Spatial-temporal dynamic evolution and influencing factors of county innovation level evidence: based on the patent data of county scale in Hebei Province

Based on patent data spanning 2000 to 2020 from 168 counties in Hebei Province, this study investigates the spatio-temporal evolution of county-level innovation and its determinants using methodologies such as standard deviation ellipses, spatial Markov chains, spatial autocorrelation, and geographical detectors. The findings indicate: (1) A rising trend in overall innovation levels across Hebei's counties, with a shift in innovation structure from low concentration to multi-type equilibrium. Core areas of county-level innovation, centered around Shijiazhuang, Langfang, and Tangshan, are gradually forming spatially, transitioning from a dispersed “point-like” pattern to a “concentrated and contiguous” distribution. (2) The “Northeast-Southwest” innovation pattern at the county level remains stable, but exhibits unstable focal points shifting predominantly southwestward, indicative of a trend towards following innovative resources and emerging industries. (3) The spatial distribution of innovation levels in counties is shaped by multiple factors, including temporal dynamics and economic development models, reflecting noticeable shifts over time.

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Published
2024-11-27
DOI
https://doi.org/10.1117/12.3048725
Primary Topic
Regional Development and Environment
Type
article
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Spatial-temporal dynamic evolution and influencing factors of county innovation level evidence: based on the patent data of county scale in Hebei Province

Hongmei Qi, Zhen‐Zhong Huang, Lulu Zhang, Chao Zhang
Regional Development and Environment
article

Spatial-temporal dynamic evolution and influencing factors of county innovation level evidence: based on the patent data of county scale in Hebei Province

Hongmei Qi, Zhen‐Zhong Huang, Lulu Zhang, Chao Zhang
article en

Abstract

Based on patent data spanning 2000 to 2020 from 168 counties in Hebei Province, this study investigates the spatio-temporal evolution of county-level innovation and its determinants using methodologies such as standard deviation ellipses, spatial Markov chains, spatial autocorrelation, and geographical detectors. The findings indicate: (1) A rising trend in overall innovation levels across Hebei's counties, with a shift in innovation structure from low concentration to multi-type equilibrium. Core areas of county-level innovation, centered around Shijiazhuang, Langfang, and Tangshan, are gradually forming spatially, transitioning from a dispersed “point-like” pattern to a “concentrated and contiguous” distribution. (2) The “Northeast-Southwest” innovation pattern at the county level remains stable, but exhibits unstable focal points shifting predominantly southwestward, indicative of a trend towards following innovative resources and emerging industries. (3) The spatial distribution of innovation levels in counties is shaped by multiple factors, including temporal dynamics and economic development models, reflecting noticeable shifts over time.

Hebei University of Economics and Business (CN)
Industry, innovation and infrastructure
Openalex Percentile: Top 66%
Regional Development and Environment
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Spatial-temporal dynamic evolution and influencing factors of county innovation level evidence: based on the patent data of county scale in Hebei Province — Hongmei Qi, Zhen‐Zhong Huang, et al. · (2024) | TGRS Research Map | TGRS