Literature DB >> 31260921

Evaluating the eco-efficiency of China's industrial sectors: A two-stage network data envelopment analysis.

Liuguo Shao1, Xiao Yu1, Chao Feng2.   

Abstract

Because the industrial process always results in pollutant emissions, pollution treatment has become necessary for the sustainable development of industry. This paper aims to evaluate the eco-efficiency of China's industrial sectors between 2007 and 2015 by using the directional distance function (DDF) of network data envelopment analysis (DEA), which contains a two-stage structure that divides industrial processes into three linked subprocesses, i.e., the production, wastewater and waste gas treatment processes. The results show that (1) from 2007 to 2015, the eco-efficiency and all process efficiencies of China's industries achieved considerable improvement. This finding indicates that China's industries have already achieved a win-win situation in the development of environmental protection and economic growth over the past few years. (2) During the sampling period, the highest performance was observed during the waste gas treatment process, followed by the wastewater treatment and production processes. During the same period, the performance of wastewater treatment exhibited the fastest growth, followed by the performance of production and waste gas treatment. (3) The eco-efficiencies of China's industrial subsectors exhibited significant industrial differences: the eco-efficiency of the mining industry was the lowest due to a decline in its performance during the waste gas treatment process, while due to the excellent performance during the production wastewater treatment process, the eco-efficiencies of the electricity, gas production and supply industries were the highest.
Copyright © 2019 Elsevier Ltd. All rights reserved.

Keywords:  China; Directional distance function; Eco-efficiency; Industrial sectors; Two-stage network DEA

Mesh:

Year:  2019        PMID: 31260921     DOI: 10.1016/j.jenvman.2019.06.099

Source DB:  PubMed          Journal:  J Environ Manage        ISSN: 0301-4797            Impact factor:   6.789


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