Factors influencing bike share membership: An analysis of Melbourne and Brisbane. (January 2015) - Fishman, Elliot; Washington, Simon; Haworth, Narelle; Watson, Angela
Highlights: Bike share programs have grown rapidly in recent years. Australian bike share programs have lower usage levels than other countries. Online survey used to develop a logistic regression model to predict membership. Riding frequency, age, proximity to docking station predict membership. Riding convenience levels and higher income increase odds of membership. Abstract: The number of bike share programs has increased rapidly in recent years and there are currently over 700 programs in operation globally. Australia's two bike share programs have been in operation since 2010 and have significantly lower usage rates compared to Europe, North America and China. This study sets out to understand and quantify the factors influencing bike share membership in Australia's two bike share programs located in Melbourne and Brisbane. An online survey was administered to members of both programs as well as a group with no known association with bike share. A logistic regression model revealed several significant predictors of membership including reactions to mandatory helmet legislation, riding activity over the previous month, and the degree to which convenience motivated private bike riding. In addition, respondents aged 18–34 and having docking station within 250 m of their workplace were found to be statistically significant predictors of bike share membership. Finally, those with relatively high incomes increased the odds of membership. These results provide insight as to the relative influence of various factors impacting on bike share membership in Australia. The findings may assist bike share operators to maximize membership potential and help achieve the primary goal of bike share – to increase the sustainability of the transport system.