Environmental efficiency analysis of transportation system in China: A non-radial DEA approach

Chang, Young Tae; Zhang, Ning; Danao, Denise; Zhang, Nan

doi:10.1016/j.enpol.2013.03.011

Cited by 406 publications

(158 citation statements)

References 33 publications

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“…Lin and Hong [34] evaluated the operational performance of 20 major airports around the world using the DEA model. Chang et al [35] and Chung et al [36] analyzed the environmental and energy efficiency of China's transportation sector and maximize the energy-saving potential of the transportation sector in China's 30 administrative regions. However, little of this research in the transportation sector considers changes over longer time scales, and contained few analyses of spatial scales.…”

Section: Literature Reviewmentioning

confidence: 99%

Analysis of the Environmental Efficiency of the Chinese Transportation Sector Using an Undesirable Output Slacks-Based Measure Data Envelopment Analysis Model

2015

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Many countries are attempting to reduce energy consumption and CO2 emissions while increasing the productivity and efficiency of their industries. An undesirable-output-oriented data envelopment analysis (DEA) model with slacks-based measure (SBM) was used to evaluate the changes in the environmental efficiency of the transportation sector in 30 Chinese provinces (municipalities and autonomous regions) between 2003 and 2012. The potential for decreasing CO2 emissions and energy saving was also assessed. Transportation was found to be inefficient in most of the provinces and the average environmental efficiency was low (0.45). The overall average efficiency reached a maximum in 2005 and continually decreased until a minimum was reached in 2009; since then, it has increased. In general, transportation is more efficient in eastern than in central or western China. A sensitivity analysis was also carried out on the input and output indicators. Based on these findings, some policies are proposed to improve the environmental efficiency of the transportation sector in China.

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Section: Literature Reviewmentioning

confidence: 99%

Analysis of the Environmental Efficiency of the Chinese Transportation Sector Using an Undesirable Output Slacks-Based Measure Data Envelopment Analysis Model

2015

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“…The difference in the two methods arises because the former adopts the geometric means of the distance functions, whereas the latter uses the arithmetic means of the distances in two periods. Many recent studies have noted that the results based on the Luenberger index are more robust than those based on the Malmquist index [26], and Chang et al [27] have made a further improvement by applying a non-radial Luenberger index. This approach was widely applied in later studies to model environmentally sensitive productivity [28].…”

Section: Introductionmentioning

confidence: 99%

Measuring the Total-Factor Carbon Emission Performance of Industrial Land Use in China Based on the Global Directional Distance Function and Non-Radial Luenberger Productivity Index

et al. 2016

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Industry is a major contributor to carbon emissions in China, and industrial land is an important input to industrial production. Therefore, a detailed analysis of the carbon emission performance of industrial land use is necessary for making reasonable carbon reduction policies that promote the sustainable use of industrial land. This paper aims to analyze the dynamic changes in the total-factor carbon emission performance of industrial land use (TCPIL) in China by applying a global directional distance function (DDF) and non-radial Luenberger productivity index. The empirical results show that the eastern region enjoys better TCPIL than the central and western regions, but the regional gaps in TCPIL are narrowing. The growth in NLCPILs (non-radial Luenberger carbon emission performance of industrial land use) in the eastern and central regions is mainly driven by technological progress, whereas efficiency improvements contribute more to the growth of NLCPIL in the western region. The provinces in the eastern region have the most innovative and environmentally-friendly production technologies. The results of the analysis of the influencing factors show implications for improving the NLCPIL, including more investment in industrial research and development (R&D), the implementation of carbon emission reduction policies, reduction in the use of fossil energy, especially coal, in the process of industrial production, actively learning about foreign advanced technology, properly solving the problem of surplus labor in industry and the expansion of industrial development.Keywords: industrial land; total-factor carbon emission performance of industrial land use (TCPIL); non-radial Luenberger productivity index; non-radial Luenberger carbon emission performance of industrial land use (NLCPIL); directional distance function (DDF); China

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“…Based on these findings, they concluded that the modal split in favor of rail transport will provide energy savings and CO2 emission reductions. Chang et al [38] presented a SBM-DEA model to assess environmental efficiency in the transport sector in China, and they stated that the application of a slacks-based measure (SBM) may help reveal the real energy consumption process. Zhou et al [39] applied the DEA approach to measure the energy efficiency performance of the transport sector in China at the provincial level, and they considered non-energy and energy inputs as well as desirable and undesirable outputs to maximize the energy-saving potential of the transport sector.…”

Section: Introductionmentioning

confidence: 99%

“…Bi et al [35] adopted a slacks-based DEA model to evaluate the energy efficiency of China's thermal power generation, with SO2, NOX and soot considered undesirable outputs. In addition, the super DEA model [36], range-adjusted measure (RAM)-DEA model [37], non-radial DEA model [34,38] and DEA-Malmquist model [29,32] have also been also employed to explore energy efficiency issues in China.…”

Section: Introductionmentioning

confidence: 99%

Estimating Energy Consumption of Transport Modes in China Using DEA

et al. 2015

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Abstract:The rapid growth of transport requirements in China will incur increasing transport energy demands and associated environmental pressures. In this paper, we employ a generalized data envelopment analysis (DEA) to evaluate the relative energy efficiency of rail, road, aviation and water transport from 1971 to 2011 by considering the energy input and passenger-kilometers (PKM) and freight ton-kilometers (TKM) outputs. The results show that the optimal energy efficiencies observed in 2011 are for rail and water transport, with the opposite observed for the energy efficiencies of aviation and road transport. In addition, we extend the DEA model to estimate future transport energy consumption in China. If each transport mode in 2020 is optimized throughout the observed period, the national transport energy consumption in 2020 will reach 497,701 kilotons coal equivalent (ktce), whereas the annual growth rate from 2011 to 2020 will be 5.7%. Assuming that efficiency improvements occur in this period, the estimated national transport energy consumption in 2020 will be 443,126 ktce, whereas the annual growth rate from 2011 to 2020 will be 4.4%, which is still higher than that of the national total energy consumption (3.8%).

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Environmental efficiency analysis of transportation system in China: A non-radial DEA approach

Cited by 406 publications

References 33 publications

Analysis of the Environmental Efficiency of the Chinese Transportation Sector Using an Undesirable Output Slacks-Based Measure Data Envelopment Analysis Model

Analysis of the Environmental Efficiency of the Chinese Transportation Sector Using an Undesirable Output Slacks-Based Measure Data Envelopment Analysis Model

Measuring the Total-Factor Carbon Emission Performance of Industrial Land Use in China Based on the Global Directional Distance Function and Non-Radial Luenberger Productivity Index

Estimating Energy Consumption of Transport Modes in China Using DEA

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