IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v15y2023i15p11833-d1208333.html
   My bibliography  Save this article

Green and Low-Carbon Efficiency Assessment of Urban Agglomeration Logistics Industry: Evidence from China’s Beijing-Tianjin-Hebei Metropolitan Area (2008–2020)

Author

Listed:
  • Bangjun Wang

    (School of Economics and Management, China University of Mining and Technology, Xuzhou 221116, China)

  • Yu Tian

    (School of Economics and Management, China University of Mining and Technology, Xuzhou 221116, China)

Abstract

With the advent of the post-industrial era, the rapid development of e-commerce has propelled the logistics industry to become the lifeline of the national economy, supporting the orderly flow of resource elements between cities. However, the concerning issues of excessive energy consumption and low logistics efficiency in the transportation process have come to the forefront. The introduction of China’s dual-carbon policy goals indicates that enhancing regional logistics’ green and low-carbon efficiency is key to solving the global logistic sustainability problem. Nowadays, the logistics sector’s efficiency in producing green and low-carbon emissions has been quantified using an input-output measurement index. Using data from 2008 to 2020 from the dynamic panel of the logistics sector in the urban agglomerations of Beijing, Tianjin, and Hebei, the three-stage SBM-DEA and Malmquist index quantitative evaluation models are selected to estimate the logistic green and low-carbon development efficiency comprehensively. The analysis discovered that green and low-carbon logistics in the Beijing-Tianjin-Hebei metropolitan agglomeration are relatively efficient overall, and the urban siphon effect of Beijing and Tianjin is noticeable. Once the impact of environmental variables and random errors is eliminated, it becomes evident that these factors tend to inflate the overall technical efficiency. Technical efficiency levels are the primary factor leading to regional logistics inefficiencies. Additionally, it is essential to note that scale efficiency positively affects urban development, leading to a rebound effect, summarizing the existing problems combined with the visualization map, and putting forward corresponding policy suggestions, which is of great practical significance.

