Previous research studied the spatiotemporal patterns in different visitor segments but lacks evidence of the segmentation of resident tourists and non-resident tourists in multi-city travel. To fill this gap, this study conducts a big data study using hotel check-in registers. The exploratory data analysis visualizes the spatiotemporal patterns and the differences between resident tourists and non-resident tourists. Then, the spatiotemporal patterns are measured by the length of stay and the number of visited cities. The regression shows that both the length of stay and the number of visited cities of non-resident tourists are higher than those of resident tourists. Moreover, non-resident tourists reduce their length of stay and their number of visited cities more than resident tourists on three-day holidays, while they increase their number of visited cities less than resident tourists on seven-day holidays. This study has significant implications for understanding spatiotemporal patterns and visitors' segmentations.

先前的研究研究了不同游客细分的时空模式，但缺乏多城市旅游中居民游客和非居民游客细分的证据。为了填补这一空白，本研究使用酒店登记入住进行了大数据研究。探索性数据分析可视化了居民游客和非居民游客之间的时空模式和差异。然后，时空模式通过停留时间和访问城市的数量来衡量。回归结果表明，非居民游客的逗留时间和到访城市数量均高于居民游客。此外，非居民游客在三天假期中的停留时间和访问城市数量比居民游客减少，而他们在7天假期中增加的访问城市数量少于居民游客。这项研究对于理解时空模式和访客的细分具有重要意义。