CO2 emissions reduction of Chinese light manufacturing industries:a novel RAM-based global Malmquist-Luenberger productivity index


Climate change has become one of the most challenging issues facing the world. Chinese government has realized the importance of energy conservation and prevention of the climate changes for sustainable development of China's economy and set targets for CO2 emissions reduction in China. In China industry contributes 84.2% of the total CO2 emissions, especially manufacturing industries. Data envelopment analysis (DEA) and Malmquist productivity (MP) index are the widely used mathematical techniques to address the relative efficiency and productivity of a group of homogenous decision making units, e.g. industries or countries. However, in many real applications, especially those related to energy efficiency, there are often undesirable outputs, e.g. the pollutions, waste and CO2 emissions, which are produced inevitably with desirable outputs in the production. This paper introduces a novel Malmquist-Luenberger productivity (MLP) index based on directional distance function (DDF) to address the issue of productivity evolution of DMUs in the presence of undesirable outputs. The new RAM (Range-adjusted measure)-based global MLP index has been applied to evaluate CO2 emissions reduction in Chinese light manufacturing industries. Recommendations for policy makers have been discussed.

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Divisions: College of Business and Social Sciences > Aston Business School > Operations & Information Management
Additional Information: © 2016, Elsevier. Licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International
Uncontrolled Keywords: data envelopment analysis,directional distance function (DDF),energy efficiency,range-adjusted measure (RAM),DEA,Energy(all),Management, Monitoring, Policy and Law
Publication ISSN: 1873-6777
Last Modified: 17 Apr 2024 07:13
Date Deposited: 05 Jul 2016 10:55
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Related URLs: http://www.scop ... tnerID=8YFLogxK (Scopus URL)
PURE Output Type: Article
Published Date: 2016-09
Published Online Date: 2016-06-18
Accepted Date: 2016-04-19
Submitted Date: 2015-11-02
Authors: Emrouznejad, Ali (ORCID Profile 0000-0001-8094-4244)
Yang, Guo-liang

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