IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v15y2023i22p15739-d1276189.html
   My bibliography  Save this article

Coupling Coordination and Spatiotemporal Evolution of Low-Carbon Logistics, Industrial Agglomeration, and Regional Economy in the Yangtze River Economic Belt

Author

Listed:
  • Yixuan Huang

    (College of Management, Wuhan University of Technology, Wuhan 430070, China)

  • Mingfei Liu

    (College of Management, Wuhan University of Technology, Wuhan 430070, China)

Abstract

The logistics industry plays a crucial role in the global economy, but also poses significant challenges to the economy, society, and environment due to increasing carbon emissions. Therefore, coordinated development between the logistics industry and regional economy has become a strategic choice for achieving sustainable development. Taking the Yangtze River Economic Belt as an example, this study constructs an evaluation index system of “low-carbon logistics–industrial agglomeration–regional economy” to explore the coupling coordination relationship and spatiotemporal distribution characteristics of the three systems from 2006 to 2020. Furthermore, it analyzes the spatial correlation features and evolutionary trends of the coordinated development among the three systems. The results indicate that during the study period, the coupling coordination degree among the three systems in the Yangtze River Economic Belt showed a fluctuating upward trend but with a relatively low level of coordination. There were significant regional differences, presenting a stepped distribution pattern of “high in the east and low in the west.” The coordinated development among the three systems exhibited a significant positive spatial correlation, with “H–H” and “L–L” agglomerations being dominant. The spatial distribution of coupling coordination degree remained relatively stable, with the overall center of gravity located in the southeast of Hubei Province. The spatial evolution pattern showed a distinct “northeast–southwest” direction. Finally, suggestions for the coordinated and sustainable development of the three systems are put forward.

