This paper aims at analysing tourist behaviour at destination by focusing on the main determinants of their stop activities. A density-based cluster algorithm identifies the stops from GPS tracking data on cruise passengers starting from data on individual trajectories. A Poisson regression model analyses the effects of socio-demographic, and itinerary characteristics on the number of stops made. The results are of interest both from a methodological perspective, related to the analysis and synthesis of GPS tracking data and from an applied perspective concerning tourists' knowledge of spatial behaviour and its implications for destination management.
|Titolo della pubblicazione ospite||Book of short papers - SIS 2021|
|Numero di pagine||6|
|Stato di pubblicazione||Published - 2021|