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Computational and data-driven approaches are imperative for assessing and improving the competitiveness of international dry ports in logistics networks. This study develops a multi-criteria assessment framework integrating infrastructure development, logistics capacity, regional economic performance, and future development potential of ports along the western region’s new land-sea corridor. The entropy method is employed to calculate indicator weights, while the GAR-TOPSIS model quantifies the competitiveness of 40 dry ports in 2022. To further analyze competitiveness levels, the K-means clustering algorithm is applied, revealing distinct patterns and trends across the ports. The findings indicate that infrastructure and logistics are immediate drivers of competitiveness, while regional economic factors and development potential significantly influence long-term advantages. Based on the results, this study proposes strategies to enhance port competitiveness: (1) leveraging computational tools to optimize infrastructure and service capabilities; (2) fostering specialized industrial strengths to drive economic growth; and (3) adopting intelligent systems to improve management practices and logistics efficiency. These measures aim to sustain the competitiveness of ports and promote balanced development across the region.

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Computational Models for Analyzing Dry Port Competitiveness Along the Western Land-Sea New Corridor

  • 会议论文

  • 发表日期：

    2025年

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  • Xiaohui Shu,
  • Siyu Yuan,
  • Yumeng Jiang,
  • Ziyan Chen

摘要

Computational and data-driven approaches are imperative for assessing and improving the competitiveness of international dry ports in logistics networks. This study develops a multi-criteria assessment framework integrating infrastructure development, logistics capacity, regional economic performance, and future development potential of ports along the western region’s new land-sea corridor. The entropy method is employed to calculate indicator weights, while the GAR-TOPSIS model quantifies the competitiveness of 40 dry ports in 2022. To further analyze competitiveness levels, the K-means clustering algorithm is applied, revealing distinct patterns and trends across the ports. The findings indicate that infrastructure and logistics are immediate drivers of competitiveness, while regional economic factors and development potential significantly influence long-term advantages. Based on the results, this study proposes strategies to enhance port competitiveness: (1) leveraging computational tools to optimize infrastructure and service capabilities; (2) fostering specialized industrial strengths to drive economic growth; and (3) adopting intelligent systems to improve management practices and logistics efficiency. These measures aim to sustain the competitiveness of ports and promote balanced development across the region.