IDEAS home Printed from https://ideas.repec.org/a/spr/endesu/v26y2024i2d10.1007_s10668-022-02833-2.html
   My bibliography  Save this article

Spatial and temporal evolution of green logistics efficiency in China and analysis of its motivation

Author

Listed:
  • Bin Chen

    (Fujian Jiangxia University)

  • Fang Liu

    (Fuzhou University)

  • Yina Gao

    (Fujian Jiangxia University)

  • Chong Ye

    (Fuzhou University)

Abstract

The serious consequences of climate warming have increasingly become a globe agenda in recent decades. China has been actively participating in various initiatives to address global climate change and has made commitments to reduce carbon emissions. Although the logistics industry is regarded as the "new driving force of national economic development", its carbon intensity is relatively high. Therefore, whether the logistics industry can develop in a green and low-carbon way is very crucial. This paper takes the green logistics efficiency of China's provincial logistics industry as the research object. The Super-SBM model is used to measure the China's green logistics efficiency, then the general dynamic characteristics is depicted by kernel density analysis. With the GML (Global Malmquist-Luenberger) index model, the reasons for the changes in green logistics efficiency are explained. Finally, Moran's I index is used to analyze the spatial correlation of green logistics efficiency in each province. The results show that the green logistics efficiency in China is at a low level, but with an upward trend. China's green logistics efficiency has a significant positive spatial correlation, showing a zonal pattern of high in the east and low in the west, and a polarization phenomenon. In addition, the bottleneck of the overall development of green logistics efficiency in China depends on the level of green technology. Furthermore, the results also imply that green technology advancement is an inherent key factor for green logistics efficiency to achieve growth.

Suggested Citation

  • Bin Chen & Fang Liu & Yina Gao & Chong Ye, 2024. "Spatial and temporal evolution of green logistics efficiency in China and analysis of its motivation," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 26(2), pages 2743-2774, February.
  • Handle: RePEc:spr:endesu:v:26:y:2024:i:2:d:10.1007_s10668-022-02833-2
    DOI: 10.1007/s10668-022-02833-2
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s10668-022-02833-2
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.

