IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v12y2020i11p4613-d367625.html
   My bibliography  Save this article

Environmental Efficiency Measurement and Convergence Analysis of Interprovincial Road Transport in China

Author

Listed:
  • Hao Xu

    (School of Business, Anhui University, Hefei 230601, China)

  • Yeqing Wang

    (School of Business, Anhui University, Hefei 230601, China)

  • Hongwei Liu

    (School of Business, Anhui University, Hefei 230601, China)

  • Ronglu Yang

    (School of Business, Anhui University, Hefei 230601, China)

Abstract

Although road transport plays a vital role in promoting the development of China’s national economy, it also produces much harmful output in the process of road transport. Various types of harmful output generate high social costs. In order to improve efficiency and protect the environment at the same time, a variety of undesirable outputs need to be considered when evaluating the environmental efficiency of road transport. In this paper, the performance of the road transport systems in 30 regions of China is evaluated considering multiple harmful outputs (noise, carbon emission, direct property losses), by employing the directional distance function. Further, a convergence analysis of the environmental efficiency of road transport is carried out. The empirical results show that the environmental efficiency of overall road transport in China increased from 0.8851 to 0.9633 from 2010 to 2017. Moreover, the environmental efficiency gaps between the eastern, central and western areas have narrowed over time, but still exist. Additionally, the results of σ convergence analysis show that convergence of environmental efficiency exists in the whole country and the western area, while only weak convergence exists in the eastern and central areas. Both absolute β convergence and conditional β convergence exist in the eastern, central and western areas. While the environmental efficiency improved over the study period, the environmental efficiencies of road transport in some provinces remain inefficient, which deserves more attention from those seeking to improve environmental efficiency. The paper concludes with suggestions for improving the environmental efficiency of road transport.

