Abstract

Since the start of 2020, we have seen major changes in the way communities operate. Mobility behaviour has been drastically impacted by work from home (WFH) and by lockdowns and restrictions in different jurisdictions. This study investigates the influence of WFH and different lockdown patterns on commuting and non-commuting trips in Australia by workers between early 2020 and late 2021. The data includes three waves of data collection to represent different lockdown periods. A multiple discrete–continuous extreme value (MDCEV) model is estimated to represent the number of one-way trips undertaken weekly with different purposes (commuting, work-related, education, shopping, personal business/social recreation), and by different modes (car, public transport, active modes). Explanatory variables include socioeconomic characteristics, location, the time period during the pandemic (i.e., waves). In addition, latent variables were included representing underlying attitudes such as satisfaction towards life or concern about the use of public transport – which might certainly play an important role in understanding individual weekly travel behaviour decisions. The model structure has the advantage that it estimates commuting and non-commuting activity together, allowing for a substitution effect between them. The results suggest that across all waves and jurisdictions, respondents who WFH more are more likely to have a higher number of shopping trips and personal business/social recreation trips, perhaps substituting these trips in replacement of their lesser commuting trips. Interestingly, all other influences held constant, individuals who are more concerned about the use of public transport are more likely to undertake commuting trips by all modes, more likely to do shopping trips, and less likely to undertake personal business/social recreation trips – suggesting they are prioritising essential trips rather than social/personal trips and perceive the risk of COVID-19 to be higher due to this travel.

Full Text
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