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Energy and environmental efficiency measurement of China's industrial sectors: A DEA model with non-homogeneous inputs and outputs
Environmental problems brought by industry are attracting extensive attention so a comprehensive analysis of industrial environmental performance is increasingly important. However, the comparison of industrial sector efficiencies is complicated by the fact that the natural resources consumed and/or...
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Published in: | Energy economics 2019-02, Vol.78, p.468-480 |
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container_title | Energy economics |
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creator | Wu, Jie Li, Mingjun Zhu, Qingyuan Zhou, Zhixiang Liang, Liang |
description | Environmental problems brought by industry are attracting extensive attention so a comprehensive analysis of industrial environmental performance is increasingly important. However, the comparison of industrial sector efficiencies is complicated by the fact that the natural resources consumed and/or the pollutants discharged by each sector may differ. In this paper, we extend the DEA model to consider two-sided non-homogeneous problems, handling DMU sets that have non-homogeneity in both inputs and outputs. This is different from the previous researches which generally focus on regional data to avoid non-homogeneity. Today environmental reform and energy conservation in various industrial sectors are both parts of the basic state policy of China. The empirical results show that: (1) Sectors' efficiencies are still low and unbalanced. The Recycling and Disposal of Waste department achieves the best energy saving and emission reduction efficiency. (2) 38 sectors can be clustered into four groups and set new benchmark in each group. (3) The overall efficiency of 38 industrial sectors in China maintained a rising trend in five years. With this more realistic analysis of environmental efficiency, the Chinese government can make more informed decisions to realize sustainable industrial development.
•We break the homogeneous assumption of conventional DEA model.•Our model solves problems with dissimilarity in both inputs and outputs.•Our model has advantages in evaluating energy and environmental efficiency of industrial sectors.•The empirical results give a new aspect to energy conservation performance in China. |
doi_str_mv | 10.1016/j.eneco.2018.11.036 |
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•We break the homogeneous assumption of conventional DEA model.•Our model solves problems with dissimilarity in both inputs and outputs.•Our model has advantages in evaluating energy and environmental efficiency of industrial sectors.•The empirical results give a new aspect to energy conservation performance in China.</description><identifier>ISSN: 0140-9883</identifier><identifier>EISSN: 1873-6181</identifier><identifier>DOI: 10.1016/j.eneco.2018.11.036</identifier><language>eng</language><publisher>Kidlington: Elsevier B.V</publisher><subject>China's industrial sectors ; Data envelopment analysis ; Efficiency ; Emissions ; Emissions control ; Empirical analysis ; Energy conservation ; Energy economics ; Energy measurement ; Environmental degradation ; Environmental efficiency ; Environmental impact ; Environmental performance ; Homogeneity ; Industrial development ; Industrial policy ; Industry ; Measurement ; Natural resources ; Non-homogeneous DMUs ; Pollutants ; Power efficiency ; Recycling ; State policy ; Sustainable development ; Waste disposal</subject><ispartof>Energy economics, 2019-02, Vol.78, p.468-480</ispartof><rights>2018 Elsevier B.V.</rights><rights>Copyright Elsevier Science Ltd. Feb 2019</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c396t-3eca95c5660877fae25bb652a0ccda07e417f2467b7af4f977c5fe4262bb15693</citedby><cites>FETCH-LOGICAL-c396t-3eca95c5660877fae25bb652a0ccda07e417f2467b7af4f977c5fe4262bb15693</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,780,784,27864,27922,27923,33221</link.rule.ids></links><search><creatorcontrib>Wu, Jie</creatorcontrib><creatorcontrib>Li, Mingjun</creatorcontrib><creatorcontrib>Zhu, Qingyuan</creatorcontrib><creatorcontrib>Zhou, Zhixiang</creatorcontrib><creatorcontrib>Liang, Liang</creatorcontrib><title>Energy and environmental efficiency measurement of China's industrial sectors: A DEA model with non-homogeneous inputs and outputs</title><title>Energy economics</title><description>Environmental problems brought by industry are attracting extensive attention so a comprehensive analysis of industrial environmental performance is increasingly important. However, the comparison of industrial sector efficiencies is complicated by the fact that the natural resources consumed and/or the pollutants discharged by each sector may differ. In this paper, we extend the DEA model to consider two-sided non-homogeneous problems, handling DMU sets that have non-homogeneity in both inputs and outputs. This is different from the previous researches which generally focus on regional data to avoid non-homogeneity. Today environmental reform and energy conservation in various industrial sectors are both parts of the basic state policy of China. The empirical results show that: (1) Sectors' efficiencies are still low and unbalanced. The Recycling and Disposal of Waste department achieves the best energy saving and emission reduction efficiency. (2) 38 sectors can be clustered into four groups and set new benchmark in each group. (3) The overall efficiency of 38 industrial sectors in China maintained a rising trend in five years. With this more realistic analysis of environmental efficiency, the Chinese government can make more informed decisions to realize sustainable industrial development.
