Research on Innovation Network Features of Patent-Intensive Industry Clusters and Their Evolution

In the contemporary economic landscape shaped by globalization and digital transformation, patent-intensive industries have emerged as critical engines for enhancing national competitiveness. This study analyzed 98,464 collaborative patent application records (2012–2023) from listed companies in patent-intensive sectors, sourced from the China National Intellectual Property Administration (CNIPA) database. Through kernel density estimation, social network analysis, and community detection techniques, we examined the evolutionary trajectories of innovation networks and spatial patterns within these industrial clusters. Our findings indicate a notable spatial agglomeration trend in patent-intensive industries, exhibiting a prominent “core-periphery” structural feature. The core nodes of this cluster network closely align with economically developed regions, and the network structure has gradually shifted from a triangular framework supported by Beijing-Tianjin-Hebei, Yangtze River Delta, and Pearl River Delta to a diversified multilateral framework. Moreover, the community structure of the collaborative network within China’s patent-intensive industrial clusters exhibits distinct characteristics driven by technological relevance and strategic synergy, rather than strictly adhering to the principle of geographical proximity. These discoveries not only enrich the application of innovation network theory in the specific context of China, but also provide valuable guidance for cluster enterprises in selecting partners and achieving collaborative innovation.

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Publication Details

Journal
Systems
Published
2025-09-10
DOI
https://doi.org/10.3390/systems13090795
Citations
2
Primary Topic
Entrepreneurship Studies and Influences
Type
article
Field-Weighted Citation Impact
5.52
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article

Research on Innovation Network Features of Patent-Intensive Industry Clusters and Their Evolution

Lei Jiang, Lanqing Ge, Deli Cheng, Chunyan Li
2 citations
Systems
Entrepreneurship Studies and Influences
5.52
article

Research on Innovation Network Features of Patent-Intensive Industry Clusters and Their Evolution

Lei Jiang, Lanqing Ge, Deli Cheng, Chunyan Li
article en
2 citations

Abstract

In the contemporary economic landscape shaped by globalization and digital transformation, patent-intensive industries have emerged as critical engines for enhancing national competitiveness. This study analyzed 98,464 collaborative patent application records (2012–2023) from listed companies in patent-intensive sectors, sourced from the China National Intellectual Property Administration (CNIPA) database. Through kernel density estimation, social network analysis, and community detection techniques, we examined the evolutionary trajectories of innovation networks and spatial patterns within these industrial clusters. Our findings indicate a notable spatial agglomeration trend in patent-intensive industries, exhibiting a prominent “core-periphery” structural feature. The core nodes of this cluster network closely align with economically developed regions, and the network structure has gradually shifted from a triangular framework supported by Beijing-Tianjin-Hebei, Yangtze River Delta, and Pearl River Delta to a diversified multilateral framework. Moreover, the community structure of the collaborative network within China’s patent-intensive industrial clusters exhibits distinct characteristics driven by technological relevance and strategic synergy, rather than strictly adhering to the principle of geographical proximity. These discoveries not only enrich the application of innovation network theory in the specific context of China, but also provide valuable guidance for cluster enterprises in selecting partners and achieving collaborative innovation.

SystemsVol. 13(9)
Tongji University (CN), Guangzhou Institute of Geography (CN)
Openalex Percentile: Top 5%
Entrepreneurship Studies and Influences
5.52
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Research on Innovation Network Features of Patent-Intensive Industry Clusters and Their Evolution — Lei Jiang, Lanqing Ge, et al. · Systems (2025) | TGRS Research Map | TGRS