Suggested Citation

  • Hao Xu & Yeqing Wang & Hongwei Liu & Ronglu Yang, 2020. "Environmental Efficiency Measurement and Convergence Analysis of Interprovincial Road Transport in China," Sustainability, MDPI, vol. 12(11), pages 1-16, June.
  • Handle: RePEc:gam:jsusta:v:12:y:2020:i:11:p:4613-:d:367625
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/12/11/4613/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2071-1050/12/11/4613/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Karlaftis, Matthew G., 2004. "A DEA approach for evaluating the efficiency and effectiveness of urban transit systems," European Journal of Operational Research, Elsevier, vol. 152(2), pages 354-364, January.
    2. Jain, Priyanka & Cullinane, Sharon & Cullinane, Kevin, 2008. "The impact of governance development models on urban rail efficiency," Transportation Research Part A: Policy and Practice, Elsevier, vol. 42(9), pages 1238-1250, November.
    3. Samuel Egbetokun & Evans S. Osabuohien & Temidayo Akinbobola & Olaronke Onanuga & Obindah Gershon & Victoria Okafor, 2019. "Environmental Pollution, Economic Growth and Institutional Quality: Exploring the Nexus in Nigeria," Research Africa Network Working Papers 19/059, Research Africa Network (RAN).
    4. Yang, Hongliang & Pollitt, Michael, 2009. "Incorporating both undesirable outputs and uncontrollable variables into DEA: The performance of Chinese coal-fired power plants," European Journal of Operational Research, Elsevier, vol. 197(3), pages 1095-1105, September.
    5. Fan, L.W. & Wu, F. & Zhou, P., 2014. "Efficiency measurement of Chinese airports with flight delays by directional distance function," Journal of Air Transport Management, Elsevier, vol. 34(C), pages 140-145.
    6. Xie, Bai-Chen & Shang, Li-Feng & Yang, Si-Bo & Yi, Bo-Wen, 2014. "Dynamic environmental efficiency evaluation of electric power industries: Evidence from OECD (Organization for Economic Cooperation and Development) and BRIC (Brazil, Russia, India and China) countrie," Energy, Elsevier, vol. 74(C), pages 147-157.
    7. 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.
    8. Cui, Qiang & Li, Ye, 2015. "An empirical study on the influencing factors of transportation carbon efficiency: Evidences from fifteen countries," Applied Energy, Elsevier, vol. 141(C), pages 209-217.
    9. Barro, Robert J & Sala-i-Martin, Xavier, 1992. "Convergence," Journal of Political Economy, University of Chicago Press, vol. 100(2), pages 223-251, April.
      • Barro, R.J. & Sala-I-Martin, X., 1991. "Convergence," Papers 645, Yale - Economic Growth Center.
      • Barro, Robert J. & Sala-i-Martin, Xavier, 1992. "Convergence," Scholarly Articles 3451299, Harvard University Department of Economics.
    10. Liu, Hongwei & Wu, Jie & Chu, Junfei, 2019. "Environmental efficiency and technological progress of transportation industry-based on large scale data," Technological Forecasting and Social Change, Elsevier, vol. 144(C), pages 475-482.
    11. Yu, Ming-Miin & Fan, Chih-Ku, 2009. "Measuring the performance of multimode bus transit: A mixed structure network DEA model," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 45(3), pages 501-515, May.
    12. 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.
    13. Martini, Gianmaria & Manello, Alessandro & Scotti, Davide, 2013. "The influence of fleet mix, ownership and LCCs on airports’ technical/environmental efficiency," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 50(C), pages 37-52.
    14. Holmgren, Johan, 2013. "The efficiency of public transport operations – An evaluation using stochastic frontier analysis," Research in Transportation Economics, Elsevier, vol. 39(1), pages 50-57.
    15. Robert J. Barro & Xavier Sala-i-Martin, 1991. "Convergence across States and Regions," Brookings Papers on Economic Activity, Economic Studies Program, The Brookings Institution, vol. 22(1), pages 107-182.
