Understanding tourist behavior at the origin-city level is essential for destination planning and regional tourism management. Most existing studies focus on aggregate intercity mobility volumes, overlooking how tourists from different cities distribute their visits across various attractions. This study addresses this gap by analyzing origin-city-level visitation patterns to three attraction categories (i.e., cultural-historic, natural scenery, and leisure) using weekly mobility data from over 300 Chinese cities to Nanjing during 2018–2019. First, the spatiotemporal heterogeneity of visitation to three attraction categories is analyzed. Second, a data-driven regionalization is conducted based on intercity similarities in attraction visitation. Logistic regression is then employed to examine how city-level characteristics, including socioeconomic, demographic, geographic, and functional attributes, are associated with these visitation patterns. Results reveal pronounced spatial heterogeneity and two dominant visitation regimes covering approximately 92% of cities: one favoring cultural-historic attractions in northern China and Guangdong, and another exhibiting more balanced visitation between cultural-historic and nature-scenery attractions in southern regions. Regression analyses highlight the importance of demographic composition, geographic orientation, urban functions, and digital attention in shaping intercity visitation differences. These findings provide empirical support for behavior-informed tourism planning, enabling policymakers to align destination management and resource allocation with the visitation patterns of different origin cities.
Liao et al. (Sun,) studied this question.