IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v7y2015i7p9187-9206d52592.html
   My bibliography  Save this article

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

Author

Listed:
  • 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
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/7/7/9187/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2071-1050/7/7/9187/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. 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.
    2. 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.
    3. 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.
    4. 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.
    5. Barıs Yoruk & Osnman Zaim, 2008. "International regulations and environmental performance," Applied Economics, Taylor & Francis Journals, vol. 40(7), pages 807-822.
    6. 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.
    7. 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.
    8. 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.
    9. 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.
    10. 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.
    11. 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.
    12. 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.
    13. 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.
    14. 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.
    15. Golany, B & Roll, Y, 1989. "An application procedure for DEA," Omega, Elsevier, vol. 17(3), pages 237-250.
    16. 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.
    17. 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.
    18. 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.
    19. 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.
    20. 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.
    21. 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.
    22. 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.
    23. 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.
    24. 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.
    25. 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.
    26. 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.
    27. 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.
    28. 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.
    29. 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.
    30. 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.
    31. Scheel, Holger, 2001. "Undesirable outputs in efficiency valuations," European Journal of Operational Research, Elsevier, vol. 132(2), pages 400-410, July.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Sueyoshi, Toshiyuki & Yuan, Yan & Goto, Mika, 2017. "A literature study for DEA applied to energy and environment," Energy Economics, Elsevier, vol. 62(C), pages 104-124.
    2. Meng, Fanyi & Su, Bin & Thomson, Elspeth & Zhou, Dequn & Zhou, P., 2016. "Measuring China’s regional energy and carbon emission efficiency with DEA models: A survey," Applied Energy, Elsevier, vol. 183(C), pages 1-21.
    3. Quintano, Claudio & Mazzocchi, Paolo & Rocca, Antonella, 2021. "Evaluation of the eco-efficiency of territorial districts with seaport economic activities," Utilities Policy, Elsevier, vol. 71(C).
    4. Wen Guo & Tao Sun & Hongjun Dai, 2017. "Efficiency Allocation of Provincial Carbon Reduction Target in China’s “13·5” Period: Based on Zero-Sum-Gains SBM Model," Sustainability, MDPI, vol. 9(2), pages 1-18, January.
    5. Truc Linh Le & Pai-Po Lee & Ke Chung Peng & Rebecca H. Chung, 2019. "Evaluation of total factor productivity and environmental efficiency of agriculture in nine East Asian countries," Agricultural Economics, Czech Academy of Agricultural Sciences, vol. 65(6), pages 249-258.
    6. Ying Li & Yung-Ho Chiu & Liang Chun Lu, 2018. "Regional Energy, CO 2 , and Economic and Air Quality Index Performances in China: A Meta-Frontier Approach," Energies, MDPI, vol. 11(8), pages 1-20, August.
    7. Xiangyu Hua & Haiping Lv & Xiangrong Jin, 2021. "Research on High-Quality Development Efficiency and Total Factor Productivity of Regional Economies in China," Sustainability, MDPI, vol. 13(15), pages 1-22, July.
    8. Mahmoudi, Reza & Emrouznejad, Ali & Shetab-Boushehri, Seyyed-Nader & Hejazi, Seyed Reza, 2020. "The origins, development and future directions of data envelopment analysis approach in transportation systems," Socio-Economic Planning Sciences, Elsevier, vol. 69(C).
    9. Mojtaba Ghiyasi & Farhad Taghizadeh-Hesary, 2021. "Environmental Efficiency Analysis for Multi Plants Production Technologies," Sustainability, MDPI, vol. 13(7), pages 1-18, April.
    10. Xiaohong Zhuang & Zhuyuan Li & Run Zheng & Sanggyun Na & Yulin Zhou, 2021. "Research on the Efficiency and Improvement of Rural Development in China: Based on Two-Stage Network SBM Model," Sustainability, MDPI, vol. 13(5), pages 1-21, March.
