TOURISM
ZHANG Kun, XIE Chao-wu, ZHANG Yi-zhen
This study focuses on constructing a cluster intensity model for Chinese tourists' safety accidents in ASEAN. Convergence index, KDE, spatial auto-correlation and Markov chain were used to analyze the spatio-temporal differentiation, dynamic evolution, and driving factors of cluster intensity. The results show that: Firstly, the SD, CV, and GINI of the cluster intensity show a downward trend, suggesting α and absolute β convergence effects. The "peak" of the kernel density curve indicating an overall increase in the cluster intensity. Secondly, there is a spatial correlation in the cluster intensity, and the number of countries with high cluster intensity is expanding over time. Thirdly, the Markov chain transition probability matrix illustrates that the transfer of cluster intensity follows distinct geographical patterns, characterized by spatial locking effects, gradient changes, and continuous enrichment of transfer modes. Fourthly, a driving mechanism model of cluster intensity is constructed based on the 4M framework. The results demonstrate that tourist reception pressure, risks associated with transportation facilities, and risks related to the natural environment significantly influence cluster intensity. Social security risks partially inhibit cluster intensity through the "crowding out" effect of tourist flow, while safety management capability exhibits a noticeable negative inhibition on cluster intensity.