IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v17y2025i16p7440-d1726389.html
   My bibliography  Save this article

Carbon Dioxide Emission-Reduction Efficiency in China’s New Energy Vehicle Sector Toward Sustainable Development: Evidence from a Three-Stage Super-Slacks Based-Measure Data Envelopment Analysis Model

Author

Listed:
  • Liying Zheng

    (Business School, Hohai University, Nanjing 211100, China)

  • Fangjuan Zhan

    (Business School, Hohai University, Nanjing 211100, China)

  • Fangrong Ren

    (College of Economics and Management, Nanjing Forestry University, Nanjing 210037, China)

Abstract

This research evaluates the carbon dioxide emission-reduction efficiency of new energy vehicles (NEVs) in China from 2018 to 2023 by applying a three-stage super-SBM data envelopment analysis (DEA) model that incorporates undesirable outputs. This model offers significant advantages over traditional DEA models, as it effectively disentangles the influences of external environmental factors and stochastic noise, thereby providing a more accurate and robust assessment of true efficiency. Its super-efficiency characteristic also allows for effective ranking of all decision-making units (DMUs) on the efficiency frontier. The empirical findings reveal several key insights. (1) The NEV industry’s carbon-reduction efficiency in China between 2018 and 2023 displayed an upward trend accompanied by pronounced fluctuations. Its mean super-efficiency score was 0.353, indicating substantial scope for improvements in scale efficiency. (2) Significant interprovincial disparities in efficiency appear. Unbalanced coordination between production and consumption in provinces such as Shaanxi, Beijing, and Liaoning has produced correspondingly high or low efficiency values. (3) Although accelerated urbanization has reduced the capital and labor inputs required by the NEV industry and has raised energy consumption, the net effect enhances carbon-reduction efficiency. Household consumption levels and technological advancement exerts divergent effects on efficiency. The former negatively relates to efficiency, whereas the latter is positively associated.

