Modelling second-best choices from the choice-based sample: revelation of potential mode-switching behaviour from transit passenger surveys
mode - rail, place - north america, place - urban, ridership - behaviour, ridership - mode choice, ridership - commuting, ridership - modelling, planning - surveys, land use - impacts, land use - urban density
Generalized extreme value model, Choice-based sample, Second-best choice, Latent satisfaction, Mode-switching behaviour, Commuter rail, Commuting mode
The paper presents an application of the choice-based sample to explain the choice of non-chosen alternatives. It uses a passenger survey of GO rail transit of the Greater Toronto and Hamilton Area to investigate the factors that may affect the potential mode switching of the current GO rail users. It used a hybrid generalized extreme value with an endogenous latent variables model for jointly modelling the GO rail station access mode choice and the choice of switching from GO rail to alternative modes. The empirical results reveal that the influence of station access difficulty does not become an issue for relatively shorter access distance (e.g. station access distance is less than 5% of the total origin–destination distance). The traveller would rather switch access mode than switching away from GO rail for such a case. Competition of alternative modes, captured through the composite cost of using an alternative to GO rail, is also found to be critical in potential switching from GO rail. It is also clear that drive-alone is the most attractive alternative to switch to. Overall, the empirical investigations reveal that land-use policies that encourage higher residential density around a GO rail station would make a higher number of modes (including non-motorized modes) feasible as access to GO rail mode and thereby reduce the impact of access cost on mode switching behaviour from GO rail. Similarly, developing a high occupancy vehicle lane network and high occupancy tolled road network to serve along the corridors that are served by GO rail would encourage multimodality and help to tackle GO rail’s capacity constraints and their corresponding negative effect of in-train crowding.
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Rashedi, Z., Hasnine, M.S., & Habib, K.N. (2022). Modelling second-best choices from the choice-based sample: revelation of potential mode-switching behaviour from transit passenger surveys. Public Transport, Vol. 14, pp. 609–633.