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

Veronika Harantová (), Jaroslav Mazanec, Vladimíra Štefancová, Jaroslav Mašek and Hana Bruhova Foltynova
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Veronika Harantová: Department of Road and Urban Transport, Faculty of Operation and Economics of Transport and Communications, University of Zilina, Univerzitna 1, 01026 Zilina, Slovakia
Jaroslav Mazanec: Department of Quantitative Methods and Economic Informatics, Faculty of Operation and Economics of Transport and Communications, University of Zilina, Univerzitna 1, 01026 Zilina, Slovakia
Vladimíra Štefancová: Department of Railway Transport, Faculty of Operation and Economics of Transport and Communications, University of Zilina, Univerzitna 1, 01026 Zilina, Slovakia
Jaroslav Mašek: Department of Railway Transport, Faculty of Operation and Economics of Transport and Communications, University of Zilina, Univerzitna 1, 01026 Zilina, Slovakia

Mathematics, 2023, vol. 11, issue 3, 1-17

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

Keywords: cluster analysis; mobility; COVID-19; travel behaviour (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (5)

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