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Evaluating the Carbon Emissions Efficiency of the Logistics Industry Based on a Super-SBM Model and the Malmquist Index from a Strong Transportation Strategy Perspective in China

Author

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  • Xiaohong Jiang

    (College of Automobile and Traffic Engineering, Nanjing Forestry University, Longpan Road 159#, Nanjing 210037, China)

  • Jianxiao Ma

    (College of Automobile and Traffic Engineering, Nanjing Forestry University, Longpan Road 159#, Nanjing 210037, China)

  • Huizhe Zhu

    (College of Automobile and Traffic Engineering, Nanjing Forestry University, Longpan Road 159#, Nanjing 210037, China)

  • Xiucheng Guo

    (School of Transportation, Southeast University, Si Pai Lou 2#, Nanjing 210096, China)

  • Zhaoguo Huang

    (School of Civil Engineering, Lanzhou University of Technology, Lanzhou 730050, China)

Abstract

Carbon emissions from the logistics industry have been rising year after year. Correct handling of the relationship between economic development and environmental protection is of great significance to the implementation of green logistics, which is an important component of China’s strategy for strong transportation. This paper focuses on the evaluation of the carbon emissions efficiency of logistics industry from a new strong transportation strategy perspective. A super-efficiency slack-based measurement (Super-SBM) model and Malmquist index are combined to evaluate the static and dynamic carbon emissions efficiency of the logistics industry. The results indicate that compared with the SBM model, the Super-SBM model can more effectively measure the carbon emissions efficiency of the logistics industry. Pilot regions for the strong transportation strategy were divided into two categories, namely regions with slow carbon emission growth rates but high efficiency, and regions with high carbon emission growth rates but low efficiency. Some policy recommendations from the strong transportation strategy perspective were proposed to improve the carbon emissions efficiency of the logistics industry, especially for the second category of pilot regions. This study is expected to provide a basis for decision-making for efficient emissions reduction measures and policies, and to encourage the pilot regions to take the lead in achieving the goal of China’s strategy for transportation.

Suggested Citation

  • Xiaohong Jiang & Jianxiao Ma & Huizhe Zhu & Xiucheng Guo & Zhaoguo Huang, 2020. "Evaluating the Carbon Emissions Efficiency of the Logistics Industry Based on a Super-SBM Model and the Malmquist Index from a Strong Transportation Strategy Perspective in China," IJERPH, MDPI, vol. 17(22), pages 1-19, November.
    • Handle: RePEc:gam:jijerp:v:17:y:2020:i:22:p:8459-:d:445394
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    Cited by:

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    2. Hanxin Wang & Weiqian Liu & Yi Liang, 2023. "Measurement of CO 2 Emissions Efficiency and Analysis of Influencing Factors of the Logistics Industry in Nine Coastal Provinces of China," Sustainability, MDPI, vol. 15(19), pages 1-21, October.
    3. Maren Schnieder & Chris Hinde & Andrew West, 2022. "Emission Estimation of On-Demand Meal Delivery Services Using a Macroscopic Simulation," IJERPH, MDPI, vol. 19(18), pages 1-17, September.
    4. Chong Wu & Jiahua Gan & Zhuo Jiang & Anding Jiang & Wenlong Zheng, 2022. "Ecological Efficiency Evaluation, Spatial Difference, and Trend Analysis of Logistics Industry and Manufacturing Industry Linkage in the Northeast Old Industrial Base," Sustainability, MDPI, vol. 14(19), pages 1-20, October.
    5. Maren Schnieder & Chris Hinde & Andrew West, 2021. "Sensitivity Analysis of Emission Models of Parcel Lockers vs. Home Delivery Based on HBEFA," IJERPH, MDPI, vol. 18(12), pages 1-21, June.
    6. Shihong Zeng & Gen Li & Shaomin Wu & Zhanfeng Dong, 2022. "The Impact of Green Technology Innovation on Carbon Emissions in the Context of Carbon Neutrality in China: Evidence from Spatial Spillover and Nonlinear Effect Analysis," IJERPH, MDPI, vol. 19(2), pages 1-25, January.
    7. Heping Ding & Yuxia Guo & Xue Wu & Cui Wang & Yu Zhang & Hongjun Liu & Yujia Liu & Aiyong Lin & Fagang Hu, 2022. "Data-Driven Resource Efficiency Evaluation and Improvement of the Logistics Industry in 30 Chinese Provinces and Cities," Sustainability, MDPI, vol. 14(15), pages 1-23, August.
    8. Meiling He & Mei Yang & Xiaohui Wu & Jun Pu & Kazuhiro Izui, 2024. "Evaluating and Analyzing the Efficiency and Influencing Factors of Cold Chain Logistics in China’s Major Urban Agglomerations under Carbon Constraints," Sustainability, MDPI, vol. 16(5), pages 1-19, February.

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