The study examines Chinese tourists’ shopping behaviors classified by region and investigates what they like and buy more or less in Taiwan. The objective of our study is to identify shopping behaviors and preferences of Chinese tourists clustering classified by region in Taiwan. The data used for this research are extracted from a rich data set includes information collected from 8,566 Chinese tourists in 303 groups visiting Taiwan in 2016 across the smart computing system of the travel agencies. One-way ANOVA is used in analyzing data to compare three regions of Chinese tourists and finds out their shopping behaviors are very different from segment to segment. Finally, the study not only concludes that there are significant differences in each of the three segments, but also provides a new vision of business intelligence and analytics (BI&A) which may be applied to tourism and future research.

Chinese tourists, shopping behaviors, clustering classified, smart computing, business intelligence and analytics (BI&A).