Exploring spatio-temporal characteristics of tourist travel behavior before and after COVID-19: A case study in Hong Kong, China

ABSTRACT

The COVID-2019 pandemic has a huge impact on tourism industry, and mastering the spatial and temporal characteristics of tourists' travel behavior during the period is very crucial for the recovery and the development of the tourism industry. This study adopts time series statistics and complex network analysis to compare and examine the network evolution features of Hong Kong before and during the COVID-19 pandemic based on the comments data generated from TripAdvisor website in 2019 and 2020. The results show that (1) Tourists' travel behavior patterns have changed to a certain degree, and they prefer to visit a small number of destinations during an itinerary. (2) Key destinations still play important roles in connecting other destinations, but the tourism community formed around the key destinations has varied from extremely dense to relatively sparse gathering. (3) The number of tourists in extremely hot destinations has been greatly declined, those destinations with fewer tourists and relatively far away from the downtown have attracted more attention. Moreover, industrial destinations have been always the most popular type of tourism destination. © 2022, Science Press. All rights reserved.