Urban Wire What does bikeshare trip data reveal about connections across DC neighborhoods?
Robin Wang, Yipeng Su
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In an earlier analysis of Washington, DC’s Capital Bikeshare program, we found that bikeshare stations tend to be concentrated in whiter and more affluent neighborhoods, and placement and use generally follow the distribution of the city’s existing transportation infrastructure. Building on that analysis, we investigated whether bikesharing in DC results in a greater connection between economically and racially diverse neighborhoods.

With funding support from the Mastercard Center for Inclusive Growth, we looked at the starting and ending stations for all Capital Bikeshare trips within DC in 2017, using publicly available, anonymized trip data. We found that riders starting trips in downtown neighborhoods are more likely to travel to a wider range of destinations compared with riders starting in predominantly African American neighborhoods east of the Anacostia River, reflecting DC’s existing socioeconomic divides.

More importantly, bikeshare riders generally travel to neighborhoods that have similar demographics to where they start. These findings suggest that although the city is embracing innovative shared mobility tools, we can’t assume everyone will adopt the tool the same way or that these investments will connect people in the same way.

We hope a better understanding of travel patterns will provide decisionmakers and communities a clearer picture of DC’s interneighborhood connectivity and how the city’s disparities are changing.

Bikeshare connectivity reflects existing socioeconomic disparities in DC

Capital Bikeshare provides a relatively affordable, flexible, and healthy transportation option for short trips in DC. Bikesharing also enables DC residents to visit more areas of the city and to connect to neighborhoods with diverse demographic and economic characteristics.

To measure how well bikesharing helps riders travel between different parts of the city, we counted how many different neighborhood destinations each starting neighborhood generated and the number of different starting neighborhoods reflected in each receiving neighborhood. We call these simple measures of exposure to different neighborhoods “destination diversity” and “receiving diversity.” We use census tracts as the relevant “neighborhood” throughout our analysis. View our methodology here (PDF).

Perhaps not surprisingly, riders who start in downtown DC reach a much broader range of neighborhoods than riders starting in other parts of the city, and downtown DC receives riders from a much broader range of neighborhoods. As demonstrated in the maps below, the eight neighborhoods with the most diverse destinations in 2017 were clustered downtown. On average, trips from the most destination-diverse locations reached 100 other neighborhoods in DC, covering almost all neighborhoods with bikeshare stations in 2017. Overall, we found that destination-diverse neighborhoods are also highly likely to be receiving-diverse because of the nature of commuting trips.

The bottom eight neighborhoods with the fewest number of trip destinations were all in Wards 7 and 8, east of the Anacostia River. Riders starting in these neighborhoods, which are predominantly African American, used bikesharing to reach a much smaller number of DC neighborhoods. The Anacostia River may be a physical barrier that limits riders’ access to other parts of DC, and the less densely distributed bike stations could potentially discourage people from travelling to more places. On average, trips from the least destination-diverse locations reached only 12 other neighborhoods in 2017.

The same patterns also hold when we examine the top and bottom eight receiving-diverse neighborhoods in DC, confirming that neighborhoods downtown had much greater bikeshare connectivity with the rest of DC than neighborhoods east of the Anacostia River. The gap also exists between neighborhoods east of the Anacostia River and in other parts of DC.

As the bar chart below shows, “destination diversity” reflects existing patterns of disparities in DC. Neighborhoods with the least-diverse destinations are located east of the river and have predominantly nonwhite residents, a higher share of unemployed residents, and much lower income, a pattern that contrasts with the profile of the most connected neighborhoods.

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Bikeshare riders tend to travel to destinations with demographics similar to where they started

But a simple destination count is limited in measuring connections between neighborhoods, as it doesn’t account for the differences in the wide range of trip destinations. To understand how bikesharing connects neighborhoods with different socioeconomic backgrounds, we also created a weighted average profile of destination neighborhoods for each neighborhood with stations and compared where trips started and terminated, in terms of income level and racial composition. The weights are defined as the total number of trips to each destination neighborhood to reflect the popularity of each destination neighborhood.

The scatter plots below show the relationship between the relative income level and racial composition for each starting neighborhood and its weighted destination neighborhood. Each blue dot represents a neighborhood, and its size shows the number of trips per station in that neighborhood in 2017. Despite DC’s racial and economic variation across neighborhoods, we found that most neighborhoods are more connected by bikeshare to places and communities with similar socioeconomic characteristics.

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Neighborhoods with lower incomes and shares of white residents appear to travel to neighborhoods with higher incomes or more white residents, rather than the reverse. Some of these neighborhoods are located on DC’s northeast border with Maryland, but most are located on the east side of the Anacostia River or adjacent to the river on the west side.

Opportunities and challenges for bikeshare and future research

Capital Bikeshare’s potential to benefit all DC residents rests on expanding users’ access to a range of destinations, and thereby the jobs and services they can reach (PDF). Our analysis suggests that despite increased popularity of bikesharing in DC, most trips in the Capital Bikeshare system are between neighborhoods that share similar socioeconomic characteristics.

But because we didn’t have demographic information on riders and could not identify last-mile bike trips after a bus ride, Metro ride, or car ride, some trips may not originate from riders’ neighborhoods of residence. In such cases, the income and racial profiles of the neighborhoods where riders start their journeys may not represent the characteristics of where they live. Future bikeshare research will benefit from a more nuanced look at these issues.

Our research also suggests that publicly available and anonymized data on bikesharing patterns—in DC and elsewhere—could help planners, policymakers, and the public identify gaps and challenges in a bikesharing program and design changes that maximize bikesharing’s potential to advance equity and inclusion.

Understanding how bikesharing contributes to inclusive and thriving communities in DC (PDF) also means looking at how the service could promote commercial activities through improved accessibility. For example, researchers from New York University’s Center for Urban Science and Progress analyzed anonymized, aggregated financial transaction data (PDF) to understand the effect of bikesharing on local businesses in New York City and Jersey City. They found spending increased in food-related businesses near bikesharing stations, calling for better understanding of the role of bikesharing in supporting local business activities. Similar methods could also be applied to research in other cities, with a focus on the potential of bikesharing to support community-based economic development in the neighborhoods that need it most.

Since introducing Capital Bikeshare, DC has expanded options for shared transportation in the city, including dockless bikes and electric scooters that aren’t tethered to stations. Early research using real-time data from operators found that electric scooters in DC had higher uptake than Capital Bikeshare in Ward 8 and among African American residents. More research could be done on quantifying the benefits from these innovative mobility tools.

As DC and other cities continue to experiment with a range of shared transportation options, filling these research and knowledge gaps can help them ensure that new mobility platforms are truly shared by all.


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Research Areas Neighborhoods, cities, and metros
Tags Racial and ethnic disparities Transportation Income and wealth distribution Racial wealth gap
Policy Centers Metropolitan Housing and Communities Policy Center