| Title |
Exploration and future trends on spatial correlation of green innovation efficiency in strategic emerging industries under the digital economy: A social network analysis |
| ID_Doc |
62761 |
| Authors |
Li, XM; Zhang, YC; Zhou, SW; Zhao, ZG; Zhao, YF |
| Title |
Exploration and future trends on spatial correlation of green innovation efficiency in strategic emerging industries under the digital economy: A social network analysis |
| Year |
2024 |
| Published |
|
| DOI |
10.1016/j.jenvman.2024.121005 |
| Abstract |
With digital technological change and the increasing frequency of interregional innovation links, the spatial correlation and diversity of strategic emerging industries' green innovation efficiency (SEI-GIE) need to be explored in depth. This paper innovatively constructs the SEI-GIE input-output index system under digital economy. The proposed grey model FINGBM(1,1) with omega-order accumulation and weighted initial value optimization realizes effective prediction of 7 input-output indicators of 30 provinces in China from 2021 to 2025. Super-SBM-DEA, gravity model, and social network analysis are applied to explore spatial network structure's dynamic process of SEI-GIE from 12th to 14th Five-Year-Plan period (2011-2025). Empirical results show that (1) Under the effect of digital economy, the SEI-GIE in China generally shows a U-shaped fluctuation trend, in which the growth trend in the central region is obvious, and the western region shows significant fluctuations. (2) The spatial correlation network of SEI-GIE presents a complex and stable center-periphery circle. Particularly, the overall increase in network efficiency highlights the strong small-world characteristics. (3) Beijing, Shanghai, Zhejiang and Jiangsu have always been in the leading core position, with strong influence and control; And Tianjin's core position in the network will decline. Additionally, Guangxi and Chongqing have great potential, but Guangdong needs to strengthen its radiation effect. (4) Block model shows that plate-I (Beijing, Tianjin) receive spatial spillovers from others, while plates-III,IV have significant spillover effects. This study provides theoretical reference for policymakers from a network perspective to promote development of China's SEI-GIE. |
| Author Keywords |
Strategic emerging industries; Green innovation efficiency; Digital economy; Spatial correlation network; Social network analysis; Grey Bernoulli model |
| Index Keywords |
Index Keywords |
| Document Type |
Other |
| Open Access |
Open Access |
| Source |
Science Citation Index Expanded (SCI-EXPANDED) |
| EID |
WOS:001239611000001 |
| WoS Category |
Environmental Sciences |
| Research Area |
Environmental Sciences & Ecology |
| PDF |
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