IDEAS home Printed from https://ideas.repec.org/a/eee/trapol/v159y2024icp28-43.html
   My bibliography  Save this article

Changes in low-carbon transportation efficiency of Chinese roads after considering the impact of new energy vehicles

Author

Listed:
  • Cheng, An
  • Jiang, Guogang
  • Teng, Xiangyu
  • Xu, Wenting
  • Li, Yimin
  • Wu, Longhui
  • Chiu, Yung-ho

Abstract

China aims to attain peak carbon emissions by 2030 and achieve carbon neutrality by 2060. As a top-ranked carbon-emitting industry, the transportation industry faces a severe low-carbon transformation situation. The rapid development of new energy vehicles (NEVs) has become an important means to improve the low-carbon transportation efficiency of Chinese roads. Existing studies rarely consider the impact of the development of NEVs, and a regional imbalance exists in the development of low-carbon transportation in China. This study takes the sales of NEVs as an important exogenous variable and uses a modified meta-dynamic non-radial directional distance function (DDF) to analyze the low-carbon transportation efficiency of Chinese roads. After incorporating the sales of NEVs into the analysis system, China's overall road transportation efficiency has significantly improved. The present value of the average annual low-carbon transportation efficiency has increased by 0.06–0.1 compared to the original value, but there are regional differences. The eastern region, with its technological advantages, has achieved the best performance with an average low-carbon transportation efficiency of 0.92. The substitution of NEVs has significantly improved the efficiency of low-carbon transportation on roads in central China. The improvement of low-carbon transportation efficiency on roads in western China is limited due to factors such as the low popularity of NEVs. We delved into the reasons for the development of NEVs to improve the efficiency of low-carbon transportation on roads, discussed the improvement of carbon emissions through the promotion of NEVs, analyzed the regional imbalance of low-carbon transportation efficiency on roads, and provided policy recommendations for the future development of NEVs from the perspective of regional differences.

