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Open AccessArticle

Predicting Bicycle-on-Board Transit Choice in a University Environment

by 1,2,3,* and 4,5,6,7
1
College of Arts and Sciences, University of Michigan-Flint, Flint, MI 48502, USA
2
Michigan Institute for Data Science (MIDAS), The University of Michigan, Ann Arbor, MI 48108, USA
3
The Centre for Urban Design and Mental Health, London SW9 7QF, UK
4
Department of Geography & Environmental Studies, Ryerson University, Toronto, ON M5B 2K3, Canada
5
Graduate Programs in Environmental Applied Science & Management, Ryerson University, Toronto, ON M5B 2K3, Canada
6
Graduate Program in Spatial Analysis, Ryerson University, Toronto, ON M5B 2K3, Canada
7
Department of Geography, University at Buffalo, Buffalo, NY 14261, USA
*
Author to whom correspondence should be addressed.
Sustainability 2021, 13(2), 512; https://doi.org/10.3390/su13020512
Received: 13 December 2020 / Revised: 28 December 2020 / Accepted: 4 January 2021 / Published: 7 January 2021
(This article belongs to the Special Issue Landscape Planning for Sustainability)
Bicycles-on-board (BoB) transit is a popular travel demand management (TDM) tool across many U.S. cities and universities, yet research on this mode within a university environment remains minimal. The purpose of this research is to investigate how personal and neighborhood factors influence this travel choice in a university setting. Relying on attitudinal data from a stated preference survey, this study examined the effect of personal characteristics and seven key neighborhood conditions on the willingness to utilize BoB for the “first mile” of the journey to campus. The study used exploratory spatial data analysis (ESDA), a discrete choice modeling framework, and geovisualizations to understand the likelihood of choosing this mode among a university population in Flint, Michigan, USA. The results revealed that the majority of constituents were not interested in BoB, aside from a cluster near the commercial business district. Also of note was that long commutes, and reduced access to parks and bicycle facilities dissuaded people from choosing this mode. Surprisingly, a neighborhood’s walkability or bikeability had no effect on respondent’s interest in using BoB. Lastly, the geovisualizations showcased where localized interventions may effectively increase this mode choice in the future. View Full-Text
Keywords: intermodal transportation; cycle-transit users; bicycling; mass-transit; TDM; geographically weighted logistic regression; discrete choice model; GIS intermodal transportation; cycle-transit users; bicycling; mass-transit; TDM; geographically weighted logistic regression; discrete choice model; GIS
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MDPI and ACS Style

Rybarczyk, G.; Shaker, R.R. Predicting Bicycle-on-Board Transit Choice in a University Environment. Sustainability 2021, 13, 512. https://doi.org/10.3390/su13020512

AMA Style

Rybarczyk G, Shaker RR. Predicting Bicycle-on-Board Transit Choice in a University Environment. Sustainability. 2021; 13(2):512. https://doi.org/10.3390/su13020512

Chicago/Turabian Style

Rybarczyk, Greg; Shaker, Richard R. 2021. "Predicting Bicycle-on-Board Transit Choice in a University Environment" Sustainability 13, no. 2: 512. https://doi.org/10.3390/su13020512

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Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

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