    11. Pyoungsoo Lee & You-Jin Park, 2017. "Eco-Efficiency Evaluation Considering Environmental Stringency," Sustainability, MDPI, vol. 9(4), pages 1-18, April.
    12. Ke Li & Malin Song, 2016. "Green Development Performance in China: A Metafrontier Non-Radial Approach," Sustainability, MDPI, vol. 8(3), pages 1-21, March.
    13. Paul Mugambi & Miguel Blanco & Daniel Ogachi & Marcos Ferasso & Lydia Bares, 2021. "Analysis of the Regional Efficiency of European Funds in Spain from the Perspective of Renewable Energy Production: The Regional Dimension," IJERPH, MDPI, vol. 18(9), pages 1-16, April.
    14. Zhao, Pengjun & Zeng, Liangen & Li, Peilin & Lu, Haiyan & Hu, Haoyu & Li, Chengming & Zheng, Mengyuan & Li, Haitao & Yu, Zhao & Yuan, Dandan & Xie, Jinxin & Huang, Qi & Qi, Yuting, 2022. "China's transportation sector carbon dioxide emissions efficiency and its influencing factors based on the EBM DEA model with undesirable outputs and spatial Durbin model," Energy, Elsevier, vol. 238(PC).
    15. Tianbo Tang & Jianxin You & Hui Sun & Hao Zhang, 2019. "Transportation Efficiency Evaluation Considering the Environmental Impact for China’s Freight Sector: A Parallel Data Envelopment Analysis," Sustainability, MDPI, vol. 11(18), pages 1-24, September.
    16. Hongxing Tu & Wei Dai & Xu Xiao, 2022. "Study on the Environmental Efficiency of the Chinese Cement Industry Based on the Undesirable Output DEA Model," Energies, MDPI, vol. 15(9), pages 1-13, May.
    17. Hao Zhang & Xinyue Wang & Letao Chen & Yujia Luo & Sujie Peng, 2022. "Evaluation of the Operational Efficiency and Energy Efficiency of Rail Transit in China’s Megacities Using a DEA Model," Energies, MDPI, vol. 15(20), pages 1-16, October.
    18. Marcos Ferasso & Miguel Blanco & Lydia Bares, 2021. "A Data Envelopment Analysis of the Impact of European Funds on Environmental Indicators," IJERPH, MDPI, vol. 18(6), pages 1-15, March.
    19. Gang Tian & Jian Shi & Licheng Sun & Xingle Long & Benhai Guo, 2017. "Dynamic changes in the energy–carbon performance of Chinese transportation sector: a meta-frontier non-radial directional distance function approach," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 89(2), pages 585-607, November.
    20. Yuan, Qianqian & Fang Chin Cheng, Charles & Wang, Jiayu & Zhu, Tian-Tian & Wang, Ke, 2020. "Inclusive and sustainable industrial development in China: An efficiency-based analysis for current status and improving potentials," Applied Energy, Elsevier, vol. 268(C).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Sueyoshi, Toshiyuki & Yuan, Yan & Goto, Mika, 2017. "A literature study for DEA applied to energy and environment," Energy Economics, Elsevier, vol. 62(C), pages 104-124.
    2. Halkos, George & Petrou, Kleoniki Natalia, 2018. "A critical review of the main methods to treat undesirable outputs in DEA," MPRA Paper 90374, University Library of Munich, Germany.
    3. Halkos, George & Petrou, Kleoniki Natalia, 2019. "Treating undesirable outputs in DEA: A critical review," Economic Analysis and Policy, Elsevier, vol. 62(C), pages 97-104.
    4. Jie Wu & Qingyuan Zhu & Pengzhen Yin & Malin Song, 2017. "Measuring energy and environmental performance for regions in China by using DEA-based Malmquist indices," Operational Research, Springer, vol. 17(3), pages 715-735, October.
    5. Zhou, Haibo & Yang, Yi & Chen, Yao & Zhu, Joe, 2018. "Data envelopment analysis application in sustainability: The origins, development and future directions," European Journal of Operational Research, Elsevier, vol. 264(1), pages 1-16.