Suggested Citation

  • Liying Zheng & Fangjuan Zhan & Fangrong Ren, 2025. "Carbon Dioxide Emission-Reduction Efficiency in China’s New Energy Vehicle Sector Toward Sustainable Development: Evidence from a Three-Stage Super-Slacks Based-Measure Data Envelopment Analysis Model," Sustainability, MDPI, vol. 17(16), pages 1-26, August.
    • Handle: RePEc:gam:jsusta:v:17:y:2025:i:16:p:7440-:d:1726389
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/17/16/7440/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/17/16/7440/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Apostolaki-Iosifidou, Elpiniki & Codani, Paul & Kempton, Willett, 2017. "Measurement of power loss during electric vehicle charging and discharging," Energy, Elsevier, vol. 127(C), pages 730-742.
    2. Wu, Peng & Wang, Yiqing & Chiu, Yung-ho & Li, Ying & Lin, Tai-Yu, 2019. "Production efficiency and geographical location of Chinese coal enterprises - undesirable EBM DEA," Resources Policy, Elsevier, vol. 64(C).
    3. Hongchen Li & Huijun Qi & Hongjian Cao & Li Yuan, 2022. "Industrial Policy and Technological Innovation of New Energy Vehicle Industry in China," Energies, MDPI, vol. 15(24), pages 1-17, December.
    4. Shiqi Ou & Rujie Yu & Zhenhong Lin & Huanhuan Ren & Xin He & Steven Przesmitzki & Jessey Bouchard, 2020. "Intensity and daily pattern of passenger vehicle use by region and class in China: estimation and implications for energy use and electrification," Mitigation and Adaptation Strategies for Global Change, Springer, vol. 25(3), pages 307-327, March.
    5. 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.
    6. Meeusen, Wim & van den Broeck, Julien, 1977. "Efficiency Estimation from Cobb-Douglas Production Functions with Composed Error," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 18(2), pages 435-444, June.
    7. Fare, Rolf & Shawna Grosskopf & Mary Norris & Zhongyang Zhang, 1994. "Productivity Growth, Technical Progress, and Efficiency Change in Industrialized Countries," American Economic Review, American Economic Association, vol. 84(1), pages 66-83, March.
    8. Liu, Xiaoxiao & Niu, Qian & Dong, Shuli & Zhong, Shuiying, 2023. "How does renewable energy consumption affect carbon emission intensity? Temporal-spatial impact analysis in China," Energy, Elsevier, vol. 284(C).
    9. Qiao, Qinyu & Zhao, Fuquan & Liu, Zongwei & He, Xin & Hao, Han, 2019. "Life cycle greenhouse gas emissions of Electric Vehicles in China: Combining the vehicle cycle and fuel cycle," Energy, Elsevier, vol. 177(C), pages 222-233.
    10. Zhibo Zhao & Jiamin Ren & Zheng Liu, 2023. "How Does Urbanization Affect Carbon Emission Performance? Evidence from 282 Cities in China," Sustainability, MDPI, vol. 15(21), pages 1-20, October.
    11. Yahong Jiang & Qunqi Wu & Min Li & Yulei Gu & Jun Yang, 2023. "What Is Affecting the Popularity of New Energy Vehicles? A Systematic Review Based on the Public Perspective," Sustainability, MDPI, vol. 15(18), pages 1-29, September.
    12. H. Fried & C. Lovell & S. Schmidt & S. Yaisawarng, 2002. "Accounting for Environmental Effects and Statistical Noise in Data Envelopment Analysis," Journal of Productivity Analysis, Springer, vol. 17(1), pages 157-174, January.
    13. Zhang, Ming & Song, Yan & Li, Peng & Li, Huanan, 2016. "Study on affecting factors of residential energy consumption in urban and rural Jiangsu," Renewable and Sustainable Energy Reviews, Elsevier, vol. 53(C), pages 330-337.
    14. Li, Rongrong & Wang, Qiang & Li, Lejia & Hu, Sailan, 2023. "Do natural resource rent and corruption governance reshape the environmental Kuznets curve for ecological footprint? Evidence from 158 countries," Resources Policy, Elsevier, vol. 85(PB).
    15. Chen, Huanyu & Yi, Jizheng & Chen, Aibin & Peng, Duanxiang & Yang, Jieqiong, 2023. "Green technology innovation and CO2 emission in China: Evidence from a spatial-temporal analysis and a nonlinear spatial durbin model," Energy Policy, Elsevier, vol. 172(C).
    16. Tone, Kaoru, 2002. "A slacks-based measure of super-efficiency in data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 143(1), pages 32-41, November.
    17. Gaopeng Jiang & Rui Jin & Cuijie Lu & Menglong Gao & Jie Li, 2024. "Provincial Coal Flow Efficiency of China Quantified by Three-Stage Data-Envelopment Analysis," Sustainability, MDPI, vol. 16(11), pages 1-21, May.
    18. 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.
    19. Wang, Qiang & Hu, Sailan & Li, Rongrong, 2024. "Could information and communication technology (ICT) reduce carbon emissions? The role of trade openness and financial development," Telecommunications Policy, Elsevier, vol. 48(3).
    20. 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)

