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Spatial–Temporal Differentiation and Trend Prediction of Coupling Coordination Degree of Port Environmental Efficiency and Urban Economy: A Case Study of the Yangtze River Delta

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  • Min Wang

    (Business School, Hohai University, Nanjing 210098, China
    School of Economics and Finance, Hohai University, Changzhou 213200, China
    Low Carbon Economy Research Institute, Hohai University, Nanjing 210098, China)

  • Yu Lan

    (Business School, Hohai University, Nanjing 210098, China
    School of Economics and Finance, Hohai University, Changzhou 213200, China)

  • Huayu Li

    (Business School, Hohai University, Nanjing 210098, China
    School of Economics and Finance, Hohai University, Changzhou 213200, China)

  • Xiaodong Jing

    (Business School, Hohai University, Nanjing 210098, China
    Asia Institute, The University of Melbourne, Melbourne, VIC 3010, Australia)

  • Sitong Lu

    (School of Management and Economics, The Chinese University of Hong Kong, Shenzhen, Shenzhen 518172, China)

  • Kexin Deng

    (Business School, New York University Shanghai, Shanghai 200122, China)

Abstract

Green development is a primary path for ports and cities to achieve a low-carbon transition under the Sustainable Development Goals and a powerful driving force to elevate regional port–city relations to a high level of coordination. In this paper, twenty port cities in the Yangtze River Delta (YRD) were selected and port environmental efficiency (PEE) was calculated through the window SBM model, while the EW-TOPSIS model was used to evaluate high-quality urban economic development (HED). The coupling coordination degree (CCD) model, the kernel density model, GIS spatial analysis, and the grey prediction model were used to further explore the spatial–temporal dynamic evolution and prediction of the CCD between PEE and HED. The results suggested that: (1) PEE fluctuation in the YRD is increasing, with a trend of seaports achieving higher PEE than river ports; (2) HED in the YRD shows upward trends, and the polarization of individual cities is obvious; (3) Temporally, the CCD in the YRD has risen from 0.438 to 0.518. Shanghai consistently maintains intermediate coordination, and Jiangsu has experienced the most significant increase in CCD. Spatially, CCD is led by Lianyungang, Suzhou, Shanghai, and Ningbo-Zhoushan, displaying a decreasing distribution pattern from east to west. The projection for 2026 suggests that all port cities within the YRD will have transitioned to a phase of orderly development. To enhance the coordination level in the YRD, policymakers should consider the YRD as a whole to position the ports functionally and manage them hierarchically, utilize the ports to break down resource boundaries to promote the synergistic division of labor among cities, and then tilt the resources towards Anhui.

Suggested Citation

  • Min Wang & Yu Lan & Huayu Li & Xiaodong Jing & Sitong Lu & Kexin Deng, 2024. "Spatial–Temporal Differentiation and Trend Prediction of Coupling Coordination Degree of Port Environmental Efficiency and Urban Economy: A Case Study of the Yangtze River Delta," Land, MDPI, vol. 13(3), pages 1-19, March.
  • Handle: RePEc:gam:jlands:v:13:y:2024:i:3:p:374-:d:1358078
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    References listed on IDEAS

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