Abstract |
The COVID-19 pandemic has drastically impacted people’s travel
behaviour and introduced uncertainty in the demand for public
transport. To investigate user preferences for travel by London
Underground during the pandemic, we conducted a stated choice experiment
among its pre-pandemic users (N = 961). We analysed the
collected data using multinomial and latent class logit models. Our
discrete choice analysis provides two sets of results. First, we derive
the crowding multiplier estimate of travel time valuation (i.e., the
ratio of the value of travel time in uncrowded and crowded situations)
for London underground users. The results indicate that travel time
valuation of Underground users increases by 73% when it operates at
technical capacity. Second, we estimate the sensitivity of the
preference for the London Underground relative to the epidemic situation
(confirmed new COVID-19 cases) and interventions (vaccination rates and
mandatory face masks). The sensitivity analysis suggests that making
face masks mandatory is a main driver for recovering the demand for the
London underground. The latent class model reveals substantial
preference heterogeneity. For instance, while the average effect of
mandatory face masks is positive, the preferences of 30% of pre-pandemic
users for travel by the Underground are negatively affected. The
positive effect of mandatory face masks on the likelihood of taking the
Underground is less pronounced among males with age below 40 years,
and a monthly income below 10,000 GBP. The estimated preference
sensitivities and crowding multipliers are relevant for supply–demand
management in transit systems and the calibration of advanced
epidemiological models. |