    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. Carla Henriques & Clara Viseu, 2022. "Are ERDFs Devoted to Boosting ICTs in SMEs Inefficient? A Three-Stage SBM Approach," Sustainability, MDPI, vol. 14(17), pages 1-20, August.
    2. Geng Peng & Xiaodan Zhang & Fang Liu & Lijuan Ruan & Kaiyou Tian, 2021. "Spatial–temporal evolution and regional difference decomposition of urban environmental governance efficiency in China," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 23(6), pages 8974-8990, June.
    3. Liu, John S. & Lu, Louis Y.Y. & Lu, Wen-Min, 2016. "Research fronts in data envelopment analysis," Omega, Elsevier, vol. 58(C), pages 33-45.
    4. Wang, Ruixue & Deng, Xiangzheng & Gao, Yunxiao & Chen, Jiancheng, 2025. "Does regional economic development drive sustainable grain production growth in China? Evidence from spatiotemporal perspective on low-carbon total factor productivity," Socio-Economic Planning Sciences, Elsevier, vol. 98(C).
    5. Shixiong Cheng & Jiahui Xie & De Xiao & Yun Zhang, 2019. "Measuring the Environmental Efficiency and Technology Gap of PM 2.5 in China’s Ten City Groups: An Empirical Analysis Using the EBM Meta-Frontier Model," IJERPH, MDPI, vol. 16(4), pages 1-22, February.
    6. Lampe, Hannes W. & Hilgers, Dennis, 2015. "Trajectories of efficiency measurement: A bibliometric analysis of DEA and SFA," European Journal of Operational Research, Elsevier, vol. 240(1), pages 1-21.
    7. Hongli Liu & Xiaoyu Yan & Jinhua Cheng & Jun Zhang & Yan Bu, 2021. "Driving Factors for the Spatiotemporal Heterogeneity in Technical Efficiency of China’s New Energy Industry," Energies, MDPI, vol. 14(14), pages 1-21, July.
    8. Sun, Yu & Yang, Feng & Wang, Dawei & Ang, Sheng, 2023. "Efficiency evaluation for higher education institutions in China considering unbalanced regional development: A meta-frontier Super-SBM model," Socio-Economic Planning Sciences, Elsevier, vol. 88(C).
    9. Xiang Liu & Jia Liu, 2016. "Measurement of Low Carbon Economy Efficiency with a Three-Stage Data Envelopment Analysis: A Comparison of the Largest Twenty CO 2 Emitting Countries," IJERPH, MDPI, vol. 13(11), pages 1-14, November.
    10. Mai, Nhat Chi, 2015. "Efficiency of the banking system in Vietnam under financial liberalization," OSF Preprints qsf6d, Center for Open Science.
    11. Adel Hatami-Marbini & Aliasghar Arabmaldar & John Otu Asu, 2022. "Robust productivity growth and efficiency measurement with undesirable outputs: evidence from the oil industry," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 44(4), pages 1213-1254, December.
    12. Feng Dong & Chang Qin & Xiaoyun Zhang & Xu Zhao & Yuling Pan & Yujin Gao & Jiao Zhu & Yangfan Li, 2021. "Towards Carbon Neutrality: The Impact of Renewable Energy Development on Carbon Emission Efficiency," IJERPH, MDPI, vol. 18(24), pages 1-23, December.
    13. Chen, Yufeng & Ni, Liangfu & Liu, Kelong, 2021. "Does China's new energy vehicle industry innovate efficiently? A three-stage dynamic network slacks-based measure approach," Technological Forecasting and Social Change, Elsevier, vol. 173(C).
    14. 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.
    15. Zhou, Lin & Fan, Jianshuang & Hu, Mingzhi & Yu, Xiaofen, 2024. "Clean air policy and green total factor productivity: Evidence from Chinese prefecture-level cities," Energy Economics, Elsevier, vol. 133(C).
    16. Jindal, Abhinav & Nilakantan, Rahul, 2021. "Falling efficiency levels of Indian coal-fired power plants: A slacks-based analysis," Energy Economics, Elsevier, vol. 93(C).
    17. Avkiran, Necmi K., 2007. "Stability and integrity tests in data envelopment analysis," Socio-Economic Planning Sciences, Elsevier, vol. 41(3), pages 224-234, September.
    18. Mengchao Yao & Yihua Zhang, 2021. "Evaluation and Optimization of Urban Land-Use Efficiency: A Case Study in Sichuan Province of China," Sustainability, MDPI, vol. 13(4), pages 1-22, February.
    19. Rongrong Liu & Dong Chen & Suchang Yang & Yang Chen, 2021. "Evaluation of Green Development Efficiency of the Major Cities in Gansu Province, China," Sustainability, MDPI, vol. 13(6), pages 1-18, March.
    20. Junqi Wen & Yong Lan & Guoqin Bu, 2024. "Do Innovation and Entrepreneurship Support Policies Promote Urban Green Transformation?—The Mediating Role of Fiscal Technology Expenditure," Sustainability, MDPI, vol. 16(7), pages 1-24, March.

    More about this item

    Keywords

    ;
    ;
    ;
    ;

    Statistics

    Access and download statistics

    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:17:y:2025:i:16:p:7440-:d:1726389. 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.