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Node Identification and Dynamic Interaction of the Synergetic Network of Ice–Snow Tourism in Northeast China

Author

Listed:
  • Yarou Tan

    (School of Geographical Science and Tourism, Jilin Normal University, Siping 136000, China)

  • Yingyue Sun

    (School of Geographical Science and Tourism, Jilin Normal University, Siping 136000, China)

  • Peng Chen

    (School of Geographical Science and Tourism, Jilin Normal University, Siping 136000, China)

  • Huarong Li

    (School of Geographical Science and Tourism, Jilin Normal University, Siping 136000, China)

Abstract

Ice–snow tourism in Northeast China is developing rapidly. Against this backdrop, revealing the spatial network structure of ice–snow tourism cities and assessing their disturbance resistance capacity is of great significance for achieving high-quality development of regional ice–snow tourism. This study takes 25 cities across the three northeastern provinces as network nodes, using data covering the period from January 2024 to March 2025. Integrating a complex network analysis framework, this paper comprehensively employs an accessibility model, tourism symbiotic linkage intensity model, and core–periphery model to distinguish core and peripheral cities within the network, analyze its structural characteristics and spatial patterns, and evaluate network vulnerability by simulating two scenarios: random attacks and deliberate attacks. The results indicate that: (1) Accessibility presents a concentric zonal pattern that attenuates gradually from the center to the periphery, accompanied by pronounced north–south disparities. Urban symbiosis intensity is strongly influenced by transportation distance, exhibiting a distinct proximity symbiosis pattern. (2) An ice–snow tourism symbiotic network has initially taken shape among northeastern cities. The network displays small-world properties; however, urban development is unbalanced, with marked hierarchical differentiation. Based on geographic location and resource endowments, the network can be divided into four cohesive subgroups. (3) The symbiotic network proves robust under random attacks, whereas connectivity declines sharply under deliberate attacks, embodying typical “robust-yet-vulnerable” structural characteristics. Both expanding the scale of core nodes and optimizing inter-node connection weights can significantly enhance network robustness. The static identification and dynamic dependency evaluation framework constructed in this study can effectively identify key nodes and vulnerable links within ice–snow city networks, and can serve as a reference for the coordinated development and structural optimization of ice-snow tourism in Northeast China.

Suggested Citation

  • Yarou Tan & Yingyue Sun & Peng Chen & Huarong Li, 2026. "Node Identification and Dynamic Interaction of the Synergetic Network of Ice–Snow Tourism in Northeast China," Sustainability, MDPI, vol. 18(14), pages 1-27, July.
  • Handle: RePEc:gam:jsusta:v:18:y:2026:i:14:p:7141-:d:1989748
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