- sennareese7
- Jun 26
- 5 min read
Chicago's summer heat brings more than just beach weather, it drives the peak months of Divvy bike usage, Chicago’s city-owned bike sharing system. In July 2024 alone there were over 700,000 Divvy bike rides. But behind these impressive numbers lies a more complex story about who has access to the city's 700+ bike stations.
When cross-analyzing demographic data with current stations grouped by neighborhoods, insights of Divvy station placements point to key patterns emerging. Specifically, information on racial composition, education, income, and homeownership was retrieved from census data for the years 2013 to 2020, grouped by the 77 neighborhoods in Chicago.
Instead of wrestling with spreadsheets and siloed datasets, BrightAgent helps me focus on the enlightening part: uncovering the stories and patterns that shapes Chicago. Brighthive helps communities and myself see the full picture - enabling smarter, more equitable decisions about public resources like bike share systems.
Key trends unveiled from current Divvy station placement
BrightAgent uncovers key trends from current Divvy station placement such as correlations with salient demographic factors and bike placement. One of the most prominent trends is that affluent, white, and highly educated neighborhoods are key drivers of current station placement, all with strong positive correlations. Specifically, the strongest correlation is between median income and station count (r = 0.659), suggesting that higher-income neighborhoods generally have better bike share infrastructure access. Education follows suit (r = 0.611), neighborhoods with higher college graduation rates are linked to having more stations. Finally, race plays a role too, with areas having higher white populations correlating with more stations (r = 0.567). Of course, other factors beyond these demographic values play a role in bike station placement such as proximity to other transportation services and centrality of neighborhoods but the three factors mentioned above appear key when analyzing frequency of Divvy stations.
Another interesting finding is that home ownership rates do not seem to play a role in where Divvy stations are placed. There’s almost no relationship between the percentage of owner-occupied homes and the number of stations in a neighborhood (r = 0.024). This suggests that the bike system does not focus on serving homeowners more than renters, or vice versa.
Delving further, the contrast is striking when you look at the extremes. 6 neighborhoods were identified as high-station neighborhoods (those with 30+ stations), with the Loop having the highest count with 69 stations. This shouldn’t come as a surprise since the Loop is the second largest central business district in the United States outside of Midtown Manhattan, employing over 400,000 workers. However, besides the Loop, there are clear disparities between neighborhoods with high and low station count. Namely, high-station communities have an average income of $104,763, where 79.1% of residents have BA degrees, and 65.1% of the population is white.
Meanwhile, low-station communities, those with 10 or fewer stations, paint a different picture. These predominantly minority neighborhoods average $46,029 in income, with 35% holding BA degrees and have 23.4% white residents. These insights demonstrate key differences between placements of these bike stations as seen on the charts
below.
This raises some big questions: Is Divvy truly serving all of Chicago? What gets in the way of including more diverse communities? While Divvy’s mission is to promote transportation equity, financial realities and growth strategies may sometimes pull in a different direction.
Current station trends could be having a push and pull effect: stations are chosen to be placed in more affluent, educated, white neighborhoods and also more stations are attracting these demographics. Understanding why these trends have emerged requires delving into where stations have expanded to over time.
Delving into insights from planned stations over time
Examining the temporal trends in planned stations reveals further insights. In the first 3 years of the Divvy program (2013-2015), new stations were more likely to be placed in affluent, white, and highly educated areas, with the communities with planned stations having higher averages for these variables, as seen on the table below. Specifically, communities selected for bike station expansion had a higher median income of $23,755 than those that weren't selected. See the chart below for the other demographic differences. This lends to the idea that the first wave of bike station additions could have been chosen to serve more privileged neighborhoods.
But the story doesn’t end there. In 2016, these differences became negative, potentially indicating an effort to address existing gaps in coverage. After 2016, these differences fluctuated between positive and negative, suggesting that factors beyond neighborhood demographics played an increasingly important role in station planning.
In fact, according to a study on redistribution of Divvy stations, the 2016 expansion specifically targeted disadvantaged neighborhoods. Chicago also began using more participatory planning methods, including online platforms where residents could suggest station locations. While not all suggestions were implemented, there was a noticeable effort to incorporate public input, especially from neighborhoods that previously had little or no Divvy presence. This participatory approach helped planners identify and fill gaps in disadvantaged neighborhoods. The changing correlation between planned stations starting in 2016 seems proof of these direct efforts to target placement in disadvantaged neighborhoods. Additionally, there is a discrepancy between the number of planned stations and current stations with 192 planned stations between 2013 and 2019 and over 700 current stations today.
While Divvy has become integral to many people’s daily life in affluent areas, several communities remain underserved. As the city continues to grow and change, understanding these patterns is key to making bike infrastructure more equitable and accessible for everyone. As Chicago evolves, the challenge isn't just expanding the system but also ensuring and emphasizing that mobility equity and accessibility keeps pace with growth. Biking should be for all and looking at the data behind bike placement is the first step towards this goal. The data shows progress, but also highlights how much more can be made.
Key Takeaways:
Divvy station placement has historically favored affluent, white, and highly educated neighborhoods, but recent expansions have aimed to address these gaps.
BrightAgent made it easy to uncover these trends by connecting and analyzing data from multiple sources, letting me focus on the “why” and “what’s next.”
Delving into the data unveiled that both the challenges and the possibilities for truly equitable bike infrastructure for Chicago is deeply insightful and rich.
The big question: Who are we really serving, and how can we do better?
Written by Senna Reese - Go-To-Market Content Associate with a keen interest in how data can shape our communities. I am fascinated by the intersection of data analysis and social impact, and am always looking for new ways to apply data-driven insights to real-world insights.
Resources:
The data analysis in this article was created with help of BrightAgent using historical DIVVY Bike Station and census data accessed through the Chicago Data Portal
https://chicagocrusader.com/new-study-reveals-chicago-loop-tops-u-s-downtowns-by-most-value-metrics/
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