Suggested Citation

  • Cheng, An & Jiang, Guogang & Teng, Xiangyu & Xu, Wenting & Li, Yimin & Wu, Longhui & Chiu, Yung-ho, 2024. "Changes in low-carbon transportation efficiency of Chinese roads after considering the impact of new energy vehicles," Transport Policy, Elsevier, vol. 159(C), pages 28-43.
    • Handle: RePEc:eee:trapol:v:159:y:2024:i:c:p:28-43
    DOI: 10.1016/j.tranpol.2024.09.020
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0967070X24002713
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.tranpol.2024.09.020?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. Färe, Rolf & Grosskopf, Shawna, 2010. "Directional distance functions and slacks-based measures of efficiency: Some clarifications," European Journal of Operational Research, Elsevier, vol. 206(3), pages 702-702, November.
    2. Zhang, Guanglu & Lin, Boqiang, 2018. "Impact of structure on unified efficiency for Chinese service sector—A two-stage analysis," Applied Energy, Elsevier, vol. 231(C), pages 876-886.
    3. Meng, Conghui & Du, Xiaoyun & Zhu, Mengcheng & Ren, Yitian & Fang, Kai, 2023. "The static and dynamic carbon emission efficiency of transport industry in China," Energy, Elsevier, vol. 274(C).
    4. Song, Yao-yao & Li, Jing-jing & Wang, Jin-li & Yang, Guo-liang & Chen, Zhenling, 2022. "Eco-efficiency of Chinese transportation industry: A DEA approach with non-discretionary input," Socio-Economic Planning Sciences, Elsevier, vol. 84(C).
    5. Xia, Yin-Shuang & Sun, Lu-Xuan & Feng, Chao, 2022. "What causes spatial inequalities of low-carbon development in China's transport sector? A newly proposed meta-frontier DEA-based decomposition approach," Socio-Economic Planning Sciences, Elsevier, vol. 80(C).
    6. 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.
    7. Tsemekidi Tzeiranaki, Sofia & Economidou, Marina & Bertoldi, Paolo & Thiel, Christian & Fontaras, Georgios & Clementi, Enrico Luca & Franco De Los Rios, Camilo, 2023. "“The impact of energy efficiency and decarbonisation policies on the European road transport sector”," Transportation Research Part A: Policy and Practice, Elsevier, vol. 170(C).
    8. Christopher O’Donnell & D. Rao & George Battese, 2008. "Metafrontier frameworks for the study of firm-level efficiencies and technology ratios," Empirical Economics, Springer, vol. 34(2), pages 231-255, March.
    9. Zhang, Tinglong & Li, Sasa & Li, Yifan & Wang, Weizhong, 2023. "Evaluation of technology innovation efficiency for the listed NEV enterprises in China," Economic Analysis and Policy, Elsevier, vol. 80(C), pages 1445-1458.
    10. Caves, Douglas W & Christensen, Laurits R & Diewert, W Erwin, 1982. "The Economic Theory of Index Numbers and the Measurement of Input, Output, and Productivity," Econometrica, Econometric Society, vol. 50(6), pages 1393-1414, November.
    11. Teng, Xiangyu & Zhuang, Weiwei & Liu, Fan-peng & Chang, Tzu-han & Chiu, Yung-ho, 2023. "China's path of carbon neutralization to develop green energy and improve energy efficiency," Renewable Energy, Elsevier, vol. 206(C), pages 397-408.
    12. Zhang, Lei & Tong, Hangyan & Liang, Yuqing & Qin, Quande, 2023. "Consumer purchase intention of new energy vehicles with an extended technology acceptance model: The role of attitudinal ambivalence," Transportation Research Part A: Policy and Practice, Elsevier, vol. 174(C).
    13. Wang, Kunlun & Zheng, Leven J. & Zhang, Justin Zuopeng & Yao, Hongjiang, 2022. "The impact of promoting new energy vehicles on carbon intensity: Causal evidence from China," Energy Economics, Elsevier, vol. 114(C).
    14. Teng, Xiangyu & Liu, Fan-peng & Chiu, Yung-ho, 2021. "The change in energy and carbon emissions efficiency after afforestation in China by applying a modified dynamic SBM model," Energy, Elsevier, vol. 216(C).
    15. 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.
    16. 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.
    17. Xiong, Yongqing & Cheng, Qian, 2023. "Effects of new energy vehicle adoption on provincial energy efficiency in China: From the perspective of regional imbalances," Energy, Elsevier, vol. 281(C).
    18. Bai, Xuejie & Jin, Zeng & Chiu, Yung-Ho, 2021. "Performance evaluation of China's railway passenger transportation sector," Research in Transportation Economics, Elsevier, vol. 90(C).
    19. Yao, Xusheng & Ma, Shoufeng & Bai, Yin & Jia, Ning, 2022. "When are new energy vehicle incentives effective? Empirical evidence from 88 pilot cities in China," Transportation Research Part A: Policy and Practice, Elsevier, vol. 165(C), pages 207-224.
    20. Omrani, Hashem & Yang, Zijiang & Karbasian, Arash & Teplova, Tamara, 2023. "Combination of top-down and bottom-up DEA models using PCA: A two-stage network DEA with shared input and undesirable output for evaluation of the road transport sector," Socio-Economic Planning Sciences, Elsevier, vol. 89(C).
    21. Zhang, Ning & Kong, Fanbin & Choi, Yongrok & Zhou, P., 2014. "The effect of size-control policy on unified energy and carbon efficiency for Chinese fossil fuel power plants," Energy Policy, Elsevier, vol. 70(C), pages 193-200.
    22. Niu, Yanliang & Li, Xin & Zhang, Jiangxue & Deng, Xiaopeng & Chang, Yuan, 2023. "Efficiency of railway transport: A comparative analysis for 16 countries," Transport Policy, Elsevier, vol. 141(C), pages 42-53.
    23. Tone, Kaoru & Tsutsui, Miki, 2010. "Dynamic DEA: A slacks-based measure approach," Omega, Elsevier, vol. 38(3-4), pages 145-156, June.
    24. Feng Li & Shiqi Ye & Julien Chevallier & Jinyu Zhang & Gang Kou, 2023. "Provincial energy and environmental efficiency analysis of Chinese transportation industry with the fixed-sum carbon emission constraint," Post-Print halshs-04250350, HAL.
