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The characteristics and influencing factors of spatial network of city-based innovation correlation in China: from the perspective of high tech zones
In the context of “space of flows”, city-based innovation correlation in driving economic growth is no longer limited to the traditional hierarchical structure. It is of great significance to explore Chinese cities innovation association network from the perspective of high-tech zones which gather a...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10539513/ https://www.ncbi.nlm.nih.gov/pubmed/37770521 http://dx.doi.org/10.1038/s41598-023-43402-5 |
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author | Zhang, Hong Jiang, Lili Zhou, Jia Chu, Nanchen Li, Fengjiao |
author_facet | Zhang, Hong Jiang, Lili Zhou, Jia Chu, Nanchen Li, Fengjiao |
author_sort | Zhang, Hong |
collection | PubMed |
description | In the context of “space of flows”, city-based innovation correlation in driving economic growth is no longer limited to the traditional hierarchical structure. It is of great significance to explore Chinese cities innovation association network from the perspective of high-tech zones which gather a large number of innovation resources. Here our report is to provide new ideas for improving the innovation capability of high-tech zones and accelerating the construction of Chinese high-quality innovation system. Here we take 142 cities with high-tech zones as research samples, and explore the characteristics and influencing factors of spatial network of city-based innovation correlation in China, through modified gravity modelsocial, network analysis and QAP analysis. The results show that city-based innovation network is not closely connected, the number of redundant connection channels is low efficiency, showing a four-level spatial pattern of “Z” shaped spindle. Among them, degree centrality of cities in eastern China is higher than that in the western region, the core cities in central China play a bridging role, and western remote cities are easily affected by related cities. Moreover, there are four innovation cohesion subgroups, including the northern hinterland subgroup, the eastern coastal subgroup, the southern subgroup and the western cooperation subgroup. Furthermore, the results of the influencing factors analysis show the differences in administrative level, economic development level, openness to the outside world, and investment in technology are conducive to the innovation association between cities, while the similarities in spatial adjacency and industrial structure will promote the strong innovation association between cities. |
format | Online Article Text |
id | pubmed-10539513 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-105395132023-09-30 The characteristics and influencing factors of spatial network of city-based innovation correlation in China: from the perspective of high tech zones Zhang, Hong Jiang, Lili Zhou, Jia Chu, Nanchen Li, Fengjiao Sci Rep Article In the context of “space of flows”, city-based innovation correlation in driving economic growth is no longer limited to the traditional hierarchical structure. It is of great significance to explore Chinese cities innovation association network from the perspective of high-tech zones which gather a large number of innovation resources. Here our report is to provide new ideas for improving the innovation capability of high-tech zones and accelerating the construction of Chinese high-quality innovation system. Here we take 142 cities with high-tech zones as research samples, and explore the characteristics and influencing factors of spatial network of city-based innovation correlation in China, through modified gravity modelsocial, network analysis and QAP analysis. The results show that city-based innovation network is not closely connected, the number of redundant connection channels is low efficiency, showing a four-level spatial pattern of “Z” shaped spindle. Among them, degree centrality of cities in eastern China is higher than that in the western region, the core cities in central China play a bridging role, and western remote cities are easily affected by related cities. Moreover, there are four innovation cohesion subgroups, including the northern hinterland subgroup, the eastern coastal subgroup, the southern subgroup and the western cooperation subgroup. Furthermore, the results of the influencing factors analysis show the differences in administrative level, economic development level, openness to the outside world, and investment in technology are conducive to the innovation association between cities, while the similarities in spatial adjacency and industrial structure will promote the strong innovation association between cities. Nature Publishing Group UK 2023-09-28 /pmc/articles/PMC10539513/ /pubmed/37770521 http://dx.doi.org/10.1038/s41598-023-43402-5 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Article Zhang, Hong Jiang, Lili Zhou, Jia Chu, Nanchen Li, Fengjiao The characteristics and influencing factors of spatial network of city-based innovation correlation in China: from the perspective of high tech zones |
title | The characteristics and influencing factors of spatial network of city-based innovation correlation in China: from the perspective of high tech zones |
title_full | The characteristics and influencing factors of spatial network of city-based innovation correlation in China: from the perspective of high tech zones |
title_fullStr | The characteristics and influencing factors of spatial network of city-based innovation correlation in China: from the perspective of high tech zones |
title_full_unstemmed | The characteristics and influencing factors of spatial network of city-based innovation correlation in China: from the perspective of high tech zones |
title_short | The characteristics and influencing factors of spatial network of city-based innovation correlation in China: from the perspective of high tech zones |
title_sort | characteristics and influencing factors of spatial network of city-based innovation correlation in china: from the perspective of high tech zones |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10539513/ https://www.ncbi.nlm.nih.gov/pubmed/37770521 http://dx.doi.org/10.1038/s41598-023-43402-5 |
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