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- W3122687278 abstract "With environmental problems becoming increasingly serious worldwide, scholars’ research views on innovation have begun to pay more attention to the technological value from an ecological perspective, instead of simply analyzing the importance of technological innovation from the perspective of economic value. Currently, improving green innovation efficiency (GIE) has been considered as a critical path to realizing economic transformation and green development. Based on the global Super-Epsilon-based measure (EBM) model, Moran index, vector autoregression (VAR) model, and block model, this study investigated the temporal and spatial characteristics of GIE in 30 provinces in China from 2009 to 2017, and analyzed the spatial heterogeneity and spatial correlation network characteristics. The results showed that in spatial terms, China’s GIE presented an extremely unbalanced development model. In provinces with a higher GIE, there was an overall improvement of GIE, but there was a lower impact in provinces with a lower GIE. The efficiency of China’s green innovation could be divided into four blocks. The first block was the main overflow, the second block was the broker, the third block was the bilateral spillover, and the fourth block was the net benefit. The four blocks had their own functions, and a very significant correlation was observed among them." @default.
- W3122687278 created "2021-02-01" @default.
- W3122687278 creator A5021089842 @default.
- W3122687278 creator A5026877639 @default.
- W3122687278 date "2021-01-21" @default.
- W3122687278 modified "2023-09-30" @default.
- W3122687278 title "Investigating the Spatial Heterogeneity and Correlation Network of Green Innovation Efficiency in China" @default.
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- W3122687278 doi "https://doi.org/10.3390/su13031104" @default.
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