Suggested Citation

  • Bangjun Wang & Yu Tian, 2023. "Green and Low-Carbon Efficiency Assessment of Urban Agglomeration Logistics Industry: Evidence from China’s Beijing-Tianjin-Hebei Metropolitan Area (2008–2020)," Sustainability, MDPI, vol. 15(15), pages 1-18, August.
  • Handle: RePEc:gam:jsusta:v:15:y:2023:i:15:p:11833-:d:1208333
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/15/15/11833/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2071-1050/15/15/11833/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Hao Zhang & Jianxin You & Xuekelaiti Haiyirete & Tianyu Zhang, 2020. "Measuring Logistics Efficiency in China Considering Technology Heterogeneity and Carbon Emission through a Meta-Frontier Model," Sustainability, MDPI, vol. 12(19), pages 1-18, October.
    2. Sundarakani, Balan & de Souza, Robert & Goh, Mark & Wagner, Stephan M. & Manikandan, Sushmera, 2010. "Modeling carbon footprints across the supply chain," International Journal of Production Economics, Elsevier, vol. 128(1), pages 43-50, November.
    3. Du, Gang & Li, Wendi, 2022. "Does innovative city building promote green logistics efficiency? Evidence from a quasi-natural experiment with 285 cities," Energy Economics, Elsevier, vol. 114(C).
    4. 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.
    5. Fernández, Xose Luis & Gundelfinger, Javier & Coto-Millán, Pablo, 2022. "The impact of logistics and intermodality on airport efficiency," Transport Policy, Elsevier, vol. 124(C), pages 233-239.
    6. Phi-Hung Nguyen, 2023. "A Fully Completed Spherical Fuzzy Data-Driven Model for Analyzing Employee Satisfaction in Logistics Service Industry," Mathematics, MDPI, vol. 11(10), pages 1-34, May.
    7. 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.
    8. Jian Xu & Yongrong Cao, 2019. "Innovation, the Flying Geese Model, IPR Protection, and Sustainable Economic Development in China," Sustainability, MDPI, vol. 11(20), pages 1-27, October.
    9. WANG, Yang & Liu, Dinghan & Sui, Xiuping & Li, Fengchun, 2022. "Does logistics efficiency matter? Evidence from green economic efficiency side," Research in International Business and Finance, Elsevier, vol. 61(C).
    10. Tian, Yihui & Zhu, Qinghua & Lai, Kee-hung & Venus Lun, Y.H., 2014. "Analysis of greenhouse gas emissions of freight transport sector in China," Journal of Transport Geography, Elsevier, vol. 40(C), pages 43-52.
    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. Ying Gong & Xiao-Qiong Yang & Chun-Yan Ran & Victor Shi & Yu-Feng Zhou, 2021. "Evaluation of the Sustainable Coupling Coordination of the Logistics Industry and the Manufacturing Industry in the Yangtze River Economic Belt," Sustainability, MDPI, vol. 13(9), pages 1-19, May.
    2. Avkiran, Necmi K., 2007. "Stability and integrity tests in data envelopment analysis," Socio-Economic Planning Sciences, Elsevier, vol. 41(3), pages 224-234, September.
    3. Jianqing Zhang & Song Wang & Peilei Yang & Fei Fan & Xueli Wang, 2020. "Analysis of Scale Factors on China’s Sustainable Development Efficiency Based on Three-Stage DEA and a Double Threshold Test," Sustainability, MDPI, vol. 12(6), pages 1-26, March.
    4. Sun, Chuanwang & Xu, Shuai & Xu, Mengjie, 2023. "What causes green efficiency losses in Chinese agriculture? A perspective based on input redundancy," Technological Forecasting and Social Change, Elsevier, vol. 197(C).
    5. 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.
    6. 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.
    7. Liu, Hsiang-Hsi & Huang, Chin-Wei & Chiu, Yung-Ho & Huang, Hsiao-Chin, 2015. "Using A Three Stage Super-Sbm Model To Analyze The Influence Of Bank'S Internationalization And Risk On The Operational Efficiency," Hitotsubashi Journal of Economics, Hitotsubashi University, vol. 56(2), pages 213-229, December.
    8. 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.
    9. Hongjun Guan & Yu Wang & Liye Dong & Aiwu Zhao, 2022. "Efficiency Decomposition Analysis of the Marine Ship Industry Chain Based on Three-Stage Super-Efficiency SBM Model—Evidence from Chinese A-Share-Listed Companies," Sustainability, MDPI, vol. 14(19), pages 1-20, September.
    10. Mai, Nhat Chi, 2015. "Efficiency of the banking system in Vietnam under financial liberalization," OSF Preprints qsf6d, Center for Open Science.
    11. Zuo, Dajie & Liang, Qichen & Zhan, Shuguang & Huang, Wencheng & Yang, Shenglan & Wang, Mengyun, 2023. "Using energy consumption constraints to control the freight transportation structure in China (2021–2030)," Energy, Elsevier, vol. 262(PB).
    12. Teng, Mingming & Shen, Minghao, 2023. "Fintech and energy efficiency: Evidence from OECD countries," Resources Policy, Elsevier, vol. 82(C).
    13. 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.
    14. 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.
    15. 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 1-22, May.
    16. Zhengxiao Yan & Wei Zhou & Yuyi Wang & Xi Chen, 2022. "Comprehensive Analysis of Grain Production Based on Three-Stage Super-SBM DEA and Machine Learning in Hexi Corridor, China," Sustainability, MDPI, vol. 14(14), pages 1-21, July.
    17. Chiu, Yung-Ho & Chen, Yu-Chuan, 2009. "The analysis of Taiwanese bank efficiency: Incorporating both external environment risk and internal risk," Economic Modelling, Elsevier, vol. 26(2), pages 456-463, March.
    18. Junfang Hao & Wanqiang Xu & Zhuo Chen & Baiyun Yuan & Yuping Wu, 2024. "Impact of Heterogeneous Environmental Regulations on Green Innovation Efficiency in China’s Industry," Sustainability, MDPI, vol. 16(1), pages 1-16, January.
    19. Liu, Junming & Tone, Kaoru, 2008. "A multistage method to measure efficiency and its application to Japanese banking industry," Socio-Economic Planning Sciences, Elsevier, vol. 42(2), pages 75-91, June.
    20. 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.

    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:15:y:2023:i:15:p:11833-:d:1208333. 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.