COVID-19 and mobility in tourism cities: A statistical change-point detection approach

This study uses statistical change-point analysis to investigate the impact of the COVID-19 pandemic on people's mobility in tourism cities. Based on the collected data sample containing mobility time series of nine tourism cities on three categories of places - Retail and Recreation, Parks and Transit Stations, we find apart from the mobility reduction observed on all place categories, most cities experienced a three-phase pattern. Moreover, a time lag between the mobility decrease and introduction of lockdown measures is detected, suggesting that the latter is not the reason for people to reduce movement. Further, the mobility reduction is found less significant on Parks and appeared earlier on Transit Stations. The findings provide useful insights on how tourism, hospitality and travel sectors are affected by crisis events. © 2021 The Authors