Understanding Factors Influencing Small to Mid-City Bike Share Ridership: A Direct Ridership Analysis

Bike share systems are commonly found in large cities thus research has focused on large cities. Little research has focused on bike share riders in small to mid-size cities. This study quantifies the factors affecting bike sharing and develops a direct ridership model (DRM) to predict monthly station-level bike share ridership in small to mid-size cities. A DRM is used to estimate how station-level bike sharing ridership correlates with demographics and land-use near bike share stations. The model is estimated using data from small cities and finds that bike share ridership is influenced the most by nearby attractions, such as parks. The results suggest that bike share riders in small cities ride for recreational purposes, rather than avoiding congestion along their commute. The developed DRM is better suited to predict ridership and to identify ideal locations for bike share system expansions in small to mid-size cities.