If We Build It, Who Will Come? Comparing Sociodemographic Characteristics of Bike Share Subscribers, Cyclists, and Residents of New York City

Bike share programs are becoming increasingly popular across U.S. cities. However, their impact on persistent disparities in cycling by gender, race, and socioeconomic status remains understudied. We examined whether subscribers of Citi Bike, New York City’s (NYC) largest bike share program, reflect the sociodemographic profile of NYC cyclists. Using NYC Community Health Survey data, we described adult NYC residents of neighborhoods with ≥1 Citi Bike stations who rode a bicycle at least once a month. Citi Bike members were also described using first-time subscriber survey data. We compared the sociodemographic characteristics of these groups via a z-score with pooled variance. Approximately 2.2 million residents lived in 15 NYC neighborhoods with ≥1 Citi Bike station, and 449,000 (20.5%) reported cycling at least once a month in the past 12 months. Among first-time Citi Bike subscribers, 23,223 (11.5%) completed the survey. Compared with NYC cyclists, Citi Bike subscribers were more likely to be women, aged 24 to 45, White, college graduates, and from a household with an income >400% than the poverty level. Compared with the general population, cyclists were more likely to be White, male, and from a household with an income >400% than the poverty level. Race/ethnicity and socioeconomic status (not gender) disparities were larger among Citi Bike subscribers than NYC cyclists. With the emergence of cycling as an alternative transportation during the COVID-19 pandemic and the extension of bike share programs, this highlights the need for ongoing, systematic monitoring of bike share user socioeconomic characteristics to evaluate equitable use and access.

Impacts of Bike Sharing Program on Subway Ridership in New York City

Bike sharing programs have become increasingly popular in many cities. These services allow users to rent bikes for utilitarian and recreational trips in the urban area. Bike sharing has been considered a suitable mode to support the first- and last-mile connectivity problems of fixed-route transit services. Bike sharing has also emerged as a convenient mode for short-distance trips that previously would not have been possible without using public transit or personal bikes. This study investigated the impacts of Citi Bike—a bike sharing program—on the subway ridership in New York City (NYC), using Poisson-Gamma models. Bike sharing trips with destinations within a quarter-mile radius of a subway station were associated with subway ridership increase. A 10% increase in the number of bike trips increased the average daily subway ridership by 2.3%. However, a higher number of bike stations around a subway station decreased the subway ridership in instances where more bike trips originated (as opposed to ended) in the subway station’s service area. The presence of dedicated bike lanes and bike racks attracted more bike users and increased subway ridership. Findings from this study indicate that the development of bike-friendly infrastructure such as activities outlined in the recent NYC Department of Transport (DOT) “Green Wave” program can increase both bike sharing and subway ridership. In addition, policies and initiatives by transportation agencies to better integrate bike sharing programs with the transit system have the potential to increase the attractiveness of bike sharing programs and maximize the subway ridership.

Quantifying the Bicycle Share Gender Gap

In this paper we examine the gender split in 76,981,561 bicycle share trips made from 2014-2018 for three of the largest public bicycle share programs in the U.S.: Bluebikes (Boston), Citi Bike (New York), and Divvy Bikes (Chicago). Overall, women made only one-quarter of all bicycle share trips from 2014-2018. The proportion of trips made by women increased over time for Citi Bike from 22.6% in 2014 to 25.5% in 2018, but hovered steady around 25% for Bluebikes and Divvy Bikes. Across programs, the gender gap was wider for older bicycle share users.

Understanding the Relationships between Demand for Shared Ride Modes: Case Study using Open Data from New York City

The concept of shared travel, making trips with other users via a common vehicle, is far from novel. However, a changing technological climate has laid the tracks for new dynamically shared modes in the form of transportation network companies (TNCs), to substantially impact travel behavior. The current body of research on how these modal offerings impact the demand for existing shared modes (e.g., bikeshare, transit) is growing. However, a comprehensive investigation of the temporal evolution of the demand for TNCs and their relationship to other shared modes, is lacking. This research tackles this important limitation by analyzing ridership data for TNCs, taxi, subway, and Citi Bike in New York City using daily ridership data from January 2015 through June 2017. The primary objective was to understand the relationship between TNCs and other shared modal offerings while accounting for the influence of temporal trends and other exogenous factors. A dynamic linear modeling framework was formulated to accommodate time-dependent trends, periodicity, and time-varying exogenous factors on the demand for TNCs. As a preliminary work, the findings of this study reinforce the observed substitution relationship between taxis and TNCs. The results may also indicate a substitutional relationship between TNCs and Citi Bike, and a complementary relationship with subway, however these results still need to be explored further. With potentially impactful findings for planning and policymakers, the predictive model developed in the study can be used to carry out forecasting in support of short- and long-term operations and planning applications.