Influence of perceived risk on travel mode choice during Covid-19

Abstract

We aim to understand the effect of different information types on risk perception and examine the relationship between perceived risk and travel behaviour during a pandemic outbreak. A hybrid choice model structure, incorporating a multiple discrete-continuous extreme value model, was formulated and estimated to explore travellers’ mode choice and usage changes. We used a risk perception map to visually explain which risk elements felt unfamiliar and uncontrollable to travellers. Virus variation, Potential sequelae, and Long-term coexistence of coronavirus with humans were perceived as the most unfamiliar and uncontrollable risk elements. The model results indicate that increased perceived risk tends to reduce travellers’ use of public transport and increase the use of shared bikes and private cars. Reducing passengers’ perceived risk is critical to encourage the re-uptake of public transport in the post-pandemic era. As travellers also show significant heterogeneity, governments should aim to design targeted intervention strategies to encourage different travellers to return to public transport when considering risk communication.