IDEAS home Printed from https://ideas.repec.org/a/eee/renene/v224y2024ics0960148124002933.html
   My bibliography  Save this article

The Spatiotemporal exploration of intercity transport energy efficiency in the mainland of China on the basis of improved stochastic frontier modelling

Author

Listed:
  • Feng, Xuesong
  • Tao, Zhibin
  • Shi, Ruolin

Abstract

In order to determine the upper bound of Transport Energy Efficiency (TEE) and investigate the temporal and regional heterogeneities of TEE, an improved stochastic frontier analysis model taking into account the meta-frontier is established in this work. Focusing on thirty provinces in the mainland of China from 2000 to 2018, this research employs the transport energy efficiency index, technical efficiency variation, frontier transport technical index, and total factor energy efficiency to assess the energy technical disparities among the studied provinces. The results indicate that TEE remains relatively low from 2000 to 2010 due to regional energy technical disparities. However, a noteworthy increase in TEE is observed from 2011 to 2018 owing to technological advancements. Furthermore, among four main intercity transport modes including highway, railway, aviation and water transports, the TEE of railway is the highest, followed by aviation and water transports. In view of the present situation and in order to develop the transport system in a sustainable way, narrowing the energy technical disparities among provinces and constructing a sustainable transport network are vital for policymakers to adopt a more rational transport development plan.

Suggested Citation

  • Feng, Xuesong & Tao, Zhibin & Shi, Ruolin, 2024. "The Spatiotemporal exploration of intercity transport energy efficiency in the mainland of China on the basis of improved stochastic frontier modelling," Renewable Energy, Elsevier, vol. 224(C).
    • Handle: RePEc:eee:renene:v:224:y:2024:i:c:s0960148124002933
    DOI: 10.1016/j.renene.2024.120228
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0960148124002933
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.renene.2024.120228?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Huaping Sun & Lingxiang Hu & Yong Geng & Guangchuan Yang, 2020. "Uncovering impact factors of carbon emissions from transportation sector: evidence from China’s Yangtze River Delta Area," Mitigation and Adaptation Strategies for Global Change, Springer, vol. 25(7), pages 1423-1437, October.
    2. Gerboni, Raffaella & Grosso, Daniele & Carpignano, Andrea & Dalla Chiara, Bruno, 2017. "Linking energy and transport models to support policy making," Energy Policy, Elsevier, vol. 111(C), pages 336-345.
    3. Ali Enes Dingil & Joerg Schweizer & Federico Rupi & Zaneta Stasiskiene, 2019. "Updated Models of Passenger Transport Related Energy Consumption of Urban Areas," Sustainability, MDPI, vol. 11(15), pages 1-16, July.
    4. Achour, Houda & Belloumi, Mounir, 2016. "Decomposing the influencing factors of energy consumption in Tunisian transportation sector using the LMDI method," Transport Policy, Elsevier, vol. 52(C), pages 64-71.
    5. Du, Kerui & Lu, Huang & Yu, Kun, 2014. "Sources of the potential CO2 emission reduction in China: A nonparametric metafrontier approach," Applied Energy, Elsevier, vol. 115(C), pages 491-501.
    6. Weibin Lin & Bin Chen & Lina Xie & Haoran Pan, 2015. "Estimating Energy Consumption of Transport Modes in China Using DEA," Sustainability, MDPI, vol. 7(4), pages 1-15, April.
    7. Bosseboeuf, Didier & Chateau, Bertrand & Lapillonne, Bruno, 1997. "Cross-country comparison on energy efficiency indicators: the on-going European effort towards a common methodology," Energy Policy, Elsevier, vol. 25(7-9), pages 673-682.
    8. Zhou, Guanghui & Chung, William & Zhang, Xiliang, 2013. "A study of carbon dioxide emissions performance of China's transport sector," Energy, Elsevier, vol. 50(C), pages 302-314.
    9. Hu, Jin-Li & Wang, Shih-Chuan, 2006. "Total-factor energy efficiency of regions in China," Energy Policy, Elsevier, vol. 34(17), pages 3206-3217, November.
    10. He, Pinglin & Sun, Yulong & Niu, Hanlu & Long, Chengfeng & Li, Shufeng, 2021. "The long and short-term effects of environmental tax on energy efficiency: Perspective of OECD energy tax and vehicle traffic tax," Economic Modelling, Elsevier, vol. 97(C), pages 307-325.
    11. Wang, Qunwei & Zhao, Zengyao & Zhou, Peng & Zhou, Dequn, 2013. "Energy efficiency and production technology heterogeneity in China: A meta-frontier DEA approach," Economic Modelling, Elsevier, vol. 35(C), pages 283-289.
    12. Ouyang, Xiaoling & Wei, Xiaoyun & Sun, Chuanwang & Du, Gang, 2018. "Impact of factor price distortions on energy efficiency: Evidence from provincial-level panel data in China," Energy Policy, Elsevier, vol. 118(C), pages 573-583.
    13. 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.
    14. 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.
    15. Han Hao & Feiqi Liu & Zongwei Liu & Fuquan Zhao, 2017. "Measuring Energy Efficiency in China’s Transport Sector," Energies, MDPI, vol. 10(5), pages 1-18, May.
    16. Wang, Huiping & Liu, Peiling, 2023. "Spatial correlation network of renewable energy consumption and its influencing factors: Evidence from 31 Chinese provinces," Renewable Energy, Elsevier, vol. 217(C).
    17. Esposito, Luca, 2023. "Renewable energy consumption and per capita income: An empirical analysis in Finland," Renewable Energy, Elsevier, vol. 209(C), pages 558-568.
    18. Tang, Bao-Jun & Li, Xiao-Yi & Yu, Biying & Wei, Yi-Ming, 2019. "Sustainable development pathway for intercity passenger transport: A case study of China," Applied Energy, Elsevier, vol. 254(C).
    Full references (including those not matched with items on IDEAS)