    16. Bhattacharya, Mita & Inekwe, John Nkwoma & Sadorsky, Perry & Saha, Anjan, 2018. "Convergence of energy productivity across Indian states and territories," Energy Economics, Elsevier, vol. 74(C), pages 427-440.
    17. Tingting Yang & Xuefeng Guan & Yuehui Qian & Weiran Xing & Huayi Wu, 2019. "Efficiency Evaluation of Urban Road Transport and Land Use in Hunan Province of China Based on Hybrid Data Envelopment Analysis (DEA) Models," Sustainability, MDPI, vol. 11(14), pages 1-18, July.
    18. Ayadi, Ahmed & Hammami, Sami, 2015. "An analysis of the performance of public bus transport in Tunisian cities," Transportation Research Part A: Policy and Practice, Elsevier, vol. 75(C), pages 51-60.
    19. R. G. Chambers & Y. Chung & R. Färe, 1998. "Profit, Directional Distance Functions, and Nerlovian Efficiency," Journal of Optimization Theory and Applications, Springer, vol. 98(2), pages 351-364, August.
    20. Pal, Debdatta & Mitra, Subrata K., 2016. "An application of the directional distance function with the number of accidents as an undesirable output to measure the technical efficiency of state road transport in India," Transportation Research Part A: Policy and Practice, Elsevier, vol. 93(C), pages 1-12.
    21. Färe, Rolf & Grosskopf, Shawna & Pasurka, Carl A., 2007. "Environmental production functions and environmental directional distance functions," Energy, Elsevier, vol. 32(7), pages 1055-1066.
    22. Bhattacharya, Mita & Inekwe, John N. & Sadorsky, Perry, 2020. "Convergence of energy productivity in Australian states and territories: Determinants and forecasts," Energy Economics, Elsevier, vol. 85(C).
    23. Wang, Ke & Wei, Yi-Ming & Zhang, Xian, 2013. "Energy and emissions efficiency patterns of Chinese regions: A multi-directional efficiency analysis," Applied Energy, Elsevier, vol. 104(C), pages 105-116.
    24. Fei Ma & Xiaodan Li & Qipeng Sun & Fei Liu & Wenlin Wang & Libiao Bai, 2018. "Regional Differences and Spatial Aggregation of Sustainable Transport Efficiency: A Case Study of China," Sustainability, MDPI, vol. 10(7), pages 1-23, July.
    25. Guoping Mei & Jingyi Gan & Ning Zhang, 2015. "Metafrontier Environmental Efficiency for China’s Regions: A Slack-Based Efficiency Measure," Sustainability, MDPI, vol. 7(4), pages 1-18, April.
    26. 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.
    27. Bian, Junsong & Zhao, Xuan, 2020. "Tax or subsidy? An analysis of environmental policies in supply chains with retail competition," European Journal of Operational Research, Elsevier, vol. 283(3), pages 901-914.
    28. Song, Malin & Zheng, Wanping & Wang, Zeya, 2016. "Environmental efficiency and energy consumption of highway transportation systems in China," International Journal of Production Economics, Elsevier, vol. 181(PB), pages 441-449.
    29. Miller, Stephen M. & Upadhyay, Mukti P., 2002. "Total factor productivity and the convergence hypothesis," Journal of Macroeconomics, Elsevier, vol. 24(2), pages 267-286, June.
    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. Chang, Lei & Taghizadeh-Hesary, Farhad & Mohsin, Muhammad, 2023. "Role of artificial intelligence on green economic development: Joint determinates of natural resources and green total factor productivity," Resources Policy, Elsevier, vol. 82(C).
    2. Lin, Chia-Yang & Chau, Ka Yin & Tran, Trung Kien & Sadiq, Muhammad & Van, Le & Hien Phan, Thi Thu, 2022. "Development of renewable energy resources by green finance, volatility and risk: Empirical evidence from China," Renewable Energy, Elsevier, vol. 201(P1), pages 821-831.
    3. Gu, Xiao & Alamri, Ahmad Mohammed & Ahmad, Maaz & Alsagr, Naif & Zhong, Xiangming & Wu, Tong, 2023. "Natural resources extraction and green finance: Dutch disease and COP27 targets for OECD countries," Resources Policy, Elsevier, vol. 81(C).
    4. Yingjuan Li & Qiong Lin & Jianyu Zhang & Liuhua Fang & Yi Li & Lianjun Zhang & Chuanhao Wen, 2023. "Convergence Analysis of the Overall Benefits of Returning Farmland into Forest in the Upper Yangtze River Basin, China," Sustainability, MDPI, vol. 15(2), pages 1-18, January.

