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

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  • Xiaowei Song

    (State Key Laboratory of Pollution Control and Resources Reuse, School of the Environment, Nanjing University, Nanjing 210023, China)

  • Yongpei Hao

    (School of Geographic and Oceanographic Sciences, Nanjing University, Nanjing 210023, China)

  • Xiaodong Zhu

    (State Key Laboratory of Pollution Control and Resources Reuse, School of the Environment, Nanjing University, Nanjing 210023, China)

Abstract

Many countries are attempting to reduce energy consumption and CO 2 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 CO 2 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.

Suggested Citation

  • Xiaowei Song & Yongpei Hao & Xiaodong Zhu, 2015. "Analysis of the Environmental Efficiency of the Chinese Transportation Sector Using an Undesirable Output Slacks-Based Measure Data Envelopment Analysis Model," Sustainability, MDPI, vol. 7(7), pages 1-20, July.
    • Handle: RePEc:gam:jsusta:v:7:y:2015:i:7:p:9187-9206:d:52592
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    References listed on IDEAS

    as
    1. Li, Lan-Bing & Hu, Jin-Li, 2012. "Ecological total-factor energy efficiency of regions in China," Energy Policy, Elsevier, vol. 46(C), pages 216-224.
    2. Gale Boyd & George Tolley & Joseph Pang, 2002. "Plant Level Productivity, Efficiency, and Environmental Performance of the Container Glass Industry," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 23(1), pages 29-43, September.
    3. Golany, B & Roll, Y, 1989. "An application procedure for DEA," Omega, Elsevier, vol. 17(3), pages 237-250.
    4. Song, Malin & An, Qingxian & Zhang, Wei & Wang, Zeya & Wu, Jie, 2012. "Environmental efficiency evaluation based on data envelopment analysis: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 16(7), pages 4465-4469.
    5. William Cooper & Kyung Park & Jesus Pastor, 1999. "RAM: A Range Adjusted Measure of Inefficiency for Use with Additive Models, and Relations to Other Models and Measures in DEA," Journal of Productivity Analysis, Springer, vol. 11(1), pages 5-42, February.
    6. Lin, L.C. & Hong, C.H., 2006. "Operational performance evaluation of international major airports: An application of data envelopment analysis," Journal of Air Transport Management, Elsevier, vol. 12(6), pages 342-351.
    7. Tongzon, Jose, 2001. "Efficiency measurement of selected Australian and other international ports using data envelopment analysis," Transportation Research Part A: Policy and Practice, Elsevier, vol. 35(2), pages 107-122, February.
    8. Shi, Guang-Ming & Bi, Jun & Wang, Jin-Nan, 2010. "Chinese regional industrial energy efficiency evaluation based on a DEA model of fixing non-energy inputs," Energy Policy, Elsevier, vol. 38(10), pages 6172-6179, October.
    9. Telle, Kjetil & Larsson, Jan, 2007. "Do environmental regulations hamper productivity growth? How accounting for improvements of plants' environmental performance can change the conclusion," Ecological Economics, Elsevier, vol. 61(2-3), pages 438-445, March.
    10. Kumar Mandal, Sabuj & Madheswaran, S., 2010. "Environmental efficiency of the Indian cement industry: An interstate analysis," Energy Policy, Elsevier, vol. 38(2), pages 1108-1118, February.
    11. Fukuyama, Hirofumi & Weber, William L., 2010. "A slacks-based inefficiency measure for a two-stage system with bad outputs," Omega, Elsevier, vol. 38(5), pages 398-409, October.
    12. M C A Silva Portela & E Thanassoulis & G Simpson, 2004. "Negative data in DEA: a directional distance approach applied to bank branches," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 55(10), pages 1111-1121, October.
    13. Chang, Young-Tae & Zhang, Ning & Danao, Denise & Zhang, Nan, 2013. "Environmental efficiency analysis of transportation system in China: A non-radial DEA approach," Energy Policy, Elsevier, vol. 58(C), pages 277-283.
