Meng, M. ORCID: 0000-0001-7240-6454, Koh, P. P. and Wong, Y. D. (2015) Influence of socio-demography and operating streetscape on last-mile mode choice. Journal of Public Transportation, 19 (2). pp. 38-54. ISSN 1077-291X (Print), 2375-0901 (Online) (doi:https://doi.org/10.5038/2375-0901.19.2.3)

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Abstract

This study investigated how personal and operational factors (travel distance and streetscape) influence traveler mode choice decisions for the last-mile home-bound trip stage from rail transit stations. Personal factors include the socio-demography of travelers, and attributes of the streetscape include the built environment (degree of areal development), prevalence of cycling, availability of short-range transport modes, and walking/cycling infrastructure. Interviewers randomly intercepted pedestrians to administer a mode choice survey at five rail transit station exits and engaged all available cyclists at bicycle parking areas in the vicinity of stations in Singapore. A multimodal logit regression model revealed a significant relationship between the last-mile home-bound trip maker’s mode choice with factors of age, gender, travel distance between transit station and destination, number of cyclists along adjacent links surrounding transit stations, number of feeder bus services to destination, availability of private vehicle, and household income. The calibrated model was applied to compute the probability of walking, cycling, and taking a feeder bus for the last-mile home-bound trip maker from a transit station. This study provides useful information for improving the efficiency and connectivity of first/last-mile mobility in a multimodal transport network.

Item Type:	Article
Uncontrolled Keywords:	Last-mile home-bound trip; operating streetscape; mode choice; transit stations; multimodal logit regression model
Subjects:	H Social Sciences > HE Transportation and Communications
Faculty / School / Research Centre / Research Group:	Faculty of Business Faculty of Business > Networks and Urban Systems Centre (NUSC) > Connected Cities Research Group Faculty of Business > Department of Systems Management & Strategy
Last Modified:	03 May 2019 12:30
URI:	http://gala.gre.ac.uk/id/eprint/22697

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