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粤港澳大湾区港群效率测度、时空演进及影响因素研究OACHSSCD

Research on efficiency measurement,spatiotemporal evolution,and influencing factors of port cluster in the Guangdong-Hong Kong-Macao Great Bay Area

中文摘要英文摘要

粤港澳大湾区港群效率提升对区域经济一体化与"双循环"新发展格局的构建具有重要意义.基于超效率 SBM 模型,测度2010-2023 年大湾区11 个港口效率,综合运用核密度估计、标准差椭圆方法与 Tobit 回归模型揭示其时空演进规律及影响因素.结果表明:大湾区港群效率整体呈波动上升态势,各港口效率变化异质性显著,港口间形成三级分层发展格局与"竞合并存"关系;时间演进上,核密度曲线中心位置右移,主峰扁平化,波峰数目由三峰向四峰演变;空间演进上,标准差椭圆重心向西北移动,空间分布从集中趋向离散,方位角先逆时针后顺时针偏移,扁率先上升后下降;影响因素中,产业结构、港口功能、科创水平显著提升港群效率,而对外开放程度则产生抑制效应.

Enhancing the efficiency of the port cluster in the Guangdong-Hong Kong-Macao Greater Bay Area is of great significance for regional economic integration and the establishment of the"dual circulation"new development pattern.Based on the super SBM model,this paper measures the efficiency of 11 ports in the Greater Bay Area from 2010 to 2023.It comprehensively employs kernel density estimation,standard deviation ellipse,and the Tobit model to reveal the spatiotemporal evolution patterns and influencing factors.The results indicate that,the overall efficiency of the port cluster in the Greater Bay Area shows a fluctuating upward trend,with significant heterogeneity in efficiency changes among individual ports.The efficiency value among ports is obviously stratified,forming a coexistence relationship of competition and cooperation.In terms of the time evolution,the kernel density curve shifts to the right,the main peak flattens,and the number of wave peak evolves from three peaks to four peaks.In terms of the spatial evolution,the center of gravity of the standard deviation ellipse moves to the northwest,the distribution tends to be discrete from concentration,the azimuth first moves counterclockwise and then clockwise,and the oblateness first rises and then decreases.In terms of the influencing factors,industrial structure,port functions,and technological innovation have a significant positive effect on the efficiency of the port cluster,while the degree of opening up has a significant negative effect.

熊盼

广州华立学院商学院||长沙理工大学经济与管理学院

港群效率时空演进超效率SBMTobit模型粤港澳大湾区

port cluster efficiencyspatiotemporal evolutionsuper SBMTobit modelthe Guangdong-Hong Kong-Macao Great Bay Area

《水利经济》 2026 (3)

28-36,54,10

国家自然科学基金项目(62263031)广东省普通高校青年创新人才类项目(2023WQNCX123)广州市哲学社会科学规划项目(2025GZGJ243)

10.3880/j.issn.1003-9511.2026.03.004

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