Two-Step Cluster Analysis of Passenger Mobility Segmentation during the COVID-19 Pandemic

In this paper, we analyse the specific behaviour of passengers in personal transport commuting to work or school during COVID-19 pandemic, based on a sample respondents from two countries. We classified commuters two-step cluster analysis into groups showing same characteristics. Data were obtained an online survey, and total size consists 2000 respondents. used five input variables, dividing clusters using analysis. observed significant differences between gender, status, car ownership when public transport, cars, other alternative means transportation for school. also examined individual with socioeconomic socio-demographic factors. total, clusters, results indicate that there are gender status. found prepaid card social status most important factors, as they reach significance level 100%, unlike compared factors importance ranging 60 80%. Moreover, demonstrate cards preferred mainly by female students. Understanding these can help planning policy knowing habits users.