    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. Feng, Chao & Wang, Miao, 2018. "Analysis of energy efficiency in China's transportation sector," Renewable and Sustainable Energy Reviews, Elsevier, vol. 94(C), pages 565-575.
    2. Yu, Dejian & He, Xiaorong, 2020. "A bibliometric study for DEA applied to energy efficiency: Trends and future challenges," Applied Energy, Elsevier, vol. 268(C).
    3. 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.
    4. Feng, Chao & Wang, Miao, 2017. "The economy-wide energy efficiency in China’s regional building industry," Energy, Elsevier, vol. 141(C), pages 1869-1879.
    5. Feng, Chao & Huang, Jian-Bai & Wang, Miao, 2018. "Analysis of green total-factor productivity in China's regional metal industry: A meta-frontier approach," Resources Policy, Elsevier, vol. 58(C), pages 219-229.
    6. Ding, Li-Li & Lei, Liang & Zhao, Xin & Calin, Adrian Cantemir, 2020. "Modelling energy and carbon emission performance: A constrained performance index measure," Energy, Elsevier, vol. 197(C).
    7. Ouyang, Xiaoling & Chen, Jiaqi & Du, Kerui, 2021. "Energy efficiency performance of the industrial sector: From the perspective of technological gap in different regions in China," Energy, Elsevier, vol. 214(C).
    8. Haider, Salman & Danish, Mohd Shadab & Sharma, Ruchi, 2019. "Assessing energy efficiency of Indian paper industry and influencing factors: A slack-based firm-level analysis," Energy Economics, Elsevier, vol. 81(C), pages 454-464.
    9. Lin, Boqiang & Du, Kerui, 2015. "Modeling the dynamics of carbon emission performance in China: A parametric Malmquist index approach," Energy Economics, Elsevier, vol. 49(C), pages 550-557.
    10. Lin, Boqiang & Du, Kerui, 2015. "Energy and CO2 emissions performance in China's regional economies: Do market-oriented reforms matter?," Energy Policy, Elsevier, vol. 78(C), pages 113-124.
    11. Kai Xu & Bart Bossink & Qiang Chen, 2019. "Efficiency Evaluation of Regional Sustainable Innovation in China: A Slack-Based Measure (SBM) Model with Undesirable Outputs," Sustainability, MDPI, vol. 12(1), pages 1-21, December.
    12. Wei, Zixiang & Han, Botang & Pan, Xiuzhen & Shahbaz, Muhammad & Zafar, Muhammad Wasif, 2020. "Effects of diversified openness channels on the total-factor energy efficiency in China's manufacturing sub-sectors: Evidence from trade and FDI spillovers," Energy Economics, Elsevier, vol. 90(C).
    13. Fei, Rilong & Lin, Boqiang, 2016. "Energy efficiency and production technology heterogeneity in China's agricultural sector: A meta-frontier approach," Technological Forecasting and Social Change, Elsevier, vol. 109(C), pages 25-34.
    14. Feng, Chao & Zhang, Hua & Huang, Jian-Bai, 2017. "The approach to realizing the potential of emissions reduction in China: An implication from data envelopment analysis," Renewable and Sustainable Energy Reviews, Elsevier, vol. 71(C), pages 859-872.
    15. Xiangyu Teng & Danting Lu & Yung-ho Chiu, 2019. "Emission Reduction and Energy Performance Improvement with Different Regional Treatment Intensity in China," Energies, MDPI, vol. 12(2), pages 1-18, January.
    16. Eguchi, Shogo & Takayabu, Hirotaka & Lin, Chen, 2021. "Sources of inefficient power generation by coal-fired thermal power plants in China: A metafrontier DEA decomposition approach," Renewable and Sustainable Energy Reviews, Elsevier, vol. 138(C).
    17. Zhencheng Xing & Jigan Wang & Jie Zhang, 2017. "CO 2 Emission Performance, Mitigation Potential, and Marginal Abatement Cost of Industries Covered in China’s Nationwide Emission Trading Scheme: A Meta-Frontier Analysis," Sustainability, MDPI, vol. 9(6), pages 1-17, June.
    18. Lin, Boqiang & Sai, Rockson, 2022. "Towards low carbon economy: Performance of electricity generation and emission reduction potential in Africa," Energy, Elsevier, vol. 251(C).
    19. Lin, Boqiang & Sai, Rockson, 2022. "Sustainable transitioning in Africa: A historical evaluation of energy productivity changes and determinants," Energy, Elsevier, vol. 250(C).
    20. 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.

    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:eee:renene:v:224:y:2024:i:c:s0960148124002933. 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: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/renewable-energy .

    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.