    25. Keshavarzian, Maryam & Kamali Anaraki, Sara & Zamani, Mehrzad & Erfanifard, Ali, 2012. "Projections of oil demand in road transportation sector on the basis of vehicle ownership projections, worldwide: 1972–2020," Economic Modelling, Elsevier, vol. 29(5), pages 1979-1985.
    26. Zhang, Ning & Zhou, Peng & Kung, Chih-Chun, 2015. "Total-factor carbon emission performance of the Chinese transportation industry: A bootstrapped non-radial Malmquist index analysis," Renewable and Sustainable Energy Reviews, Elsevier, vol. 41(C), pages 584-593.
    27. George Battese & D. Rao & Christopher O'Donnell, 2004. "A Metafrontier Production Function for Estimation of Technical Efficiencies and Technology Gaps for Firms Operating Under Different Technologies," Journal of Productivity Analysis, Springer, vol. 21(1), pages 91-103, January.
    28. R. D. Banker & A. Charnes & W. W. Cooper, 1984. "Some Models for Estimating Technical and Scale Inefficiencies in Data Envelopment Analysis," Management Science, INFORMS, vol. 30(9), pages 1078-1092, September.
    29. 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.
    30. 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.
    31. Diao, Qinghua & Sun, Wei & Yuan, Xinmei & Li, Lili & Zheng, Zhi, 2016. "Life-cycle private-cost-based competitiveness analysis of electric vehicles in China considering the intangible cost of traffic policies," Applied Energy, Elsevier, vol. 178(C), pages 567-578.
    32. 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.
    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. Mao, Yumeng & Li, Xuemei & Jiao, Dehan & Zhao, Xiaolei, 2024. "Characterizing the spatial correlation network structure and impact mechanism of carbon emission efficiency: Evidence from China's transportation sector," Energy, Elsevier, vol. 313(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. Teng, Xiangyu & Liu, Fan-peng & Chang, Tzu-han & Chiu, Yung-ho, 2023. "Measuring China’s energy efficiency by considering forest carbon sequestration and applying a meta dynamic non-radial directional distance function," Energy, Elsevier, vol. 263(PC).
    2. Teng, Xiangyu & Zhuang, Weiwei & Liu, Fan-peng & Chang, Tzu-han & Chiu, Yung-ho, 2023. "China's path of carbon neutralization to develop green energy and improve energy efficiency," Renewable Energy, Elsevier, vol. 206(C), pages 397-408.
    3. 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.
    4. Wang, Qunwei & Chiu, Yung-Ho & Chiu, Ching-Ren, 2017. "Non-radial metafrontier approach to identify carbon emission performance and intensity," Renewable and Sustainable Energy Reviews, Elsevier, vol. 69(C), pages 664-672.
    5. Chen, Jiabin & Wen, Shaobo & Liu, Yuchen, 2022. "Research on the efficiency of the mining industry in China from the perspective of time and space," Resources Policy, Elsevier, vol. 75(C).
    6. Xiao-Ning Li & Ying Feng & Pei-Ying Wu & Yung-Ho Chiu, 2021. "An Analysis of Environmental Efficiency and Environmental Pollution Treatment Efficiency in China’s Industrial Sector," Sustainability, MDPI, vol. 13(5), pages 1-25, February.
    7. Yongqi Feng & Haolin Zhang & Yung-ho Chiu & Tzu-Han Chang, 2021. "Innovation efficiency and the impact of the institutional quality: a cross-country analysis using the two-stage meta-frontier dynamic network DEA model," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(4), pages 3091-3129, April.
    8. Yu-Chuan Chen & Yung-Ho Chiu & Tzu-Han Chang & Tai-Yu Lin, 2023. "Sustainable Development, Government Efficiency, and People’s Happiness," Journal of Happiness Studies, Springer, vol. 24(4), pages 1549-1578, April.
    9. 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).
    10. Jianglong Li & Boqiang Lin, 2016. "Green Economy Performance and Green Productivity Growth in China’s Cities: Measures and Policy Implication," Sustainability, MDPI, vol. 8(9), pages 1-21, September.
    11. Yanni Yu & Yongrok Choi, 2015. "Measuring Environmental Performance Under Regional Heterogeneity in China: A Metafrontier Efficiency Analysis," Computational Economics, Springer;Society for Computational Economics, vol. 46(3), pages 375-388, October.
    12. Xiangyu Teng & Fan‐peng Liu & Yung‐ho Chiu, 2020. "The impact of coal and non‐coal consumption on China's energy performance improvement," Natural Resources Forum, Blackwell Publishing, vol. 44(4), pages 334-352, November.
    13. 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.
    14. 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.
    15. Wang, Qunwei & Su, Bin & Sun, Jiasen & Zhou, Peng & Zhou, Dequn, 2015. "Measurement and decomposition of energy-saving and emissions reduction performance in Chinese cities," Applied Energy, Elsevier, vol. 151(C), pages 85-92.
    16. Liu, Guangtian & Wang, Bing & Zhang, Ning, 2016. "A coin has two sides: Which one is driving China’s green TFP growth?," Economic Systems, Elsevier, vol. 40(3), pages 481-498.
    17. 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.
    18. Na Wang & Yongrok Choi, 2019. "Comparative Analysis of the Energy and CO 2 Emissions Performance and Technology Gaps in the Agglomerated Cities of China and South Korea," Sustainability, MDPI, vol. 11(2), pages 1-25, January.
    19. Wang, Qunwei & Su, Bin & Zhou, Peng & Chiu, Ching-Ren, 2016. "Measuring total-factor CO2 emission performance and technology gaps using a non-radial directional distance function: A modified approach," Energy Economics, Elsevier, vol. 56(C), pages 475-482.
    20. Fang-Rong Ren & Ze Tian & Yu-Ting Shen & Yung-Ho Chiu & Tai-Yu Lin, 2019. "Energy, CO 2 , and AQI Efficiency and Improvement of the Yangtze River Economic Belt," Energies, MDPI, vol. 12(4), pages 1-17, February.

    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:trapol:v:159:y:2024:i:c:p:28-43. 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.elsevier.com/wps/find/journaldescription.cws_home/30473/description#description .

    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.