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The spatial network structure of energy-saving and carbon-reducing technological innovation in China

Jing Liu et al.

Innovation and Green Development2026https://doi.org/10.1016/j.igd.2026.100348article
ABDC B
Weight
0.50

Abstract

The innovation of energy-saving and carbon-reduction technologies has become a key driver for the green and low-carbon transformation of economic development. This paper utilizes panel data from 291 cities in China from 2012 to 2023 to construct a spatial correlation network for energy-saving and carbon-reduction technology innovation through a gravity model, applying social network analysis methods to analyze the spatial structural characteristics. The study finds that the spatial correlation and network stability of energy-saving and carbon-reduction technology innovation in China have strengthened year by year, but the overall correlation intensity remains relatively low. Developed cities in the eastern region are at the core of the network, playing the roles of “central actors”, with prominent intermediary functions. Within the Yangtze River Delta and Beijing-Tianjin-Hebei urban agglomerations, four major sectors have formed with distinct responsibilities, and their interconnections dominate the network structure. This research provides theoretical support for designing regional collaborative innovation policies. • First, this paper focuses on the innovation of energy-saving and carbon-reduction technologies, promoting empirical research progress in the subfield of green and low-carbon technology innovation under the background of the "dual carbon" goals, thereby laying a solid foundation for subsequent related studies. • Second, a spatial association network is constructed using a gravity model, which effectively accounts for the combined influence of economic and geographical proximity to measure inter-regional spatial interactions accurately. • Third, the paper provides a comprehensive analysis of the network's structural characteristics, systematically examining macro-level diffusion patterns among innovation sectors and micro-level associative modes between regions, thus offering a complete picture from the overall architecture to local linkages.

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https://doi.org/https://doi.org/10.1016/j.igd.2026.100348

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@article{jing2026,
  title        = {{The spatial network structure of energy-saving and carbon-reducing technological innovation in China}},
  author       = {Jing Liu et al.},
  journal      = {Innovation and Green Development},
  year         = {2026},
  doi          = {https://doi.org/https://doi.org/10.1016/j.igd.2026.100348},
}

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The spatial network structure of energy-saving and carbon-reducing technological innovation in China

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Evidence weight

0.50

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.50 × 0.4 = 0.20
M · momentum0.50 × 0.15 = 0.07
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

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