    14. Boyd, Gale A. & Pang, Joseph X., 2000. "Estimating the linkage between energy efficiency and productivity," Energy Policy, Elsevier, vol. 28(5), pages 289-296, May.
    15. Verughese Jacob & Subhash Sharma & Richard Grabowski, 1997. "Capital stock estimates for major sectors and disaggregated manufacturing in selected OECD countries," Applied Economics, Taylor & Francis Journals, vol. 29(5), pages 563-579.
    16. Charnes, A. & Cooper, W. W. & Golany, B. & Seiford, L. & Stutz, J., 1985. "Foundations of data envelopment analysis for Pareto-Koopmans efficient empirical production functions," Journal of Econometrics, Elsevier, vol. 30(1-2), pages 91-107.
    17. Färe, Rolf & Grosskopf, Shawna, 2010. "Directional distance functions and slacks-based measures of efficiency," European Journal of Operational Research, Elsevier, vol. 200(1), pages 320-322, January.
    18. Sueyoshi, Toshiyuki & Goto, Mika & Ueno, Takahiro, 2010. "Performance analysis of US coal-fired power plants by measuring three DEA efficiencies," Energy Policy, Elsevier, vol. 38(4), pages 1675-1688, April.
    19. Zhou, P. & Ang, B.W. & Wang, H., 2012. "Energy and CO2 emission performance in electricity generation: A non-radial directional distance function approach," European Journal of Operational Research, Elsevier, vol. 221(3), pages 625-635.
    20. Fare, Rolf, et al, 1989. "Multilateral Productivity Comparisons When Some Outputs Are Undesirable: A Nonparametric Approach," The Review of Economics and Statistics, MIT Press, vol. 71(1), pages 90-98, February.
    21. Charnes, A. & Cooper, W. W. & Rhodes, E., 1978. "Measuring the efficiency of decision making units," European Journal of Operational Research, Elsevier, vol. 2(6), pages 429-444, November.
    22. Chung, William & Zhou, Guanghui & Yeung, Iris M.H., 2013. "A study of energy efficiency of transport sector in China from 2003 to 2009," Applied Energy, Elsevier, vol. 112(C), pages 1066-1077.
    23. Seiford, Lawrence M. & Zhu, Joe, 2002. "Modeling undesirable factors in efficiency evaluation," European Journal of Operational Research, Elsevier, vol. 142(1), pages 16-20, October.
    24. Zhou, P. & Ang, B.W. & Poh, K.L., 2006. "Slacks-based efficiency measures for modeling environmental performance," Ecological Economics, Elsevier, vol. 60(1), pages 111-118, November.
    25. Barıs Yoruk & Osnman Zaim, 2008. "International regulations and environmental performance," Applied Economics, Taylor & Francis Journals, vol. 40(7), pages 807-822.
    26. Merkert, Rico & Hensher, David A., 2011. "The impact of strategic management and fleet planning on airline efficiency - A random effects Tobit model based on DEA efficiency scores," Transportation Research Part A: Policy and Practice, Elsevier, vol. 45(7), pages 686-695, August.
    27. Daniel Tyteca, 1997. "Linear Programming Models for the Measurement of Environmental Performance of Firms—Concepts and Empirical Results," Journal of Productivity Analysis, Springer, vol. 8(2), pages 183-197, May.
    28. Tone, Kaoru, 2001. "A slacks-based measure of efficiency in data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 130(3), pages 498-509, May.
    29. Burnett, Royce D. & Hansen, Don R., 2008. "Ecoefficiency: Defining a role for environmental cost management," Accounting, Organizations and Society, Elsevier, vol. 33(6), pages 551-581, August.
    30. Bian, Yiwen & Yang, Feng, 2010. "Resource and environment efficiency analysis of provinces in China: A DEA approach based on Shannon's entropy," Energy Policy, Elsevier, vol. 38(4), pages 1909-1917, April.
    31. Scheel, Holger, 2001. "Undesirable outputs in efficiency valuations," European Journal of Operational Research, Elsevier, vol. 132(2), pages 400-410, July.
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