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

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. • This paper examines the effect of different information on perceived risk and the influence of perceived risk on travel behaviour changes during the Covid-19 pandemic. • A risk perception map is used to find out risk elements that feel unfamiliar and uncontrollable to travellers. • A hybrid choice structure, incorporating a multiple discrete-continuous extreme value (MDCEV) model is formulated and estimated to understand mode choice and changes in the frequency of usage of these modes. • As Travellers show significant heterogeneity, targeted intervention strategies for different types of travellers are required to encourage re-uptake of public transport. [ABSTRACT FROM AUTHOR]