Urban Green Innovation Efficiency in China: Spatiotemporal Evolution and Influencing Factors
Investigating urban green innovation efficiency (UGIE) is imperative because it is correlated with the development of an ecological civilization and an innovative country. Spatiotemporal evolution and influencing factors of UGIE are two important scientific problems that are worth exploring. This st...
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| Format: | Article |
| Language: | English |
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MDPI AG
2022-12-01
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| Series: | Land |
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| Online Access: | https://www.mdpi.com/2073-445X/12/1/75 |
| _version_ | 1797439917297500160 |
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| author | Shumin Dong Yuting Xue Guixiu Ren Kai Liu |
| author_facet | Shumin Dong Yuting Xue Guixiu Ren Kai Liu |
| author_sort | Shumin Dong |
| collection | DOAJ |
| description | Investigating urban green innovation efficiency (UGIE) is imperative because it is correlated with the development of an ecological civilization and an innovative country. Spatiotemporal evolution and influencing factors of UGIE are two important scientific problems that are worth exploring. This study presents an indicator system for UGIE that includes input, expected output, and unexpected output, and employs a super-efficiency slacks-based measure (super-SBM) to calculate UGIE in 284 cities at or above the prefecture level in China from 2005 to 2020. Then, we adopted spatial auto-correlation to identify its spatial differences among these cities and Geodetector to evaluate its influencing factors. The results are as follows: (1) The overall UGIE tended to rise, except in northeastern China, megacities, and super large-sized cities. (2) The UGIE of Chinese cities exhibited remarkable spatial differences and auto-correlation, and the “low-low” type enjoyed the most local spatial auto-correlations. (3) Sociocultural factors represented by the number of collections in public libraries became the most important factors affecting the UGIE in China. |
| first_indexed | 2024-03-09T12:00:38Z |
| format | Article |
| id | doaj.art-785ddc3a3ba84e8899ad94b4534af3e2 |
| institution | Directory Open Access Journal |
| issn | 2073-445X |
| language | English |
| last_indexed | 2024-03-09T12:00:38Z |
| publishDate | 2022-12-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Land |
| spelling | doaj.art-785ddc3a3ba84e8899ad94b4534af3e22023-11-30T23:03:57ZengMDPI AGLand2073-445X2022-12-011217510.3390/land12010075Urban Green Innovation Efficiency in China: Spatiotemporal Evolution and Influencing FactorsShumin Dong0Yuting Xue1Guixiu Ren2Kai Liu3College of Geography and Environment, Shandong Normal University, Jinan 250358, ChinaCollege of Geography and Environment, Shandong Normal University, Jinan 250358, ChinaCollege of Geography and Environment, Shandong Normal University, Jinan 250358, ChinaCollege of Geography and Environment, Shandong Normal University, Jinan 250358, ChinaInvestigating urban green innovation efficiency (UGIE) is imperative because it is correlated with the development of an ecological civilization and an innovative country. Spatiotemporal evolution and influencing factors of UGIE are two important scientific problems that are worth exploring. This study presents an indicator system for UGIE that includes input, expected output, and unexpected output, and employs a super-efficiency slacks-based measure (super-SBM) to calculate UGIE in 284 cities at or above the prefecture level in China from 2005 to 2020. Then, we adopted spatial auto-correlation to identify its spatial differences among these cities and Geodetector to evaluate its influencing factors. The results are as follows: (1) The overall UGIE tended to rise, except in northeastern China, megacities, and super large-sized cities. (2) The UGIE of Chinese cities exhibited remarkable spatial differences and auto-correlation, and the “low-low” type enjoyed the most local spatial auto-correlations. (3) Sociocultural factors represented by the number of collections in public libraries became the most important factors affecting the UGIE in China.https://www.mdpi.com/2073-445X/12/1/75urban green innovation efficiency (UGIE)green innovationspatiotemporal evolutioninfluencing factorsuper-SBMspatial auto-correlation |
| spellingShingle | Shumin Dong Yuting Xue Guixiu Ren Kai Liu Urban Green Innovation Efficiency in China: Spatiotemporal Evolution and Influencing Factors Land urban green innovation efficiency (UGIE) green innovation spatiotemporal evolution influencing factor super-SBM spatial auto-correlation |
| title | Urban Green Innovation Efficiency in China: Spatiotemporal Evolution and Influencing Factors |
| title_full | Urban Green Innovation Efficiency in China: Spatiotemporal Evolution and Influencing Factors |
| title_fullStr | Urban Green Innovation Efficiency in China: Spatiotemporal Evolution and Influencing Factors |
| title_full_unstemmed | Urban Green Innovation Efficiency in China: Spatiotemporal Evolution and Influencing Factors |
| title_short | Urban Green Innovation Efficiency in China: Spatiotemporal Evolution and Influencing Factors |
| title_sort | urban green innovation efficiency in china spatiotemporal evolution and influencing factors |
| topic | urban green innovation efficiency (UGIE) green innovation spatiotemporal evolution influencing factor super-SBM spatial auto-correlation |
| url | https://www.mdpi.com/2073-445X/12/1/75 |
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