Mining Eco-Efficiency Measurement and Driving Factors Identification Based on Meta-US-SBM in Guangxi Province, China
The mining industry is one of the pillar industries of Guangxi’s economic and social development. The output value of mining and related industries accounts for 27% of the whole district’s total industrial output value. Therefore, the mining eco-efficiency measurement in Guangxi can be of great sign...
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doaj-7e26d384f77146ca8d5910743f0d89612021-06-01T00:24:22ZengMDPI AGInternational Journal of Environmental Research and Public Health1661-78271660-46012021-05-01185397539710.3390/ijerph18105397Mining Eco-Efficiency Measurement and Driving Factors Identification Based on Meta-US-SBM in Guangxi Province, ChinaYonglin Li0Zhili Zuo1Deyi Xu2Yi Wei3School of Economics and Management, China University of Geosciences, Wuhan 430074, ChinaSchool of Economics and Management, China University of Geosciences, Wuhan 430074, ChinaSchool of Economics and Management, China University of Geosciences, Wuhan 430074, ChinaSchool of Economics and Management, China University of Geosciences, Wuhan 430074, ChinaThe mining industry is one of the pillar industries of Guangxi’s economic and social development. The output value of mining and related industries accounts for 27% of the whole district’s total industrial output value. Therefore, the mining eco-efficiency measurement in Guangxi can be of great significance for the sustainable development of Guangxi’s mining industry. This study adopted Meta-US-SBM to measure the mining eco-efficiency in Guangxi from 2008 to 2018, including economic efficiency, resource efficiency, and environmental efficiency. It used the standard deviation ellipse model to simulate the migration trend of four efficiencies in Guangxi and used GeoDetector and Tobit models to explore the internal and external factors that affect the mining eco-efficiency. The four efficiencies in Guangxi show large temporal and spatial heterogeneity, and the internal and external factors that affect the mining eco-efficiency are different. The following conclusions can be drawn. (1) Environmental efficiency and mining eco-efficiency are improving, while economic efficiency and resource efficiency are deteriorating. Cities bordering other provinces have a significantly better mining eco-efficiency than non-bordering cities. (2) The development center in Guangxi has migrated to the Beibu Gulf Economic Zone. (3) Natural resources index and mining economic scale have a great impact on the mining eco-efficiency, and with the increase of the mining economic scale, the mining eco-efficiency showed a typical “U-shaped” curve. Finally, this study put forward corresponding policy recommendations to improve the mining eco-efficiency in Guangxi from four aspects: opening-up, technological progress, regional coordination, and government control.https://www.mdpi.com/1660-4601/18/10/5397mining eco-efficiencyMeta-US-SBMstandard deviation ellipse modelGeoDetectorTobit ModelGuangxi |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Yonglin Li Zhili Zuo Deyi Xu Yi Wei |
spellingShingle |
Yonglin Li Zhili Zuo Deyi Xu Yi Wei Mining Eco-Efficiency Measurement and Driving Factors Identification Based on Meta-US-SBM in Guangxi Province, China International Journal of Environmental Research and Public Health mining eco-efficiency Meta-US-SBM standard deviation ellipse model GeoDetector Tobit Model Guangxi |
author_facet |
Yonglin Li Zhili Zuo Deyi Xu Yi Wei |
author_sort |
Yonglin Li |
title |
Mining Eco-Efficiency Measurement and Driving Factors Identification Based on Meta-US-SBM in Guangxi Province, China |
title_short |
Mining Eco-Efficiency Measurement and Driving Factors Identification Based on Meta-US-SBM in Guangxi Province, China |
title_full |
Mining Eco-Efficiency Measurement and Driving Factors Identification Based on Meta-US-SBM in Guangxi Province, China |
title_fullStr |
Mining Eco-Efficiency Measurement and Driving Factors Identification Based on Meta-US-SBM in Guangxi Province, China |
title_full_unstemmed |
Mining Eco-Efficiency Measurement and Driving Factors Identification Based on Meta-US-SBM in Guangxi Province, China |
title_sort |
mining eco-efficiency measurement and driving factors identification based on meta-us-sbm in guangxi province, china |
publisher |
MDPI AG |
series |
International Journal of Environmental Research and Public Health |
issn |
1661-7827 1660-4601 |
publishDate |
2021-05-01 |
description |
The mining industry is one of the pillar industries of Guangxi’s economic and social development. The output value of mining and related industries accounts for 27% of the whole district’s total industrial output value. Therefore, the mining eco-efficiency measurement in Guangxi can be of great significance for the sustainable development of Guangxi’s mining industry. This study adopted Meta-US-SBM to measure the mining eco-efficiency in Guangxi from 2008 to 2018, including economic efficiency, resource efficiency, and environmental efficiency. It used the standard deviation ellipse model to simulate the migration trend of four efficiencies in Guangxi and used GeoDetector and Tobit models to explore the internal and external factors that affect the mining eco-efficiency. The four efficiencies in Guangxi show large temporal and spatial heterogeneity, and the internal and external factors that affect the mining eco-efficiency are different. The following conclusions can be drawn. (1) Environmental efficiency and mining eco-efficiency are improving, while economic efficiency and resource efficiency are deteriorating. Cities bordering other provinces have a significantly better mining eco-efficiency than non-bordering cities. (2) The development center in Guangxi has migrated to the Beibu Gulf Economic Zone. (3) Natural resources index and mining economic scale have a great impact on the mining eco-efficiency, and with the increase of the mining economic scale, the mining eco-efficiency showed a typical “U-shaped” curve. Finally, this study put forward corresponding policy recommendations to improve the mining eco-efficiency in Guangxi from four aspects: opening-up, technological progress, regional coordination, and government control. |
topic |
mining eco-efficiency Meta-US-SBM standard deviation ellipse model GeoDetector Tobit Model Guangxi |
url |
https://www.mdpi.com/1660-4601/18/10/5397 |
work_keys_str_mv |
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