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The purpose of this research is to identify correlates of bike stationactivity for Nice Ride Minnesota, a bike share system in Minneapolis - St. PaulMetropolitan Area in Minnesota. We obtained the number of trips to and fromeach of the 116 bike share stations operating in 2011 from Nice Ride Minnesota.Data for independent variables included in models come from a variety ofsources; including the 2010 US Census, the Metropolitan Council, a regionalplanning agency, and the cities of Minneapolis and St. Paul. We use log-linearand negative binomial regression models to evaluate the marginal effects ofthese factors on average daily station trips. Our models have high goodness offit, and each of 13 independent variables is significant at the 10% level orhigher. The number of trips at Nice Ride stations is associated withneighborhood socio demographics (i.e., age and race), proximity to the centralbusiness district, proximity to water, accessibility to trails, distance toother bike share stations, and measures of economic activity. Analysts can usethese results to optimize bike share operations, locate new stations, andevaluate the potential of new bike share programs.

Modeling Bike Share Station Activity: Effects of Nearby Businesses and Jobs on Trips to and from Stations