A latent class analysis to understand riders’ adoption of on-demand mobility services as a complement to transit

Yiyuan Wang () and Qing Shen ()
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Yiyuan Wang: University of Washington
Qing Shen: University of Washington

Transportation, 2024, vol. 51, issue 3, No 11, 1043-1061

Abstract: Abstract On-demand app-based shared mobility services have created new opportunities for complementing traditional fixed-route transit through transit agencies’ efforts to incorporate them into their service provision. This paper presents one of the first studies that rigorously examine riders’ responses to a pilot aimed at providing such a transit-supplementing service. The study conducts latent class analysis on riders of the Via to Transit program, a mobility pilot in the Seattle region where on-demand service was offered to connect transit riders to light rail stations. The analysis identifies three distinct rider groups with heterogenous responses to the on-demand service: (1) riders who previously used private cars or ride-hailing; (2) riders who were pedestrians and bikers but switched likely because of safety concern; (3) mostly socio-economically disadvantaged riders who previously relied on the bus, but switched to the new service for the convenience and speed. These results point to rich transportation policy implications, which can inform decision-making by public transit agencies as they are exploring alternative ways to deliver the mobility services.

Keywords: Public transit; On-demand shared mobility; Latent class analysis; Heterogeneous travel behavior responses; Built environments (search for similar items in EconPapers)
Date: 2024
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DOI: 10.1007/s11116-022-10351-3

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