Revealing the city-scale spatial coopetitive relationships between themed and non-themed tourism attractions in three Chinese cities

The themes of cities and the types of attractions they offer significantly influence visitors’ decisions to explore specific destinations. However, systematic research on the competitive and cooperative (coopetition) relationships between thematic and non-thematic urban attractions remains scarce. This study analyzes the spatial patterns of coopetition relationships between thematic and non-thematic attractions in three Chinese tourist cities—Chengdu, Dalian, and Shenyang—during the 2020 National Day, based on pedestrian trajectory data provided by a service operator. By leveraging network analysis, geographic metrics, and a quantitative modeling approach, this paper introduces a novel framework that integrates network analysis with motif analysis to examine the interaction patterns between attractions. Specifically, the Fruchterman–Reingold algorithm is utilized to establish an analytical framework for thematic and non-thematic interactions among urban attractions. The results reveal both similarities and differences in the coopetition relationships of urban attractions. Across the cities studied, thematic attractions exhibit a strong tendency to cluster, while the competition among non-thematic attractions is more evenly distributed. The study is helpful to dynamically abstract the coopetition relationships and support the sustainable decision-making for urban tourism management.