Spatial structures of tourism destinations: A trajectory data mining approach leveraging mobile big data

Abstract The advancement of mobile technology provides an opportunity to obtain the real-time information of travelers, such as their spatial and temporal behaviors, during their visits to a destination. This study analyzes a large scale mobile phone dataset that captures the cellphone trace of international travelers who visited South Korea. We apply a trajectory data mining approach to understand the spatial structures of tourist activities within three different destinations. Through spatial clustering analysis and sequential pattern mining, the study reveals multiple “hot spots” (or popular areas) in travel destinations and spatial interactions across these places. As a result, this paper provides important tourism implications integrating spatial models with destination planning, which is the foundation of tourism design.