Daily Data: How to Increase Bike-Share Ridership at No Additional Cost
- February 20, 2015
- CBR - Behavioral Science
Bike-sharing programs in cities such as Paris, Beijing, and Chicago encourage commuters to use public transportation by supplying bikes they can ride to catch connections at other stations, or to simply get closer to their final destinations. But the optimal design for attracting users remains elusive, as there’s little data on how variables such as bike availability and station location affect a commuter’s decision to use the service.
New research from INSEAD and Chicago Booth sheds light on how the design of a bike-sharing system shapes ridership. The working paper, by Ashish Kabra and Karan Girotra of INSEAD, and Elena Belavina of Chicago Booth, quantifies how shorter distances to stations and more bike availability significantly increase the number of users.
Bike-sharing systems typically involve docking stations set up at public transportation depots and popular destinations, such as universities and large office complexes. A typical user might check out a bike at the end of a subway or train ride, and check it in shortly afterwards, when he reaches a hub for a connection or a dock nearer his destination.
The researchers spent four months observing the number of trips that started in Paris’ 349 bike-sharing stations in two-minute intervals. The work gave them 22 million such observations, or about 2.5 million bike trips—a far larger database than typically used in structural demand models.
The researchers estimate that a 10 percent reduction in travel distance to the bike-share stations can increase system use by 6.7 percent. A 10 percent increase in bike availability can increase system use nearly 12 percent, according to the study. They demonstrate that the bike-sharing program in central Paris would have 29.41 percent more ridership, without spending more money on bikes or docking points, if its station network design had incorporated these estimates of commuter preferences.
The researchers note that their estimated effects of accessibility and distance on consumer utility likely apply in contexts beyond transportation, such as retail stores, banks and other consumer services.
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