Intertemporal environmental efficiency assessment in China: A new network-based dynamic super-efficiency measure
In order to make a complete ranking of intertemporal environmental efficiency in a dynamic manner, this paper combines the network-based dynamic data envelopment analysis (DEA), super-efficiency with the unified efficiency under natural and managerial disposability, and designs a dynamic DEA model a...
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| Veröffentlicht in: | PloS one 2023-08, Vol.18 (8), p.e0290896-e0290896 |
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| description | In order to make a complete ranking of intertemporal environmental efficiency in a dynamic manner, this paper combines the network-based dynamic data envelopment analysis (DEA), super-efficiency with the unified efficiency under natural and managerial disposability, and designs a dynamic DEA model and the corresponding dynamic super-efficiency DEA model. Compared with previous studies, the proposed measure can fully rank the overall environmental efficiency of all decision making units (DMUs) in a dynamic manner, and more importantly, it provides the information about when and what factors lead to inefficiency or efficiency of DMUs. The proposed models are applied to examine the environmental efficiency of 30 provinces in China from 2008 to 2017. The results show that there are significant regional differences of environmental efficiency in China. In addition, slack analysis shows that most eastern efficient provinces have no obvious advantages in energy consumption, labor and waste water emission; most central and western efficient provinces have no advantages in sulfur dioxide (SO2) emissions and GDP. To improve overall efficiency, eastern inefficient provinces should mainly focus on reducing energy consumption, SO2 emissions and labor, and increasing capital investment in right years, central and western inefficient provinces can focus on reducing SO2 emissions and labor in most years, most of provinces need to increase gross domestic capital formation. |
| doi_str_mv | 10.1371/journal.pone.0290896 |
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Compared with previous studies, the proposed measure can fully rank the overall environmental efficiency of all decision making units (DMUs) in a dynamic manner, and more importantly, it provides the information about when and what factors lead to inefficiency or efficiency of DMUs. The proposed models are applied to examine the environmental efficiency of 30 provinces in China from 2008 to 2017. The results show that there are significant regional differences of environmental efficiency in China. In addition, slack analysis shows that most eastern efficient provinces have no obvious advantages in energy consumption, labor and waste water emission; most central and western efficient provinces have no advantages in sulfur dioxide (SO2) emissions and GDP. To improve overall efficiency, eastern inefficient provinces should mainly focus on reducing energy consumption, SO2 emissions and labor, and increasing capital investment in right years, central and western inefficient provinces can focus on reducing SO2 emissions and labor in most years, most of provinces need to increase gross domestic capital formation.</description><identifier>ISSN: 1932-6203</identifier><identifier>EISSN: 1932-6203</identifier><identifier>DOI: 10.1371/journal.pone.0290896</identifier><language>eng</language><publisher>San Francisco: Public Library of Science</publisher><subject>Computer and Information Sciences ; Data envelopment analysis ; Decision making ; Ecology and Environmental Sciences ; Efficiency ; Emissions ; Energy consumption ; Engineering and Technology ; Environmental assessment ; Environmental impact ; Environmental protection ; Evaluation ; Labor ; People and Places ; Physical Sciences ; Research and Analysis Methods ; Sulfur ; Sulfur dioxide ; Wastewater</subject><ispartof>PloS one, 2023-08, Vol.18 (8), p.e0290896-e0290896</ispartof><rights>COPYRIGHT 2023 Public Library of Science</rights><rights>2023 Lin, Li. This is an open access article distributed under the terms of the Creative Commons Attribution License: http://creativecommons.org/licenses/by/4.0/ (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><rights>2023 Lin, Li 2023 Lin, Li</rights><rights>2023 Lin, Li. This is an open access article distributed under the terms of the Creative Commons Attribution License: http://creativecommons.org/licenses/by/4.0/ (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. 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Compared with previous studies, the proposed measure can fully rank the overall environmental efficiency of all decision making units (DMUs) in a dynamic manner, and more importantly, it provides the information about when and what factors lead to inefficiency or efficiency of DMUs. The proposed models are applied to examine the environmental efficiency of 30 provinces in China from 2008 to 2017. The results show that there are significant regional differences of environmental efficiency in China. In addition, slack analysis shows that most eastern efficient provinces have no obvious advantages in energy consumption, labor and waste water emission; most central and western efficient provinces have no advantages in sulfur dioxide (SO2) emissions and GDP. To improve overall efficiency, eastern inefficient provinces should mainly focus on reducing energy consumption, SO2 emissions and labor, and increasing capital investment in right years, central and western inefficient provinces can focus on reducing SO2 emissions and labor in most years, most of provinces need to increase gross domestic capital formation.</description><subject>Computer and Information Sciences</subject><subject>Data envelopment analysis</subject><subject>Decision making</subject><subject>Ecology and Environmental Sciences</subject><subject>Efficiency</subject><subject>Emissions</subject><subject>Energy consumption</subject><subject>Engineering and Technology</subject><subject>Environmental assessment</subject><subject>Environmental impact</subject><subject>Environmental protection</subject><subject>Evaluation</subject><subject>Labor</subject><subject>People and Places</subject><subject>Physical Sciences</subject><subject>Research and Analysis 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environmental efficiency assessment in China: A new network-based dynamic super-efficiency measure</atitle><jtitle>PloS one</jtitle><date>2023-08-31</date><risdate>2023</risdate><volume>18</volume><issue>8</issue><spage>e0290896</spage><epage>e0290896</epage><pages>e0290896-e0290896</pages><issn>1932-6203</issn><eissn>1932-6203</eissn><abstract>In order to make a complete ranking of intertemporal environmental efficiency in a dynamic manner, this paper combines the network-based dynamic data envelopment analysis (DEA), super-efficiency with the unified efficiency under natural and managerial disposability, and designs a dynamic DEA model and the corresponding dynamic super-efficiency DEA model. Compared with previous studies, the proposed measure can fully rank the overall environmental efficiency of all decision making units (DMUs) in a dynamic manner, and more importantly, it provides the information about when and what factors lead to inefficiency or efficiency of DMUs. The proposed models are applied to examine the environmental efficiency of 30 provinces in China from 2008 to 2017. The results show that there are significant regional differences of environmental efficiency in China. In addition, slack analysis shows that most eastern efficient provinces have no obvious advantages in energy consumption, labor and waste water emission; most central and western efficient provinces have no advantages in sulfur dioxide (SO2) emissions and GDP. To improve overall efficiency, eastern inefficient provinces should mainly focus on reducing energy consumption, SO2 emissions and labor, and increasing capital investment in right years, central and western inefficient provinces can focus on reducing SO2 emissions and labor in most years, most of provinces need to increase gross domestic capital formation.</abstract><cop>San Francisco</cop><pub>Public Library of Science</pub><doi>10.1371/journal.pone.0290896</doi><tpages>e0290896</tpages><orcidid>https://orcid.org/0000-0002-8068-7716</orcidid><oa>free_for_read</oa></addata></record> |
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| subjects | Computer and Information Sciences Data envelopment analysis Decision making Ecology and Environmental Sciences Efficiency Emissions Energy consumption Engineering and Technology Environmental assessment Environmental impact Environmental protection Evaluation Labor People and Places Physical Sciences Research and Analysis Methods Sulfur Sulfur dioxide Wastewater |
| title | Intertemporal environmental efficiency assessment in China: A new network-based dynamic super-efficiency measure |
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