THERMAL SCIENCE

International Scientific Journal

Leying Xu

,

Hong Cheng

,

Fuhong Luo

,

Xudong Cheng

,

Ruonan Jiang

CARBON EMISSION EFFICIENCY EVALUATION OF BEIJING-TIANJIN-HEBEI LOGISTICS INDUSTRY BASED ON SBM MODEL

ABSTRACT
The establishment of a sound low-carbon logistics system is the basic solution to China’s resource, environmental and ecological problems. From the perspective of resources, environment and ecology, building a low-carbon logistics system is the basic solution to the problems of resources, environment and ecology that China is facing. The project takes the logistics industry as the object to establish an evaluation model of logistics industry carbon emission efficiency and obtain the evaluation results of logistics industry carbon emission in 2014-2019. The carbon utilization efficiency of the system is calculated by slacks-based measurement (SBM) method. On this basis, Arc-Map software is used to conduct spatial modelling of empirical analysis is carried out. Through the research on the Beijing-Tianjin-Hebei region, we will further improve the ambitious strategic plan of “carbon reduction, carbon neutrality” and contribute to the country’s economic and social development.
KEYWORDS
Beijing-Tianjin-Hebei logistics industry in China, Carbon emission efficiency, SBM model
PAPER SUBMITTED: 2022-12-13
PAPER REVISED: 2023-02-18
PAPER ACCEPTED: 2023-05-20
PUBLISHED ONLINE: 2023-06-11
DOI REFERENCE: https://doi.org/10.2298/TSCI221213137X
CITATION EXPORT: view in browser or download as text file
THERMAL SCIENCE YEAR 2023, VOLUME 27, ISSUE Issue 4, PAGES [2987 - 2998]
REFERENCES
  1. Fumin Deng, Lin Xu, Yuan Fang, Qunxi Gong, Zhi Li, PCA-DEA-tobit regression assessment with carbon emission constraints of China's logistics industry. Journal of Cleaner Production, 2020(271)
  2. TongFei. Low carbon pilot policy research on the influence of the logistics industry carbon emissions. Chang ‘a university, 2021.001783.
  3. Zhang Li-Guo, Li Dong, Gong Ai-Qing. Dynamic change and regional variation of total factor energy efficiency in China's logistics industry. Resources Science,2015,37(04):754-763.]
  4. Ma M, Tang L. Evaluation of technical efficiency of logistics industry based on three-stage DEA method. Railway transportation and economy, 2019, 9 (7): 14--21. DOI: 10.16668 / j.carol carroll nki. Issn 1003-1421.2019.07.03.
  5. Li Y, Sun Z Q. Analysis of operational efficiency of Chinese logistics industry and its influencing factors under carbon emission constraints. Business Economics Research,2021, (08):75-78.]
  6. Yao Y K. Study on carbon emission efficiency of Chinese logistics industry based on DEA-BCC model
  7. Lin Xiuqun, Li Yang, Tang Xiangyang. Measurement and dynamic change of total factor carbon emission efficiency in Chinese logistics industry. Journal of Highway and Transportation Science and Technology,202,39(11):182-190.
  8. Fang J. Study on the impact of environmental regulation on the carbon emission efficiency of Chinese logistics Enterprises. Taiyuan: North University of China,2021.
  9. GAO Fengfeng. Research on Coordinated Development of Logistics Industry and low-carbon Economy in China. Tianjin: Tianjin University of Technology, 2016.
  10. Zhang L G. Energy consumption and carbon dioxide emission efficiency measurement and analysis of China's logistics industry. Nanjing: Nanjing University of Aeronautics and Astronautics,2015.
  11. Mariano, EB.; Gobbo, JA.; Camioto, FD.; Rebelatto, DAD. CO2 emissions and logistics performance: A composite index proposal. Clean Prod. 2017(163)
  12. Li H, Li W. Carbon emission efficiency evaluation and dynamic evolution analysis of logistics industry: A case study of provinces along the Silk Road Economic Belt. Environmental Science and Technology, 2019,42 (03)
