| Title |
Spatial and Temporal Evolution Analysis of Industrial Green Technology Innovation Efficiency in the Yangtze River Economic Belt |
| ID_Doc |
30546 |
| Authors |
Yao, MC; Duan, JJ; Wang, QS |
| Title |
Spatial and Temporal Evolution Analysis of Industrial Green Technology Innovation Efficiency in the Yangtze River Economic Belt |
| Year |
2022 |
| Published |
International Journal Of Environmental Research And Public Health, 19, 11 |
| DOI |
10.3390/ijerph19116361 |
| Abstract |
As a fusion point of innovation-driven green development, green technology innovation has become an essential engine for green transformation and high-quality economic development of the Yangtze River Economic Belt. Based on the panel data of 110 cities in the Yangtze River Economic Belt from 2006 to 2020, this paper uses the super-SBM model to measure the efficiency of industrial green technology innovation. Then, the Dagum Gini coefficient and its subgroup decomposition method, kernel density estimation, and the spatial Markov chain will discuss the convergence characteristics and dynamic evolution law of industrial green technology innovation efficiency in the Yangtze River Economic Belt. The results indicate several key points. (1) On the whole, the industrial green innovation efficiency of the Yangtze River Economic Belt shows a trend of the "N" type, which increases slowly at first and then decreases and then increases, and shows a non-equilibrium feature of "east high and west low" in space. (2) The average GML index of industrial green technology innovation efficiency in the Yangtze River Economic Belt is greater than 1, and technological progress is the main driving force in promoting efficiency growth. (3) There are spatial and temporal differences in industrial green technological innovation efficiency in the Yangtze River Economic Belt. Interregional differences and hypervariable density are the primary sources of overall differences. (4) During the study period, the absolute difference in industrial green technology innovation efficiency among regions showed a trend of "expansion-reduction-expansion", and the innovation efficiency gradually converged to a single equilibrium point. (5) The industrial green technology innovation efficiency transfer in the Yangtze River Economic Belt shows a specific spatial dependence. Accordingly, policy suggestions are put forward to further improve industrial green technological innovation in the Yangtze River Economic Belt. |
| Author Keywords |
industrial green technology innovation; super-SBM model; GML index; kernel density estimation; spatial Markov chain |
| Index Keywords |
Index Keywords |
| Document Type |
Other |
| Open Access |
Open Access |
| Source |
Science Citation Index Expanded (SCI-EXPANDED); Social Science Citation Index (SSCI) |
| EID |
WOS:000809046000001 |
| WoS Category |
Environmental Sciences; Public, Environmental & Occupational Health |
| Research Area |
Environmental Sciences & Ecology; Public, Environmental & Occupational Health |
| PDF |
https://www.mdpi.com/1660-4601/19/11/6361/pdf?version=1653379669
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