Suggested Citation

  • Yixuan Huang & Mingfei Liu, 2023. "Coupling Coordination and Spatiotemporal Evolution of Low-Carbon Logistics, Industrial Agglomeration, and Regional Economy in the Yangtze River Economic Belt," Sustainability, MDPI, vol. 15(22), pages 1-23, November.
    • Handle: RePEc:gam:jsusta:v:15:y:2023:i:22:p:15739-:d:1276189
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/15/22/15739/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/15/22/15739/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Hang Jiang & Taipeng Sun & Beini Zhuang & Jiangqiu Wu, 2023. "Determinants of Low-Carbon Logistics Capability Based on Dynamic fsQCA: Evidence from China’s Provincial Panel Data," Sustainability, MDPI, vol. 15(14), pages 1-19, July.
    2. 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.
    3. Dan O'Donoghue & Bill Gleave, 2004. "A Note on Methods for Measuring Industrial Agglomeration," Regional Studies, Taylor & Francis Journals, vol. 38(4), pages 419-427.
    4. Polat, Mustafa & Kara, Karahan & Yalcin, Galip Cihan, 2022. "Clustering Countries on Logistics Performance and Carbon Dioxide (CO2) Emission Efficiency: An Empirical Analysis," Business and Economics Research Journal, Uludag University, Faculty of Economics and Administrative Sciences, vol. 13(2), pages 221-238, April.
    5. Dong Mu & Salman Hanif & Khalid Mehmood Alam & Omer Hanif, 2022. "A Correlative Study of Modern Logistics Industry in Developing Economy and Carbon Emission Using ARDL: A Case of Pakistan," Mathematics, MDPI, vol. 10(4), pages 1-18, February.
    6. Rashidi, Kamran & Cullinane, Kevin, 2019. "Evaluating the sustainability of national logistics performance using Data Envelopment Analysis," Transport Policy, Elsevier, vol. 74(C), pages 35-46.
    7. Matthew Panhans & Lucia Lavric & Nick Hanley, 2017. "The Effects of Electricity Costs on Firm Re-location Decisions: Insights for the Pollution Havens Hypothesis?," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 68(4), pages 893-914, December.
    8. Tone, Kaoru, 2001. "A slacks-based measure of efficiency in data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 130(3), pages 498-509, May.
    9. Nefs, Merten & van Haaren, Jeroen & van Oort, Frank, 2023. "The limited regional employment benefits of XXL-logistics centres in the Netherlands," Journal of Transport Geography, Elsevier, vol. 109(C).
    10. Haojun Wang & Xiao Su & Jun M. Liu, 2023. "The Spatial Spillover Effect of Logistics and Manufacturing Co-Agglomeration on Regional Economic Resilience: Evidence from China’s Provincial Panel Data," Sustainability, MDPI, vol. 15(10), pages 1-23, May.
    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. Ashrafi, Ali & Seow, Hsin-Vonn & Lee, Lai Soon & Lee, Chew Ging, 2013. "The efficiency of the hotel industry in Singapore," Tourism Management, Elsevier, vol. 37(C), pages 31-34.
    2. Chen, Yufeng & Ni, Liangfu & Liu, Kelong, 2021. "Does China's new energy vehicle industry innovate efficiently? A three-stage dynamic network slacks-based measure approach," Technological Forecasting and Social Change, Elsevier, vol. 173(C).
    3. Honma, Satoshi, 2012. "Environmental and economic efficiencies in the Asia-Pacific region," MPRA Paper 43361, University Library of Munich, Germany.
    4. 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.
    5. Le Sun & Congmou Zhu & Shaofeng Yuan & Lixia Yang & Shan He & Wuyan Li, 2022. "Exploring the Impact of Digital Inclusive Finance on Agricultural Carbon Emission Performance in China," IJERPH, MDPI, vol. 19(17), pages 1-18, September.
    6. Senhua Huang & Lingming Chen, 2023. "The Impact of the Digital Economy on the Urban Total-Factor Energy Efficiency: Evidence from 275 Cities in China," Sustainability, MDPI, vol. 15(4), pages 1-20, February.
    7. Can Zhang & Jixia Li, 2024. "The Impact of Official Promotion Incentives on Urban Ecological Welfare Performance and Its Spatial Effect," Sustainability, MDPI, vol. 16(7), pages 1-29, April.
    8. Muliaman Hadad & Maximilian Hall & Karligash Kenjegalieva & Wimboh Santoso & Richard Simper, 2011. "Banking efficiency and stock market performance: an analysis of listed Indonesian banks," Review of Quantitative Finance and Accounting, Springer, vol. 37(1), pages 1-20, July.
    9. Gómez-Calvet, Roberto & Conesa, David & Gómez-Calvet, Ana Rosa & Tortosa-Ausina, Emili, 2014. "Energy efficiency in the European Union: What can be learned from the joint application of directional distance functions and slacks-based measures?," Applied Energy, Elsevier, vol. 132(C), pages 137-154.
    10. Jo, Ah-Hyun & Chang, Young-Tae, 2023. "The effect of airport efficiency on air traffic, using DEA and multilateral resistance terms gravity models," Journal of Air Transport Management, Elsevier, vol. 108(C).
    11. Hongli Liu & Xiaoyu Yan & Jinhua Cheng & Jun Zhang & Yan Bu, 2021. "Driving Factors for the Spatiotemporal Heterogeneity in Technical Efficiency of China’s New Energy Industry," Energies, MDPI, vol. 14(14), pages 1-21, July.
    12. Yi-Chung Hsu, 2014. "Efficiency in government health spending: a super slacks-based model," Quality & Quantity: International Journal of Methodology, Springer, vol. 48(1), pages 111-126, January.
    13. Mousavi, Mohammad M. & Ouenniche, Jamal & Xu, Bing, 2015. "Performance evaluation of bankruptcy prediction models: An orientation-free super-efficiency DEA-based framework," International Review of Financial Analysis, Elsevier, vol. 42(C), pages 64-75.
    14. Chenchen Su & Jinchuan Shen & Fei Wang, 2024. "Can income growth and environmental improvements go hand in hand? An empirical study of Chinese agriculture," Agricultural Economics, Czech Academy of Agricultural Sciences, vol. 70(7), pages 321-333.
    15. Fan Wang & Lili Feng & Jin Li & Lin Wang, 2020. "Environmental Regulation, Tenure Length of Officials, and Green Innovation of Enterprises," IJERPH, MDPI, vol. 17(7), pages 1-16, March.
    16. Ningyi Liu & Yongyu Wang, 2022. "Urban Agglomeration Ecological Welfare Performance and Spatial Convergence Research in the Yellow River Basin," Land, MDPI, vol. 11(11), pages 1-18, November.
    17. Zhou, Lin & Fan, Jianshuang & Hu, Mingzhi & Yu, Xiaofen, 2024. "Clean air policy and green total factor productivity: Evidence from Chinese prefecture-level cities," Energy Economics, Elsevier, vol. 133(C).
    18. Loske, Dominic & Klumpp, Matthias, 2021. "Human-AI collaboration in route planning: An empirical efficiency-based analysis in retail logistics," International Journal of Production Economics, Elsevier, vol. 241(C).
    19. Nguyen Thi Kim Lien & Luyen Le Anh, 2024. "Adopting SBM-Max and Super SBM-Max to Evaluate the Efficiency of Freight Transportation Arrangement Providers: A Study in Vietnam," LOGI – Scientific Journal on Transport and Logistics, Sciendo, vol. 15(1), pages 73-84.
    20. Chia-Nan Wang & Jen-Der Day & Nguyen Thi Kim Lien & Luu Quoc Chien, 2018. "Integrating the Additive Seasonal Model and Super-SBM Model to Compute the Efficiency of Port Logistics Companies in Vietnam," Sustainability, MDPI, vol. 10(8), pages 1-17, August.

    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:22:p:15739-:d:1276189. 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.