<p>Tourism ecological security (TES) is a crucial factor influencing the sustainability of urban agglomerations (UAs). However, existing research mainly focuses on the quantitative assessment of TES, neglecting the complexity of its spatial correlation network (SCN) within urban integration contexts. Using the Yangtze River Delta Urban Agglomeration (YRDUA) as a case study, this study employs the DPSIRM-EBM model, social network analysis, and quadratic assignment procedure to systematically explore the structural characteristics and driving mechanisms of TES’s SCN. The findings are as follows: (1) TES in the YRDUA has exhibited a rising trend with an average annual growth of 0.54%, and displays significant spatial heterogeneity. (2) Spatial correlation has transcended simple geographic adjacency and formed a complex multi-core network structure; however, the network density remains relatively low, indicating potential for structural optimization. (3) Network centrality exhibits a “core-periphery” distribution, with eastern cities showing a positive correlation between TES levels and network status, while western cities show an inverse relationship. (4) The SCN of TES can be categorized into four distinct plates with significant spatial correlations and spillover effects between plates. (5) Economic development, city proximity, industrial structure, and human capital positively influence TES’s spatial correlations, while geospatial distance and openness level have negative impacts. Focusing on efficiency and relational perspectives, this study not only proposes an innovative evaluation system for TES but also provides decision support to enhance TES and optimize network structures within UAs.</p>

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Spatial correlation network characteristics of tourism ecological security and its driving mechanism in the Yangtze River Delta Urban Agglomeration, China

  • Zhicheng Lai,
  • Xiaoting Shi,
  • Zhuomin Tao,
  • Lei Li,
  • Cheng Jin

摘要

Tourism ecological security (TES) is a crucial factor influencing the sustainability of urban agglomerations (UAs). However, existing research mainly focuses on the quantitative assessment of TES, neglecting the complexity of its spatial correlation network (SCN) within urban integration contexts. Using the Yangtze River Delta Urban Agglomeration (YRDUA) as a case study, this study employs the DPSIRM-EBM model, social network analysis, and quadratic assignment procedure to systematically explore the structural characteristics and driving mechanisms of TES’s SCN. The findings are as follows: (1) TES in the YRDUA has exhibited a rising trend with an average annual growth of 0.54%, and displays significant spatial heterogeneity. (2) Spatial correlation has transcended simple geographic adjacency and formed a complex multi-core network structure; however, the network density remains relatively low, indicating potential for structural optimization. (3) Network centrality exhibits a “core-periphery” distribution, with eastern cities showing a positive correlation between TES levels and network status, while western cities show an inverse relationship. (4) The SCN of TES can be categorized into four distinct plates with significant spatial correlations and spillover effects between plates. (5) Economic development, city proximity, industrial structure, and human capital positively influence TES’s spatial correlations, while geospatial distance and openness level have negative impacts. Focusing on efficiency and relational perspectives, this study not only proposes an innovative evaluation system for TES but also provides decision support to enhance TES and optimize network structures within UAs.