Available online at: https://trid.trb.org/view/1572893
Qian, Xiaodong and Miguel Jaller (2019) Station-Level Analysis for Bikeshare Activity in Disadvantaged Communities. Transportation Research Board 98th Annual Meeting
Bikeshare systems are rapidly becoming more prevalent around the world. This popularity means that an increasing number of people can enjoy the convenience of cycling and the associated physical health benefits without actually owning a bike (or having access to their own bikes). However, low-income populations and people of color are not highly represented users of bikeshares. Currently, there is limited research to estimate bikeshare ridership in these communities. This research fills that gap by analyzing current utilization rates of bikeshare systems among disadvantaged populations. This study develops a Negative Binomial regression model to estimate bikeshare ridership in disadvantaged areas using data from Chicago’s bikeshare system (Divvy). The results show that bikeshare stations in disadvantaged communities have approximately 2,380 annual trips less than in other areas on average (an approximate 32% reduction from the average generated trips in all stations). Among factors influencing bikeshare trips, employment rate has the highest positive marginal effect. Additionally, this research analyzes the bikeshare trip utilization between annual member and 24-hour pass users in disadvantaged areas. The proportion of trips by subscribers is significantly lower in disadvantaged communities than in other areas. Interestingly, residents in disadvantaged communities tend to make longer bikeshare trips once they are already annual members.
Key words: Bicycling, low income groups, regression analysis, vehicle sharing