Mobility challenges for senior passengers during the Covid-19 pandemic

Abstract

This paper aims to clarify the differences in the factors influencing subway traffic behaviour of senior passengers (SP) and non-senior passengers (NSP) during the coronavirus disease-2019 (Covid-19) pandemic based on big data in Seoul, South Korea. A one-way analysis of variance is carried out to analyse the influencing factors of subway use of SP and NSP during the Covid-19 pandemic. Furthermore, a multiple linear regression is conducted to identify the factors affecting SP and NSP. Finally, the traffic patterns of SP and NSP were analysed with respect to districts by way of geographically weighted regression. The spatial scope of this study includes Seoul, which consists of 25 districts (gu). The temporal range is from 1 January 2017 to 31 December 2020, and the number of people using subway in Seoul is used as the main dataset. The results suggest that SP are more affected by subway than NSP, and the most influential factors are cultural gathering facilities and the number of subway stations. The regression model showed high explanatory power for southern Seoul, which has a high concentration of facilities related to the influencing factors.