    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. Song, Malin & Wang, Jianlin, 2018. "Environmental efficiency evaluation of thermal power generation in China based on a slack-based endogenous directional distance function model," Energy, Elsevier, vol. 161(C), pages 325-336.
    2. 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.
    3. Pal, Debdatta & Mitra, Subrata K., 2016. "An application of the directional distance function with the number of accidents as an undesirable output to measure the technical efficiency of state road transport in India," Transportation Research Part A: Policy and Practice, Elsevier, vol. 93(C), pages 1-12.
    4. Alizadeh, Reza & Gharizadeh Beiragh, Ramin & Soltanisehat, Leili & Soltanzadeh, Elham & Lund, Peter D., 2020. "Performance evaluation of complex electricity generation systems: A dynamic network-based data envelopment analysis approach," Energy Economics, Elsevier, vol. 91(C).
    5. Zhang, Ning & Zhao, Yu & Wang, Na, 2022. "Is China's energy policy effective for power plants? Evidence from the 12th Five-Year Plan energy saving targets," Energy Economics, Elsevier, vol. 112(C).
    6. Sun, Jiasen & Yuan, Yang & Yang, Rui & Ji, Xiang & Wu, Jie, 2017. "Performance evaluation of Chinese port enterprises under significant environmental concerns: An extended DEA-based analysis," Transport Policy, Elsevier, vol. 60(C), pages 75-86.
    7. Zhang, Bin & Lu, Danting & He, Yan & Chiu, Yung-ho, 2018. "The efficiencies of resource-saving and environment: A case study based on Chinese cities," Energy, Elsevier, vol. 150(C), pages 493-507.
    8. Kounetas, Konstantinos & Zervopoulos, Panagiotis D., 2019. "A cross-country evaluation of environmental performance: Is there a convergence-divergence pattern in technology gaps?," European Journal of Operational Research, Elsevier, vol. 273(3), pages 1136-1148.
    9. Arabi, Behrouz & Munisamy, Susila & Emrouznejad, Ali & Shadman, Foroogh, 2014. "Power industry restructuring and eco-efficiency changes: A new slacks-based model in Malmquist–Luenberger Index measurement," Energy Policy, Elsevier, vol. 68(C), pages 132-145.
    10. Yao, Di & Xu, Liqun & Li, Jinpei, 2020. "Does technical efficiency play a mediating role between bus facility scale and ridership attraction? Evidence from bus practices in China," Transportation Research Part A: Policy and Practice, Elsevier, vol. 132(C), pages 77-96.
    11. Wang, Ke & Wei, Yi-Ming & Huang, Zhimin, 2018. "Environmental efficiency and abatement efficiency measurements of China's thermal power industry: A data envelopment analysis based materials balance approach," European Journal of Operational Research, Elsevier, vol. 269(1), pages 35-50.
    12. Ying Li & Yung‐ho Chiu & Tai‐Yu Lin & Hongyi Cen & Yabin Liu, 2021. "Evaluation of natural disaster treatment efficiency in 27 Chinese provinces," Natural Resources Forum, Blackwell Publishing, vol. 45(3), pages 256-288, August.
    13. Xiaohong Liu & Jiasen Sun & Feng Yang & Jie Wu, 2020. "How ownership structure affects bank deposits and loan efficiencies: an empirical analysis of Chinese commercial banks," Annals of Operations Research, Springer, vol. 290(1), pages 983-1008, July.
    14. Merkert, Rico & Mulley, Corinne & Hakim, Md Mahbubul, 2017. "Determinants of bus rapid transit (BRT) system revenue and effectiveness – A global benchmarking exercise," Transportation Research Part A: Policy and Practice, Elsevier, vol. 106(C), pages 75-88.
    15. Chaozheng Zhang & Yangyue Su & Gangqiao Yang & Danling Chen & Rongxuan Yang, 2020. "Spatial-Temporal Characteristics of Cultivated Land Use Efficiency in Major Function-Oriented Zones: A Case Study of Zhejiang Province, China," Land, MDPI, vol. 9(4), pages 1-20, April.
    16. Fangqing Wei & Junfei Chu & Jiayun Song & Feng Yang, 2019. "A cross-bargaining game approach for direction selection in the directional distance function," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 41(3), pages 787-807, September.
    17. Du, Huibin & Matisoff, Daniel C. & Wang, Yangyang & Liu, Xi, 2016. "Understanding drivers of energy efficiency changes in China," Applied Energy, Elsevier, vol. 184(C), pages 1196-1206.
    18. Ke Wang & Yi-Ming Wei & Zhimin Huang, 2017. "Environmental efficiency and abatement efficiency measurements of China¡¯s thermal power industry: A data envelopment analysis based materials balance approach," CEEP-BIT Working Papers 108, Center for Energy and Environmental Policy Research (CEEP), Beijing Institute of Technology.
    19. Kounetas, Kostas & Zervopoulos, Panagiotis, 2017. "Annex I and non-Annex I countries’productive performance revisited using a generalized directional distance function under a metafrontier framework: Is there any convergence-divergence pattern for tec," MPRA Paper 80904, University Library of Munich, Germany.
    20. Mardani, Abbas & Zavadskas, Edmundas Kazimieras & Streimikiene, Dalia & Jusoh, Ahmad & Khoshnoudi, Masoumeh, 2017. "A comprehensive review of data envelopment analysis (DEA) approach in energy efficiency," Renewable and Sustainable Energy Reviews, Elsevier, vol. 70(C), pages 1298-1322.

    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:12:y:2020:i:11:p:4613-:d:367625. 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.