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Carbon emission efficiency of China's logistics industry: Measurement, evolution mechanism, and promotion countermeasures

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  • Ding, Heping
  • Liu, Conghu

Abstract

Improving carbon emission efficiency of the logistics industry (LCEE) is important in achieving carbon neutrality. We examine the carbon emissions of 31 provinces and cities in China that aim to reduce emissions and increase efficiency in the logistics industry. We construct the evaluation index system of LCEE, using the Super-EBM-unexpected model to measure it. Moreover, the global Malmquist–Luenberger index and the spatial autocorrelation model are used to analyze its temporal and spatial evolution mechanisms and identify its influencing factors via the spatial Durbin model. The results show a very low average LCEE value and a decreasing gradient distribution in space for China. The average pure technical efficiency is the main driving force for improving LCEE. Environmental regulation and the residents' consumption level positively affect LCEE. However, economic level, industrial structure, government input, and energy intensity have a negative impact. Countermeasures and recommendations are proposed to improve LCEE and provide theoretical and methodological support for its research and management. The study provides implications for policymaking related to ecosystem protection and sustainable development in the logistics industry.

Suggested Citation

  • Ding, Heping & Liu, Conghu, 2024. "Carbon emission efficiency of China's logistics industry: Measurement, evolution mechanism, and promotion countermeasures," Energy Economics, Elsevier, vol. 129(C).
    • Handle: RePEc:eee:eneeco:v:129:y:2024:i:c:s0140988323007193
    DOI: 10.1016/j.eneco.2023.107221
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    1. Liangen Zeng & Haiyan Lu & Yenping Liu & Yang Zhou & Haoyu Hu, 2019. "Analysis of Regional Differences and Influencing Factors on China’s Carbon Emission Efficiency in 2005–2015," Energies, MDPI, vol. 12(16), pages 1-21, August.
    2. Ray, Subhash C & Desli, Evangelia, 1997. "Productivity Growth, Technical Progress, and Efficiency Change in Industrialized Countries: Comment," American Economic Review, American Economic Association, vol. 87(5), pages 1033-1039, December.
    3. 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).
    4. Tone, Kaoru & Tsutsui, Miki, 2010. "An epsilon-based measure of efficiency in DEA - A third pole of technical efficiency," European Journal of Operational Research, Elsevier, vol. 207(3), pages 1554-1563, December.
    5. Zhou, P. & Ang, B.W. & Han, J.Y., 2010. "Total factor carbon emission performance: A Malmquist index analysis," Energy Economics, Elsevier, vol. 32(1), pages 194-201, January.
    6. Wang, Guofeng & Deng, Xiangzheng & Wang, Jingyu & Zhang, Fan & Liang, Shiqi, 2019. "Carbon emission efficiency in China: A spatial panel data analysis," China Economic Review, Elsevier, vol. 56(C), pages 1-1.
    7. Zhang, Ren-Long & Liu, Xiao-Hong, 2021. "Evaluating ecological efficiency of Chinese industrial enterprise," Renewable Energy, Elsevier, vol. 178(C), pages 679-691.
    8. Luc Anselin & Rodolfo Bongiovanni & Jess Lowenberg-DeBoer, 2004. "A Spatial Econometric Approach to the Economics of Site-Specific Nitrogen Management in Corn Production," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 86(3), pages 675-687.
    9. R. Ramanathan, 2002. "Combining indicators of energy consumption and CO 2 emissions: a cross-country comparison," International Journal of Global Energy Issues, Inderscience Enterprises Ltd, vol. 17(3), pages 214-227.
    10. Kaoru Tone, 2011. "Slacks-Based Measure of Efficiency," International Series in Operations Research & Management Science, in: William W. Cooper & Lawrence M. Seiford & Joe Zhu (ed.), Handbook on Data Envelopment Analysis, chapter 0, pages 195-209, Springer.
    11. J. Elhorst, 2010. "Applied Spatial Econometrics: Raising the Bar," Spatial Economic Analysis, Taylor & Francis Journals, vol. 5(1), pages 9-28.
    12. Aigner, Dennis & Lovell, C. A. Knox & Schmidt, Peter, 1977. "Formulation and estimation of stochastic frontier production function models," Journal of Econometrics, Elsevier, vol. 6(1), pages 21-37, July.
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