Paper ID
2391
Paper Type
full
Description
We investigate how the digital business model of on-demand ridesharing platforms like Uber and Lyft interacts with an established, centralized public mass transit system. Our study uses data on ridesharing, taxi, shared bike, and subway usage in New York City and exploits a series of exogenous shocks to the system – the closing of subway stations – to isolate substitution effects. We find that the average shock is associated with a 2.8 - 3.3% increase in the use of ridesharing, which translates into 5.5 additional Uber rides and 1.5 additional Lyft rides per taxi zone and four-hour period. Although this suggests that on-demand ridesharing acts as infrastructure that helps smooth unexpected transportation supply and demand surges, the estimated effect is small relative to the average number of subway rides displaced. Our results indicate that the flexibility inherent in ridesharing’s crowd-based business model could be further exploited to support capital-intensive transit systems in the future.
Recommended Citation
Hoffmann Pham, Katherine; Ipeirotis, Panos; and Sundararajan, Arun, "Ridesharing and the Use of Public Transportation" (2019). ICIS 2019 Proceedings. 8.
https://aisel.aisnet.org/icis2019/business_models/business_models/8
Ridesharing and the Use of Public Transportation
We investigate how the digital business model of on-demand ridesharing platforms like Uber and Lyft interacts with an established, centralized public mass transit system. Our study uses data on ridesharing, taxi, shared bike, and subway usage in New York City and exploits a series of exogenous shocks to the system – the closing of subway stations – to isolate substitution effects. We find that the average shock is associated with a 2.8 - 3.3% increase in the use of ridesharing, which translates into 5.5 additional Uber rides and 1.5 additional Lyft rides per taxi zone and four-hour period. Although this suggests that on-demand ridesharing acts as infrastructure that helps smooth unexpected transportation supply and demand surges, the estimated effect is small relative to the average number of subway rides displaced. Our results indicate that the flexibility inherent in ridesharing’s crowd-based business model could be further exploited to support capital-intensive transit systems in the future.