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Article: Measuring energy consumption efficiency of the construction industry: The case of China

TitleMeasuring energy consumption efficiency of the construction industry: The case of China
Authors
KeywordsChinese construction
Data envelopment analysis
Efficiency
Energy
Malmquist productivity index
Productivity
Issue Date2015
Citation
Journal of Cleaner Production, 2015, v. 107, p. 509-515 How to Cite?
AbstractThe energy conservation has become a considerable issue in construction industry for achieving sustainable development. Therefore it is crucial for policy-makers to look for optimized and flexible tools to measure the total energy consumption efficiency in construction industry. Data envelopment analysis (DEA) can be applied for multiple input and output decision-making units (DMUs) productivity measurement. DEA-based Malmquist productivity index (MPI) can be used as a tool for measuring the productivity change longitudinally. In this paper, we use input-oriented model to measure the energy consumption productivity change of the construction industry from 2004 to 2009 with data in 26 provinces of China. It is found that only Guangdong demonstrated effective energy improving in the whole reference period. It also identified the regional groups always lie on the efficiency frontier of energy consumption as benchmarks. Regional analysis shows that energy conservation gaps exist between northeastern, western region and central, eastern region. DEA-based Malmquist productivity index provides a good way to measure the energy consumption efficiency and can help policy-makers to improve strategies of sustainable development in China.
Persistent Identifierhttp://hdl.handle.net/10722/333138
ISSN
2023 Impact Factor: 9.7
2023 SCImago Journal Rankings: 2.058
ISI Accession Number ID

 

DC FieldValueLanguage
dc.contributor.authorXue, Xiaolong-
dc.contributor.authorWu, Hengqin-
dc.contributor.authorZhang, Xiaoling-
dc.contributor.authorDai, Jason-
dc.contributor.authorSu, Chang-
dc.date.accessioned2023-10-06T05:17:00Z-
dc.date.available2023-10-06T05:17:00Z-
dc.date.issued2015-
dc.identifier.citationJournal of Cleaner Production, 2015, v. 107, p. 509-515-
dc.identifier.issn0959-6526-
dc.identifier.urihttp://hdl.handle.net/10722/333138-
dc.description.abstractThe energy conservation has become a considerable issue in construction industry for achieving sustainable development. Therefore it is crucial for policy-makers to look for optimized and flexible tools to measure the total energy consumption efficiency in construction industry. Data envelopment analysis (DEA) can be applied for multiple input and output decision-making units (DMUs) productivity measurement. DEA-based Malmquist productivity index (MPI) can be used as a tool for measuring the productivity change longitudinally. In this paper, we use input-oriented model to measure the energy consumption productivity change of the construction industry from 2004 to 2009 with data in 26 provinces of China. It is found that only Guangdong demonstrated effective energy improving in the whole reference period. It also identified the regional groups always lie on the efficiency frontier of energy consumption as benchmarks. Regional analysis shows that energy conservation gaps exist between northeastern, western region and central, eastern region. DEA-based Malmquist productivity index provides a good way to measure the energy consumption efficiency and can help policy-makers to improve strategies of sustainable development in China.-
dc.languageeng-
dc.relation.ispartofJournal of Cleaner Production-
dc.subjectChinese construction-
dc.subjectData envelopment analysis-
dc.subjectEfficiency-
dc.subjectEnergy-
dc.subjectMalmquist productivity index-
dc.subjectProductivity-
dc.titleMeasuring energy consumption efficiency of the construction industry: The case of China-
dc.typeArticle-
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1016/j.jclepro.2014.04.082-
dc.identifier.scopuseid_2-s2.0-84942982149-
dc.identifier.volume107-
dc.identifier.spage509-
dc.identifier.epage515-
dc.identifier.isiWOS:000363071000050-

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