    6. Zhou, P. & Ang, B.W. & Poh, K.L., 2008. "A survey of data envelopment analysis in energy and environmental studies," European Journal of Operational Research, Elsevier, vol. 189(1), pages 1-18, August.
    7. 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.
    8. Wu, Jie & Zhu, Qingyuan & Liang, Liang, 2016. "CO2 emissions and energy intensity reduction allocation over provincial industrial sectors in China," Applied Energy, Elsevier, vol. 166(C), pages 282-291.
    9. Arabi, Behrouz & Munisamy, Susila & Emrouznejad, Ali, 2015. "A new slacks-based measure of Malmquist–Luenberger index in the presence of undesirable outputs," Omega, Elsevier, vol. 51(C), pages 29-37.
    10. Ramli, Noor Asiah & Munisamy, Susila, 2015. "Eco-efficiency in greenhouse emissions among manufacturing industries: A range adjusted measure," Economic Modelling, Elsevier, vol. 47(C), pages 219-227.
    11. Yu, Dejian & He, Xiaorong, 2020. "A bibliometric study for DEA applied to energy efficiency: Trends and future challenges," Applied Energy, Elsevier, vol. 268(C).
    12. Young-Tae Chang & Nan Zhang, 2017. "Environmental efficiency of transportation sectors in China and Korea," Maritime Economics & Logistics, Palgrave Macmillan;International Association of Maritime Economists (IAME), vol. 19(1), pages 68-93, March.
    13. Gómez-Calvet, Roberto & Conesa, David & Gómez-Calvet, Ana Rosa & Tortosa-Ausina, Emili, 2014. "Energy efficiency in the European Union: What can be learned from the joint application of directional distance functions and slacks-based measures?," Applied Energy, Elsevier, vol. 132(C), pages 137-154.
    14. César Salazar & Roberto Cárdenas-Retamal & Marcela Jaime, 2023. "Environmental efficiency in the salmon industry—an exploratory analysis around the 2007 ISA virus outbreak and subsequent regulations in Chile," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 25(8), pages 8107-8135, August.
    15. Adler, Nicole & Volta, Nicola, 2016. "Accounting for externalities and disposability: A directional economic environmental distance function," European Journal of Operational Research, Elsevier, vol. 250(1), pages 314-327.
    16. Halkos, George E. & Tzeremes, Nickolaos G., 2013. "A conditional directional distance function approach for measuring regional environmental efficiency: Evidence from UK regions," European Journal of Operational Research, Elsevier, vol. 227(1), pages 182-189.
    17. Ning Zhang & Jong-Dae Kim, 2014. "Measuring sustainability by Energy Efficiency Analysis for Korean Power Companies: A Sequential Slacks-Based Efficiency Measure," Sustainability, MDPI, vol. 6(3), pages 1-13, March.
    18. Xiang Ji & Jiasen Sun & Qunwei Wang & Qianqian Yuan, 2019. "Revealing Energy Over-Consumption and Pollutant Over-Emission Behind GDP: A New Multi-criteria Sustainable Measure," Computational Economics, Springer;Society for Computational Economics, vol. 54(4), pages 1391-1421, December.
    19. Wang, Ke & Lu, Bin & Wei, Yi-Ming, 2013. "China’s regional energy and environmental efficiency: A Range-Adjusted Measure based analysis," Applied Energy, Elsevier, vol. 112(C), pages 1403-1415.
    20. Long, Xingle & Wu, Chao & Zhang, Jijian & Zhang, Jing, 2018. "Environmental efficiency for 192 thermal power plants in the Yangtze River Delta considering heterogeneity: A metafrontier directional slacks-based measure approach," Renewable and Sustainable Energy Reviews, Elsevier, vol. 82(P3), pages 3962-3971.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jsusta:v:7:y:2015:i:7:p:9187-9206:d:52592. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.