    File URL: https://libkey.io/10.1007/s10668-022-02833-2?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Ubeda, S. & Arcelus, F.J. & Faulin, J., 2011. "Green logistics at Eroski: A case study," International Journal of Production Economics, Elsevier, vol. 131(1), pages 44-51, May.
    2. Yudi Fernando & Mei-Mei Tew, 2016. "Reverse logistics in manufacturing waste management: the missing link between environmental commitment and operational performance," International Journal of Integrated Supply Management, Inderscience Enterprises Ltd, vol. 10(3/4), pages 264-282.
    3. Weihua Gan & Wenpei Yao & Shuying Huang, 2022. "Evaluation of Green Logistics Efficiency in Jiangxi Province Based on Three-Stage DEA from the Perspective of High-Quality Development," Sustainability, MDPI, vol. 14(2), pages 1-19, January.
    4. Emel Aktas & J. M. Bloemhof & Jan C. Fransoo & Hans-Otto Günther & Werner Jammernegg, 2018. "Green logistics solutions," Flexible Services and Manufacturing Journal, Springer, vol. 30(3), pages 363-365, September.
    5. Wen Qin & Xiaolie Qi, 2022. "Evaluation of Green Logistics Efficiency in Northwest China," Sustainability, MDPI, vol. 14(11), pages 1-14, June.
    6. 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.
    7. Yongrong Xin & Kengcheng Zheng & Yujiao Zhou & Yangyang Han & P. R. Tadikamalla & Qin Fan, 2022. "Logistics Efficiency under Carbon Constraints Based on a Super SBM Model with Undesirable Output: Empirical Evidence from China’s Logistics Industry," Sustainability, MDPI, vol. 14(9), pages 1-24, April.
    8. 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.
    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. Ibrahim, Mustapha D. & Pereira, Miguel Alves & Caldas, Paulo, 2024. "Efficiency analysis of the innovation-driven sustainable logistics industry," Socio-Economic Planning Sciences, Elsevier, vol. 96(C).
    2. 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.
    3. Karolina Sikirinskaya & Elena Ponomarenko, 2024. "Transport and Logistics Market Transformation: Prospects for Russian-Chinese Integration under Sanctions Restrictions," Economic Studies journal, Bulgarian Academy of Sciences - Economic Research Institute, issue 4, pages 144-163.
    4. 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.
    5. Kumar, V.N.S.A. & Kumar, V. & Brady, M. & Garza-Reyes, Jose Arturo & Simpson, M., 2017. "Resolving forward-reverse logistics multi-period model using evolutionary algorithms," International Journal of Production Economics, Elsevier, vol. 183(PB), pages 458-469.
    6. Ruijing Zheng & Yu Cheng & Haimeng Liu & Wei Chen & Xiaodong Chen & Yaping Wang, 2022. "The Spatiotemporal Distribution and Drivers of Urban Carbon Emission Efficiency: The Role of Technological Innovation," IJERPH, MDPI, vol. 19(15), pages 1-22, July.
    7. Hongtao Jiang & Jian Yin & Yuanhong Qiu & Bin Zhang & Yi Ding & Ruici Xia, 2022. "Industrial Carbon Emission Efficiency of Cities in the Pearl River Basin: Spatiotemporal Dynamics and Driving Forces," Land, MDPI, vol. 11(8), pages 1-22, July.
    8. Cortés, Pablo & Muñuzuri, Jesús & Guadix, José & Onieva, Luis, 2013. "Optimal algorithm for the demand routing problem in multicommodity flow distribution networks with diversification constraints and concave costs," International Journal of Production Economics, Elsevier, vol. 146(1), pages 313-324.
    9. Graham, Stephanie & Graham, Byron & Holt, Diane, 2018. "The relationship between downstream environmental logistics practices and performance," International Journal of Production Economics, Elsevier, vol. 196(C), pages 356-365.
    10. Henryk Dzwigol & Nataliia Trushkina & Aleksy Kwilinski, 2021. "The Organizational and Economic Mechanism of Implementing the Concept of Green Logistics," Virtual Economics, The London Academy of Science and Business, vol. 4(2), pages 41-75, April.
    11. Shutian Cui & Renlong Wang, 2024. "A Novel {\delta}-SBM-OPA Approach for Policy-Driven Analysis of Carbon Emission Efficiency under Uncertainty in the Chinese Industrial Sector," Papers 2408.11600, arXiv.org, revised Dec 2024.
    12. Schrettle, Stefan & Hinz, Andreas & Scherrer -Rathje, Maike & Friedli, Thomas, 2014. "Turning sustainability into action: Explaining firms' sustainability efforts and their impact on firm performance," International Journal of Production Economics, Elsevier, vol. 147(PA), pages 73-84.
    13. Wen Qin & Xiaolie Qi, 2022. "Evaluation of Green Logistics Efficiency in Northwest China," Sustainability, MDPI, vol. 14(11), pages 1-14, June.
    14. Rui Ren & Wanjie Hu & Jianjun Dong & Bo Sun & Yicun Chen & Zhilong Chen, 2019. "A Systematic Literature Review of Green and Sustainable Logistics: Bibliometric Analysis, Research Trend and Knowledge Taxonomy," IJERPH, MDPI, vol. 17(1), pages 1-25, December.
    15. Maria João Santos & Pedro Amorim & Alexandra Marques & Ana Carvalho & Ana Póvoa, 2020. "The vehicle routing problem with backhauls towards a sustainability perspective: a review," TOP: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 28(2), pages 358-401, July.
    16. 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.
    17. Dekker, Rommert & Bloemhof, Jacqueline & Mallidis, Ioannis, 2012. "Operations Research for green logistics – An overview of aspects, issues, contributions and challenges," European Journal of Operational Research, Elsevier, vol. 219(3), pages 671-679.
    18. Harris, Irina & Mumford, Christine L. & Naim, Mohamed M., 2014. "A hybrid multi-objective approach to capacitated facility location with flexible store allocation for green logistics modeling," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 66(C), pages 1-22.
    19. Asghari, Mohammad & Mirzapour Al-e-hashem, S. Mohammad J., 2021. "Green vehicle routing problem: A state-of-the-art review," International Journal of Production Economics, Elsevier, vol. 231(C).
    20. Kramer, Raphael & Subramanian, Anand & Vidal, Thibaut & Cabral, Lucídio dos Anjos F., 2015. "A matheuristic approach for the Pollution-Routing Problem," European Journal of Operational Research, Elsevier, vol. 243(2), pages 523-539.

    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:spr:endesu:v:26:y:2024:i:2:d:10.1007_s10668-022-02833-2. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.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.