Identifying tourism attractiveness based on intra-destination tourist behaviour: evidence from Wi-Fi data

Knowledge of tourism attractiveness is crucial for tourists to choose preferred destinations and helps tourism managers configure attractive resources to better meet tourist demands. However, small-scale (e.g. intra-destination) studies of tourism attractiveness are scarce, despite their unique significance in understanding tourist demand at the destination level. Based on time geography theory, this study proposes a new method called the stay-time-based tourism attractiveness index (STTAI), which can be used to identify tourism attractiveness within a destination using Wi-Fi data. Specifically, we tracked Wi-Fi probe requests from 670,000 travellers over a month in the Shichahai scenic area, a famous cultural tourism destination in Beijing. After segmenting tourists from the Wi-Fi data, we employed the STTAI to identify locations with frequent and extended tourist stays as activity stations with high tourism attractiveness. Further, this study examined the environmental impact on identified tourism attractiveness using regression analysis.