Modeling Bike Share Station Activity: Effects of Nearby Businesses and Jobs on Trips to and from Stations
Publication: Journal of Urban Planning and Development
Volume 142, Issue 1
Abstract
The purpose of this research is to identify correlates of bike station activity for Nice Ride Minnesota, a bike share system in the Minneapolis–St. Paul Metropolitan Area in Minnesota. The number of trips to and from each of the 116 bike share stations operating in 2011 was obtained from Nice Ride Minnesota. Data for independent variables included in the proposed models come from a variety of sources, including the 2010 U.S. Census; the Metropolitan Council, a regional planning agency; and the Cities of Minneapolis and St. Paul. Log-linear and negative binomial regression models are used to evaluate the marginal effects of these factors on average daily station trips. The models have high goodness of fit, and each of 13 independent variables is significant at the 10% level or higher. The number of trips at Nice Ride stations is associated with neighborhood sociodemographics (i.e., age and race), proximity to the central business district, proximity to water, accessibility to trails, distance to other bike share stations, and measures of economic activity. Analysts can use these results to optimize bike share operations, locate new stations, and evaluate the potential of new bike share programs.
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Acknowledgments
The authors greatly appreciate the Bikes Belong Foundation for its financial support, and Mitch Vars of Nice Ride Minnesota, Tony Hull of Transit for Livable Communities, and Mary Ann Murphy of the University of Southern California for their help and support.
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Information & Authors
Information
Published In
Journal of Urban Planning and Development
Volume 142 • Issue 1 • March 2016
Copyright
© 2015 American Society of Civil Engineers.
History
Received: Jun 12, 2014
Accepted: Dec 5, 2014
Published online: Feb 9, 2015
Discussion open until: Jul 9, 2015
Published in print: Mar 1, 2016
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