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

Author

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  • 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
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    References listed on IDEAS

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    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. 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.
    3. 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.
    4. 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.
    5. 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).
    6. 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.
    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, 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.
    9. 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.
    10. 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.
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