Metrics of the complex network algorithm.

Tourists’ motivation is a key factor influencing their spatiotemporal behavior patterns. However, studies analyzing the spatial movement patterns of tourists with different motives are scant. In this study, the travel diaries of 4,306 tourists were employed as the primary data source, and the Louvain algorithm was applied to identify tourist flow networks with different motives; moreover, the complex network method was utilized to analyze the hierarchical structure and heterogeneity of the organizational patterns of tourist flow networks with different motives. The analysis revealed the following main conclusions. (1) There are three types of tourism flow networks with different motivations: exploring nature, exploring culture and nature-culture motivations. (2) All types of motivated tourist flow networks exhibit significant node hierarchies. The core nodes in natural network are the most controllable, whereas those in natural-cultural network are less controllable and more evenly connected. (3) Node connectivity strength decays significantly with distance. Geographic constraints exert the greatest impact on natural network. (4) Different-motivated tourist flow networks present a Multi-scale Hierarchical Nested Pattern. Tourists gather in multi-core cultural networks and multi-core natural-cultural networks, using them as a base to spread to neighboring regions. They shift between core nodes and use new cores as a base for tours. This study enriches the theoretical system of tourist behavior research and provides effective practical recommendations for the Shanxi tourism industry to improve tourists’ travel experience.