

7 Citations (Scopus)

Abstract

Against the background of rapid improvement in economic growth and innovation capabilities, China is facing with development gaps and regional disparities. Based on the solid theoretical foundations and literature review, we aim to investigate the spatial mechanisms of regional innovation mobility at China’s provincial scale. Using patent counts from 2000 to 2015 modelled by Geographical Weighted Regression (GWR), the study examines the determinants of regional innovation mobility from the social, economic, natural and institutional perspectives. Through highlighting innovation mobility, this study regards innovation as a dynamic economic phenomenon rather than a static measure, and visualization results are clearly presented to display the overall landscape of China’s innovation mobility. Furthermore, in the analysis, we consider the effect of physical factors on regional innovation and empirically examine their roles. Our findings indicate that the relationships between regional innovation mobility and its determinants are spatially nonstationary and heterogenic. The study is of great significance to understand regional development differences and formulate reasonable regional policies.

Original languageEnglish
Pages (from-to)247-270
Number of pages24
JournalSocial Indicators Research
Volume156
Issue number1
Early online date24 Feb 2021
DOIs
Publication statusPublished - Jul 2021
Externally publishedYes

Bibliographical note

Publisher Copyright:
© 2021, The Author(s), under exclusive licence to Springer Nature B.V. part of Springer Nature.

Keywords

  • China
  • Disparities
  • GWR model
  • Regional innovation mobility
  • Spatial mechanisms
  • Visualization maps

Fingerprint

Dive into the research topics of 'Spatial mechanisms of regional innovation mobility in China'. Together they form a unique fingerprint.

Cite this