We present a novel approach to understanding distance as a barrier to cycling and its use as a dependent variable in multinomial logistic regression. In doing so, this study explores distances in relation to spatially and relevant human factors such as gender and propensity to cycle among college students. College students (N = 949) participated in a health survey and stated possible predictors of cycling based on their cycle usage and preferences in the previous 30 days. While utilizing GIS in a bicycle-friendly network, we created geo-statistical GIS-groupings and performed multinomial logistic regression analysis. We examined college students to discover how their demographic and personal characteristics may mediate the deterrent properties of distance when considered as a dependent variable in cycling to a college campus. Age and propensity for cycling for transportation mediate the negative effect of distance on the likelihood of cycling. The findings also suggest that infrastructure improvements could lessen the impact of distance as a barrier to cycling and increase the likelihood of cycling for commuting.
NOTICE: This is the author’s version of a work that was accepted for publication in Applied Geography. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Applied Geography, vol. 60, June 2015. doi: 10.1016/j.apgeog.2015.03.009