Segmentation of Chinese Tourists by Seasonal and Trend Patterns: The Case of Macao

This study proposes a novel data-driven technique utilizing feature-based time series clustering to segment the huge Chinese market based on two distinct tourism phenomena, seasonality and growth trend. The study first extracted the temporal and spatial features from secondary time-series data of Macao tourist arrivals from 23 provinces/municipalities in mainland China and clustered, based on the extracted features, the tourists, thus splitting regions into five segments with distinct seasonal and growth patterns. The segments suggested there is an association between the tourism demand dynamic and the regions’ geographical and socio-economic characteristics. This exploratory study provides practical insights that could enable destination planners to target markets with high growth potential and to manage seasonal variation in tourism demand through formulating policies catering to different market segments.