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Study on the Spatio–Temporal Evolution of China’s Smart Water Co-Governance in G–E–P Mode
Smart water co-governance (SWCG) is a fundamental driving force to reduce the water crisis and promote the sustainable development of water resources. To explore the applicability and development of SWCG in different regions, the authors of this paper took 31 provinces of China (with the exception H...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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MDPI
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8656874/ https://www.ncbi.nlm.nih.gov/pubmed/34886371 http://dx.doi.org/10.3390/ijerph182312648 |
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author | Zhang, Ning Wang, Zichen Ru, Hongkai Li, Haiyang |
author_facet | Zhang, Ning Wang, Zichen Ru, Hongkai Li, Haiyang |
author_sort | Zhang, Ning |
collection | PubMed |
description | Smart water co-governance (SWCG) is a fundamental driving force to reduce the water crisis and promote the sustainable development of water resources. To explore the applicability and development of SWCG in different regions, the authors of this paper took 31 provinces of China (with the exception Hong Kong, Macao, and Taiwan) as research districts and used the three-stage data envelopment analysis (DEA) method to measure and compare the efficiency of smart water governance (SWG) in the government–enterprise–public (G–E–P) mode and without public participation in the government–enterprise (G–E) mode in 2019. Then, the Malmquist model was used to measure the spatio–temporal evolution of the G–E–P mode from 2010 to 2019, focusing on the analysis of the top ten provinces of the China Internet Development Index in 2019. According to the empirical analysis, the following results were obtained: (1) the efficiency of SWCG in the G–E–P mode was significantly higher than that in G–E model, as 13 provinces showed a significant decline and 10 provinces had a small change. In addition, SWCG in the G–E–P mode showed a good development trend in the eastern and southern regions. (2) The governance efficiency, pure technical efficiency, and scale efficiency showed upward trends, but the technological progress index and total factor productivity were still low. Therefore, SWG should vigorously promote public participation and the independent implementation of enterprises under the guidance and restriction of the government. Meanwhile, the construction of an SWG infrastructure and the level of science and technology should be strengthened. In addition, each province should adjust the input–output structure according to its redundancy or deficiency, weigh the suitability of the input level and scale, and strengthen the matching and support of the ability of multi-subjects and factors to ensure that an appropriate input–output scale level is reached and the efficiency of SWCG is improved. |
format | Online Article Text |
id | pubmed-8656874 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-86568742021-12-10 Study on the Spatio–Temporal Evolution of China’s Smart Water Co-Governance in G–E–P Mode Zhang, Ning Wang, Zichen Ru, Hongkai Li, Haiyang Int J Environ Res Public Health Article Smart water co-governance (SWCG) is a fundamental driving force to reduce the water crisis and promote the sustainable development of water resources. To explore the applicability and development of SWCG in different regions, the authors of this paper took 31 provinces of China (with the exception Hong Kong, Macao, and Taiwan) as research districts and used the three-stage data envelopment analysis (DEA) method to measure and compare the efficiency of smart water governance (SWG) in the government–enterprise–public (G–E–P) mode and without public participation in the government–enterprise (G–E) mode in 2019. Then, the Malmquist model was used to measure the spatio–temporal evolution of the G–E–P mode from 2010 to 2019, focusing on the analysis of the top ten provinces of the China Internet Development Index in 2019. According to the empirical analysis, the following results were obtained: (1) the efficiency of SWCG in the G–E–P mode was significantly higher than that in G–E model, as 13 provinces showed a significant decline and 10 provinces had a small change. In addition, SWCG in the G–E–P mode showed a good development trend in the eastern and southern regions. (2) The governance efficiency, pure technical efficiency, and scale efficiency showed upward trends, but the technological progress index and total factor productivity were still low. Therefore, SWG should vigorously promote public participation and the independent implementation of enterprises under the guidance and restriction of the government. Meanwhile, the construction of an SWG infrastructure and the level of science and technology should be strengthened. In addition, each province should adjust the input–output structure according to its redundancy or deficiency, weigh the suitability of the input level and scale, and strengthen the matching and support of the ability of multi-subjects and factors to ensure that an appropriate input–output scale level is reached and the efficiency of SWCG is improved. MDPI 2021-11-30 /pmc/articles/PMC8656874/ /pubmed/34886371 http://dx.doi.org/10.3390/ijerph182312648 Text en © 2021 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Zhang, Ning Wang, Zichen Ru, Hongkai Li, Haiyang Study on the Spatio–Temporal Evolution of China’s Smart Water Co-Governance in G–E–P Mode |
title | Study on the Spatio–Temporal Evolution of China’s Smart Water Co-Governance in G–E–P Mode |
title_full | Study on the Spatio–Temporal Evolution of China’s Smart Water Co-Governance in G–E–P Mode |
title_fullStr | Study on the Spatio–Temporal Evolution of China’s Smart Water Co-Governance in G–E–P Mode |
title_full_unstemmed | Study on the Spatio–Temporal Evolution of China’s Smart Water Co-Governance in G–E–P Mode |
title_short | Study on the Spatio–Temporal Evolution of China’s Smart Water Co-Governance in G–E–P Mode |
title_sort | study on the spatio–temporal evolution of china’s smart water co-governance in g–e–p mode |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8656874/ https://www.ncbi.nlm.nih.gov/pubmed/34886371 http://dx.doi.org/10.3390/ijerph182312648 |
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