Innovation network, knowledge spillover, and urban green economic performance

With the development of transport and information technology (IT), urban innovation linkages are becoming increasingly close and are key factors in regional economic growth. Despite previous studies analyzing urban network characteristics, structures, and factors that influence them, there has been little exploration of their socioeconomic effects. Based on unique patent transaction data, this study analyzes the spatiotemporal evolution of urban innovation networks and their impacts and internal mechanisms on regional green total factor productivity (GTFP) using social network analysis, data envelopment analysis, and a negative binomial model. It was found that (1) the enhancement of intercity innovation linkages and their networked development have significantly improved urban GTFP and the innovation network’s embeddedness helps obtain network externalities to improve urban GTFP. (2) The innovation network promotes inter-regional production factor flow and optimal allocation and generates knowledge spillover effects to improve green technology innovation capacity, thus improving urban GTFP. (3) Spatial heterogeneity exists in the impact of the innovation network on the GTFP of different regions and economically developed big cities by gathering more innovation resources, forming closer innovation links, improving the level of green technology innovation and production efficiency, and contributing to urban GTFP. Economically developed big cities can have more innovation resources and form closer innovation links, improve green technology innovation and production efficiency, and have a stronger promotional effect on improving urban GTFP.

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Publication Details

Journal
Frontiers in Physics
Published
2025-02-26
DOI
https://doi.org/10.3389/fphy.2025.1537110
Citations
4
Primary Topic
Innovation Diffusion and Forecasting
Type
article
Field-Weighted Citation Impact
8.43

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article

Innovation network, knowledge spillover, and urban green economic performance

Dan Zhao, Chenghui Tang, Xiaolin Huang
4 citations
Frontiers in Physics
Innovation Diffusion and Forecasting
8.43
article

Innovation network, knowledge spillover, and urban green economic performance

Dan Zhao, Chenghui Tang, Xiaolin Huang
article en
4 citations

Abstract

With the development of transport and information technology (IT), urban innovation linkages are becoming increasingly close and are key factors in regional economic growth. Despite previous studies analyzing urban network characteristics, structures, and factors that influence them, there has been little exploration of their socioeconomic effects. Based on unique patent transaction data, this study analyzes the spatiotemporal evolution of urban innovation networks and their impacts and internal mechanisms on regional green total factor productivity (GTFP) using social network analysis, data envelopment analysis, and a negative binomial model. It was found that (1) the enhancement of intercity innovation linkages and their networked development have significantly improved urban GTFP and the innovation network’s embeddedness helps obtain network externalities to improve urban GTFP. (2) The innovation network promotes inter-regional production factor flow and optimal allocation and generates knowledge spillover effects to improve green technology innovation capacity, thus improving urban GTFP. (3) Spatial heterogeneity exists in the impact of the innovation network on the GTFP of different regions and economically developed big cities by gathering more innovation resources, forming closer innovation links, improving the level of green technology innovation and production efficiency, and contributing to urban GTFP. Economically developed big cities can have more innovation resources and form closer innovation links, improve green technology innovation and production efficiency, and have a stronger promotional effect on improving urban GTFP.

Frontiers in PhysicsVol. 13
Open University of China (CN), Shanghai University of Finance and Economics (CN), Gannan Normal University (CN), Beijing Open University (CN)
Shanghai Office of Philosophy and Social Science
Openalex Percentile: Top 3%
Innovation Diffusion and Forecasting
8.43
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