Substitution effect or complementation effect for bicycle travel choice preference and other transportation availability: Evidence from US large-scale shared bicycle travel behaviour data

Substitution effect or complementation effect for bicycle travel choice preference and other... Among all transportation modes, how do people choose their strategy when commuting? To better understand travel behaviour in new era, we introduce the perspective of “Multi-Choice” to complement that of existing “Single-Choice” based on the random utility maximisation theory and focus on actual travel data from the Pronto! system in Seattle in 2015, to test such a theory as well as other geographical and demographical data. By using mixed multiple regression, we find that at the peak of weekday use, the accessibility of other transportation modes (quantified by their density of infrastructure) could affect the departure flow of the Pronto! stations around them (within a 0.5 km buffer), but in a different trend in terms of multi-choice process. Besides those, we also find that the density of the points of interest around the station could positively affect departure flows on weekends, while the traffic-related factors did not. The current study broadens the traditional perspective of travel demand models by introducing a multi-choice option, and testing it against actual mode choices in people's daily behaviour using shared-bicycle data from Pronto!, Seattle. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Journal of Cleaner Production Elsevier

Substitution effect or complementation effect for bicycle travel choice preference and other transportation availability: Evidence from US large-scale shared bicycle travel behaviour data

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Publisher
Elsevier
Copyright
Copyright © 2018 Elsevier Ltd
ISSN
0959-6526
D.O.I.
10.1016/j.jclepro.2018.04.233
Publisher site
See Article on Publisher Site

Abstract

Among all transportation modes, how do people choose their strategy when commuting? To better understand travel behaviour in new era, we introduce the perspective of “Multi-Choice” to complement that of existing “Single-Choice” based on the random utility maximisation theory and focus on actual travel data from the Pronto! system in Seattle in 2015, to test such a theory as well as other geographical and demographical data. By using mixed multiple regression, we find that at the peak of weekday use, the accessibility of other transportation modes (quantified by their density of infrastructure) could affect the departure flow of the Pronto! stations around them (within a 0.5 km buffer), but in a different trend in terms of multi-choice process. Besides those, we also find that the density of the points of interest around the station could positively affect departure flows on weekends, while the traffic-related factors did not. The current study broadens the traditional perspective of travel demand models by introducing a multi-choice option, and testing it against actual mode choices in people's daily behaviour using shared-bicycle data from Pronto!, Seattle.

Journal

Journal of Cleaner ProductionElsevier

Published: Sep 1, 2018

References

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