| Title | Features of Industrial Green Technology Innovation in the Yangtze River Economic Belt of China Based on Spatial Correlation Network |
|---|---|
| ID_Doc | 30669 |
| Authors | Yao, MC; Li, ZQ; Wang, YF |
| Title | Features of Industrial Green Technology Innovation in the Yangtze River Economic Belt of China Based on Spatial Correlation Network |
| Year | 2023 |
| Published | Sustainability, 15, 7 |
| Abstract | A generic phrase for technical and managerial innovation geared toward environmental conservation is "green-technology innovation." It is essential to attain ecologically friendly development that promotes economic progress. Promoting the combined growth of the economy, society, and environment is extremely important. The industrial-green-technology innovation efficiency of 110 cities in the Yangtze River Economic Belt is calculated using the Sup-SBM model from 2011 to 2021 while considering undesirable output. The modified gravity model is then used to convert the attribute data of industrial-green-technology innovation efficiency into relational data. The Yangtze River Economic Belt uses the social-network-analysis (SNA) approach to investigate the geographical correlation-network properties of industrial-green-technology innovation efficiency. The findings demonstrate the following: (1) There is a rising trend in the degree of industrial-green-technology innovation efficiency between different cities in the Yangtze River Economic Belt, and this pattern is known as "three plates." (2) The examination of network characteristics reveals an indigenous core-edge structure in space, with the network density of the Yangtze River Economic Belt displaying an increasing trend over the research period. (3) Individual characteristic analysis reveals that although the innovation-efficiency network tends to be flat, the degree centrality and closeness centrality of industrial-green-technology innovation efficiency in the Yangtze River Economic Belt indicate an upward trend over the research period. In addition, Chengdu in the upstream region, Wuhan in the center, and Shanghai in the downstream area serve as bridge and intermediary nodes in the spatial correlation network. (4) Block-model analysis reveals a close spatial link between blocks. A more complex and durable spatial link is now possible because of the spatial relationship of green-innovation efficiency in cities, which has shattered the boundaries imposed by traditional geographic space. The Yangtze River Economic Belt will be jointly promoted by several of the policy recommendations in this paper, aligning with that. |
| https://www.mdpi.com/2071-1050/15/7/6033/pdf?version=1680184605 |
Similar Articles
| ID | Score | Article |
|---|---|---|
30546
|
Yao, MC; Duan, JJ; Wang, QS Spatial and Temporal Evolution Analysis of Industrial Green Technology Innovation Efficiency in the Yangtze River Economic Belt(2022)International Journal Of Environmental Research And Public Health, 19, 11 | |
| 30260
|
Fan, DC; Wu, XL Spatial Correlation Network Analysis of Industrial Green Technology Innovation Efficiency in China(2023)Systems, 11, 5 | |
| 35723
|
Long, RY; Guo, HY; Zheng, DT; Chang, RH; Na, SY RETRACTED: Research on the Measurement, Evolution, and Driving Factors of Green Innovation Efficiency in Yangtze River Economic Belt: A Super-SBM and Spatial Durbin Model (Retracted Article)(2020) | |
| 35531
|
Fan, JD; Xiao, ZH Analysis of spatial correlation network of China's green innovation(2021) | |
| 35817
|
Cai, SK; Hu, BX; Guo, M Research on spatial-temporal heterogeneity of driving factors of green innovation efficiency in Yangtze River Delta urban agglomeration-empirical test based on the Geographically Weighted Regression model(2024) | |
| 30789
|
Yao, MC; Zhang, RJ; Dong, HZ Analysis of the Spatiotemporal Convergence Effect and Influencing Factors of Industrial Green Technology Innovation Efficiency in the Yangtze River Economic Belt in China(2024) | |
| 62713
|
Zhang, XF; Wu, XM; Zhou, WH; Fu, NN Research on the green innovation effect of digital economy network - Empirical evidence from the manufacturing industry in the Yangtze River Delta(2024) | |
| 33245
|
Zhuang, H; Lin, HX; Zhong, KY Spatial spillover effects and driving factors of regional green innovation efficiency in china from a network perspective(2022) | |
| 35584
|
Liu, YQ; Shao, XY; Tang, MP; Lan, HX Spatio-temporal evolution of green innovation network and its multidimensional proximity analysis: Empirical evidence from China(2021) | |
| 30235
|
He, YZ; Wang, Y; Quan, CG Coupled Coordination and Drivers of Green Technology Innovation and Carbon Emission Efficiency(2024)Sustainability, 16, 7 |