  13. Zhu Taoxing, Xu Yuqing, Bao Binshuo. Analysis on development characteristics and efficiency of regional logistics: Based on carbon emission and LMDI method. Technology Economics and Management Research, 2021 (06).
  14. Xu W G. Study on carbon emission efficiency evaluation of provincial logistics industry under the background of low carbon. Wuxi: Jiangnan University, 2021.
  15. Junai Yang, Ling Tang, Zhifu Mi,Sen Liu, Ling Li, Jiali Zheng, Carbon emissions performance in logistics at the city level.Journal of Cleaner Production,2019 (231)
  16. Yan Y. Dynamic efficiency measurement of regional logistics along the Belt and Road and its influencing factors: from the perspective of double carbon. Business Economics Research, 2022 (13)
  17. Liang Jing, Sheng Huimin, Lv Jing. An empirical study on the impact of logistics industry agglomeration on logistics carbon emissions in Bohai Rim. Ecological Economy,2020,36(09):38
  18. Bao Yaodong, Li Yanshu, Zhang Shizhong. Study on carbon emission scale and influencing factors of logistics industry in Yangtze River Delta. Ecological Economy,2020,36(11):25-31+53.
  19. K Tone.A Slacks-based measure of efficiency in data envelopment analysis
  20. K Tone.Dealing with undesirable outputs in DEA: a Slacks-Based Measure (SBM) approach
  21. Shang M F. Study on carbon emission efficiency measurement and urbanization impact of logistics industry in urban agglomeration. Qingdao: China University of Petroleum (East China), 2017.
  22. Wu Z J. Research on carbon emission efficiency measurement and control measures of logistics industry along the "Belt and Road" domestic routes. Kunming: Kunming University of Science and Technology, 2021.
  23. Jiang X, Ma J, Zhu H, Guo XHuang Z. 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. International Journal of Environmental Research and Public Health, 2020(17).
  24. Xiang Qifeng, Wang Wenju. China's energy structure adjustment and the energy conservation and emissions reduction potential evaluation. Journal of economics and management research, 2014, No. 260 (7): 13-22.
  25. Ri, jia-guo liu, Li Tianqi. Regional difference of energy eco-efficiency in manufacturing industry considering non-desired output: a two-stage analysis based on SBM and Tobit model
  26. Hu Yanyong, Zhang Rui, Qie Xiaotong, Liu Hong. Evaluation on energy carbon emission efficiency of China's coal resources under full life cycle. China Environmental Science, 2022,42 (06)
  27. Ning N C, Zheng W, Zeng L N. Evaluation and influencing factors of provincial carbon emission efficiency in China from 2007 to 2016: a two-stage analysis based on super-efficiency SBM-Tobit model. Journal of Peking University (Natural Science), 2021,57 (01)
  28. Zhang S W. The impact of household consumption structure change on energy consumption. Zhejiang Gongshang University, 2015.
  29. Qin Y Y, Liao Y. China's industrial carbon emission structure calculation and its implications. Southwest Finance,2023, (02):82-94.
  30. Wu Yiqing, Leng Xuanrong, Tian Jingjing. Promoting deeper expansion of industrial chain cooperation between Beijing, Tianjin and Hebei: Review and Prospect of nine years of coordinated industrial development between Beijing, Tianjin and Hebei. Economics and management: 1-8
  31. Liu Pengzhen, Zhang Liyuan, Dong Huizhong. Spatial and temporal evolution of carbon emission intensity and its influencing factors in Beijing-Tianjin-Hebei and neighboring "2+26" cities. The environmental pollution and control, 2022, 44 (6): 772-776
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Carbon emission efficiency evaluation of Beijing-Tianjin-Hebei logistics industry based on SBM model

© 2024 Society of Thermal Engineers of Serbia. Published by the Vinča Institute of Nuclear Sciences, National Institute of the Republic of Serbia, Belgrade, Serbia. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International licence