A framework for measuring global Malmquist–Luenberger productivity index with CO2 emissions on Chinese manufacturing industries

Emrouznejad, Ali; Yang, Guo Liang

doi:10.1016/j.energy.2016.09.032

Cited by 116 publications

(45 citation statements)

References 61 publications

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“…In order to provide usable information for this objective, the index is therefore distinguishing between a technological progress for the whole set of DMUs-individually adapted for each institution-on the one side and the technological efficiency on the other side [77]. A series of applications do exist for this specific longitudinal efficiency analysis, as shown for example by Thanassoulis, Shiraz and Maniadakis [78] for water and gas companies from different countries, Emrouznejad and Yang [79] for CO 2 emissions of Chinese manufacturing, Sueyoshi and Goto [80] for the environmental evaluation of petroleum companies, or Chang, Kuo and Chen [81] for a pollution evaluation in China.…”

Section: Efficiency Measurementmentioning

confidence: 99%

How to Achieve Supply Chain Sustainability Efficiently? Taming the Triple Bottom Line Split Business Cycle

Klumpp

2018

Sustainability

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For sustainable supply chains, specific concepts regarding how to efficiently improve sustainability are needed in a global comprehensive triple bottom line (TBL) approach, especially for forwarders as central actors in supply chain design. Such specific advice is provided by reporting empirical DEA Malmquist index findings from seven large European forwarders regarding a TBL sustainability analysis from 2006 to 2016. A major obstacle in improving sustainability consists in the newly discovered fact that with the business cycle, the three TBL areas of economic, ecologic and social objectives for logistics are undergoing different up-and down-ward trends, making it very hard to improve all three simultaneously. Additional factors are identified in the characteristics of size and government influence regarding the sustainability efficiency of forwarders. This has important impacts on supply chain design like e.g., with selection criteria.

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Section: Efficiency Measurementmentioning

confidence: 99%

How to Achieve Supply Chain Sustainability Efficiently? Taming the Triple Bottom Line Split Business Cycle

Klumpp

2018

Sustainability

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“…As its advantage at dealing with measuring the relative efficiency of decision making units with multiple inputs and outputs, DEA has been widely adopted to evaluate the energy, environmental, and carbon emission efficiency . Although DEA‐based assessment method could overcome the subjectivity exists in the index evaluation method, the static efficiency evaluation method fails to provide specific factors of trend change; the Malmquist productivity index based on the DEA method makes up for this deficiency …”

Section: Literaturementioning

confidence: 99%

“…[28][29][30][31] Although DEA-based assessment method could overcome the subjectivity exists in the index evaluation method, the static efficiency evaluation method fails to provide specific factors of trend change; the Malmquist productivity index based on the DEA method makes up for this deficiency. [32][33][34][35] The third group is based on environment-economy elasticity to analyze the decoupling status of regional or industry level. Decoupling refers to two variables change at different speed, the Organization for Economic Co-operation and Development (OEDC) defined decoupling as breaking the link between "environmental bads" and "economic goods."…”

Section: Literaturementioning

confidence: 99%

China's provincial energy‐related carbon emissions‐economy nexus: A two‐stage framework based on decoupling analysis and panel vector autoregression

Pan

Liu

Tsai

et al. 2019

Energy Science & Engineering

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China is transforming the growth model and speeding up industrial structural improvement and upgrading now and in the coming years, which means the slowdown of economic growth and more serious environmental costs in economic and social development would be the “New Normal.” As the world's largest energy consumer and carbon‐emitting country, China's emissions reduction commitments are crucial to global greenhouse gas emissions mitigation, so there is a profusion of research focused on China's economy‐environment nexus. Among which, the dynamic relationship of carbon emission and economic growth and its evolution combined the national, regional, provincial data have not been discussed thoroughly. This paper analyses the elasticity of economic performance of carbon emissions based on 30 Chinese provincial data from 2000 to 2016; furthermore, a panel vector autoregressive model is constructed to discuss the interactions of variables within environmental economic system. It is concluded that China is experiencing a turning point from weak decoupling to strong decoupling in recent years, and its economic performance of carbon emissions has been gradually improved with larger disparities among provinces though. Regression result confirms the role of the energy mix on carbon emissions, and it also indicates that the impact of most factors influencing that have been discussed in previous studies may not be direct, prominent, and for long term.

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“…Zhao, Ke et al [2] pointed out that more than 50% of fossil fuels are consumed directly or indirectly by the manufacturing industry. Manufacturing is responsible for nearly a third of global energy consumption and 36% of carbon dioxide emissions [3]. Consequently, the goals of improving energy efficiency and reducing emission reduction have placed great demand on the manufacturing industry.…”

Section: Introductionmentioning

confidence: 99%

Analysis of Coordinated Development of Energy and Environment in China’s Manufacturing Industry under Environmental Regulation: A Comparative Study of Sub-Industries

et al. 2019

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In order to explore the impact of environmental regulation on the coordinated development of energy and the environment with the background of governance transition, we propose a three-stage integrated approach and use the panel data of China’s manufacturing industry 27 sub-sectors during the period of 2006–2015. In the first stage, according to the environmental pollution intensity, the manufacturing industry is divided into heavily polluting industry, moderately polluting industry, and lightly polluting industry. The second stage is employed the slacks-based measure (SBM)-undesirable method to study the sub-industries’ green energy-environmental efficiency under different environmental pollution intensities. Besides, the dynamic changes of technical innovation and efficiency among different industries are analyzed through the Malmquist productivity index. For the purpose of investigating the transmission mechanism of the Porter’s hypothesis and exploring the compound effects of environmental regulation and governance transition on green development, in the third stage, we use the panel data analysis to conduct more in-depth research on the relationship between environmental regulation, governance transition, and technical innovation. Results show that the highest average green energy-environmental efficiency is lightly polluting industry, which is 0.52, followed by the heavily polluting industry at 0.40, and the lowest is the moderately polluting industry, which is 0.32. By decomposing total factor productivity, heavily polluting industry is at the forefront of technical innovation. Panel data analysis results indicate that investment in research and development and governance transition could promote the growth of total factor productivity for manufacturing.

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A framework for measuring global Malmquist–Luenberger productivity index with CO2 emissions on Chinese manufacturing industries

Cited by 116 publications

References 61 publications

How to Achieve Supply Chain Sustainability Efficiently? Taming the Triple Bottom Line Split Business Cycle

How to Achieve Supply Chain Sustainability Efficiently? Taming the Triple Bottom Line Split Business Cycle

China's provincial energy‐related carbon emissions‐economy nexus: A two‐stage framework based on decoupling analysis and panel vector autoregression

Analysis of Coordinated Development of Energy and Environment in China’s Manufacturing Industry under Environmental Regulation: A Comparative Study of Sub-Industries

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