•We break the homogeneous assumption of conventional DEA model.•Our model solves problems with dissimilarity in both inputs and outputs.•Our model has advantages in evaluating energy and environmental efficiency of industrial sectors.•The empirical results give a new aspect to energy conservation performance in China.</description><subject>China's industrial sectors</subject><subject>Data envelopment analysis</subject><subject>Efficiency</subject><subject>Emissions</subject><subject>Emissions control</subject><subject>Empirical analysis</subject><subject>Energy conservation</subject><subject>Energy economics</subject><subject>Energy measurement</subject><subject>Environmental degradation</subject><subject>Environmental efficiency</subject><subject>Environmental impact</subject><subject>Environmental performance</subject><subject>Homogeneity</subject><subject>Industrial development</subject><subject>Industrial policy</subject><subject>Industry</subject><subject>Measurement</subject><subject>Natural resources</subject><subject>Non-homogeneous DMUs</subject><subject>Pollutants</subject><subject>Power efficiency</subject><subject>Recycling</subject><subject>State policy</subject><subject>Sustainable development</subject><subject>Waste disposal</subject><issn>0140-9883</issn><issn>1873-6181</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2019</creationdate><recordtype>article</recordtype><sourceid>7TQ</sourceid><sourceid>8BJ</sourceid><recordid>eNp9kEGP0zAQhS0EEqXLL-BiiQOnZD1ObCcrcai6hUVaaS9wthxnvHXV2F07WdQrv5yk5cxpRpr35s18hHwCVgIDeXsoMaCNJWfQlAAlq-QbsoJGVYWEBt6SFYOaFW3TVO_Jh5wPjDEhRbMif3YB0_OZmtBTDK8-xTBgGM2RonPeegz2TAc0eUq4DGh0dLv3wXzJ1Id-ymPyszijHWPKd3RD73cbOsQej_S3H_c0xFDs4xCf5wvjtJhO05gveXEal_6GvHPmmPHjv7omv77tfm4fisen7z-2m8fCVq0ciwqtaYUVUrJGKWeQi66TghtmbW-YwhqU47VUnTKudq1SVjisueRdB0K21Zp8vu49pfgyYR71IU4pzJGac-CKqUrArKquKptizgmdPiU_mHTWwPQCWx_0BbZeYGsAPcOeXV-vLpwfePWYdL6ww96nGY3uo_-v_y8oBYta</recordid><startdate>20190201</startdate><enddate>20190201</enddate><creator>Wu, Jie</creator><creator>Li, Mingjun</creator><creator>Zhu, Qingyuan</creator><creator>Zhou, Zhixiang</creator><creator>Liang, Liang</creator><general>Elsevier B.V</general><general>Elsevier Science Ltd</general><scope>AAYXX</scope><scope>CITATION</scope><scope>7ST</scope><scope>7TA</scope><scope>7TQ</scope><scope>8BJ</scope><scope>8FD</scope><scope>C1K</scope><scope>DHY</scope><scope>DON</scope><scope>FQK</scope><scope>JBE</scope><scope>JG9</scope><scope>SOI</scope></search><sort><creationdate>20190201</creationdate><title>Energy and environmental efficiency measurement of China's industrial sectors: A DEA model with non-homogeneous inputs and outputs</title><author>Wu, Jie ; Li, Mingjun ; Zhu, Qingyuan ; Zhou, Zhixiang ; Liang, Liang</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c396t-3eca95c5660877fae25bb652a0ccda07e417f2467b7af4f977c5fe4262bb15693</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2019</creationdate><topic>China's industrial sectors</topic><topic>Data envelopment analysis</topic><topic>Efficiency</topic><topic>Emissions</topic><topic>Emissions control</topic><topic>Empirical analysis</topic><topic>Energy conservation</topic><topic>Energy economics</topic><topic>Energy measurement</topic><topic>Environmental degradation</topic><topic>Environmental efficiency</topic><topic>Environmental impact</topic><topic>Environmental performance</topic><topic>Homogeneity</topic><topic>Industrial development</topic><topic>Industrial policy</topic><topic>Industry</topic><topic>Measurement</topic><topic>Natural resources</topic><topic>Non-homogeneous DMUs</topic><topic>Pollutants</topic><topic>Power efficiency</topic><topic>Recycling</topic><topic>State policy</topic><topic>Sustainable development</topic><topic>Waste disposal</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Wu, Jie</creatorcontrib><creatorcontrib>Li, Mingjun</creatorcontrib><creatorcontrib>Zhu, Qingyuan</creatorcontrib><creatorcontrib>Zhou, Zhixiang</creatorcontrib><creatorcontrib>Liang, Liang</creatorcontrib><collection>CrossRef</collection><collection>Environment