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27 November 2024 Spatial-temporal dynamic evolution and influencing factors of county innovation level evidence: based on the patent data of county scale in Hebei Province
Lulu Zhang, Hongmei Qi, Zhenzhong Huang, Chao Zhang
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Proceedings Volume 13402, International Conference on Remote Sensing, Mapping, and Geographic Information Systems (RSMG 2024); 134023O (2024) https://doi.org/10.1117/12.3048725
Event: International Conference on Remote Sensing, Mapping, and Geographic Information Systems (RSMG 2024), 2024, Zhengzhou, China
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.
(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.
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Lulu Zhang, Hongmei Qi, Zhenzhong Huang, and Chao Zhang "Spatial-temporal dynamic evolution and influencing factors of county innovation level evidence: based on the patent data of county scale in Hebei Province", Proc. SPIE 13402, International Conference on Remote Sensing, Mapping, and Geographic Information Systems (RSMG 2024), 134023O (27 November 2024); https://doi.org/10.1117/12.3048725
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KEYWORDS
Patents
Reflection
Autocorrelation
Data modeling
Statistical analysis
Standards development
Analytical research
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