Abstracts</collection><collection>Materials Business File</collection><collection>PAIS Index</collection><collection>International Bibliography of the Social Sciences (IBSS)</collection><collection>Technology Research Database</collection><collection>Environmental Sciences and Pollution Management</collection><collection>PAIS International</collection><collection>PAIS International (Ovid)</collection><collection>International Bibliography of the Social Sciences</collection><collection>International Bibliography of the Social Sciences</collection><collection>Materials Research Database</collection><collection>Environment Abstracts</collection><jtitle>Energy economics</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Wu, Jie</au><au>Li, Mingjun</au><au>Zhu, Qingyuan</au><au>Zhou, Zhixiang</au><au>Liang, Liang</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Energy and environmental efficiency measurement of China's industrial sectors: A DEA model with non-homogeneous inputs and outputs</atitle><jtitle>Energy economics</jtitle><date>2019-02-01</date><risdate>2019</risdate><volume>78</volume><spage>468</spage><epage>480</epage><pages>468-480</pages><issn>0140-9883</issn><eissn>1873-6181</eissn><abstract>Environmental problems brought by industry are attracting extensive attention so a comprehensive analysis of industrial environmental performance is increasingly important. However, the comparison of industrial sector efficiencies is complicated by the fact that the natural resources consumed and/or the pollutants discharged by each sector may differ. In this paper, we extend the DEA model to consider two-sided non-homogeneous problems, handling DMU sets that have non-homogeneity in both inputs and outputs. This is different from the previous researches which generally focus on regional data to avoid non-homogeneity. Today environmental reform and energy conservation in various industrial sectors are both parts of the basic state policy of China. The empirical results show that: (1) Sectors' efficiencies are still low and unbalanced. The Recycling and Disposal of Waste department achieves the best energy saving and emission reduction efficiency. (2) 38 sectors can be clustered into four groups and set new benchmark in each group. (3) The overall efficiency of 38 industrial sectors in China maintained a rising trend in five years. With this more realistic analysis of environmental efficiency, the Chinese government can make more informed decisions to realize sustainable industrial development.
•We break the homogeneous assumption of conventional DEA model.•Our model solves problems with dissimilarity in both inputs and outputs.•Our model has advantages in evaluating energy and environmental efficiency of industrial sectors.•The empirical results give a new aspect to energy conservation performance in China.</abstract><cop>Kidlington</cop><pub>Elsevier B.V</pub><doi>10.1016/j.eneco.2018.11.036</doi><tpages>13</tpages></addata></record> |
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source | International Bibliography of the Social Sciences (IBSS); ScienceDirect Freedom Collection; PAIS Index |
subjects | China's industrial sectors Data envelopment analysis Efficiency Emissions Emissions control Empirical analysis Energy conservation Energy economics Energy measurement Environmental degradation Environmental efficiency Environmental impact Environmental performance Homogeneity Industrial development Industrial policy Industry Measurement Natural resources Non-homogeneous DMUs Pollutants Power efficiency Recycling State policy Sustainable development Waste disposal |
title | Energy and environmental efficiency measurement of China's industrial sectors: A DEA model with non-homogeneous inputs and outputs |
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