Abstract: Peer-to-peer ridesharing, as a new travel mode, could be a potential solution to two major transportation issues: congestion and air pollution by reducing inefficient driving and promoting public transit ridership. Uber, as one of the leader transport network company, launched in San Francisco in 2010 and expanded around the world. This new travel mode could affect transportation situation, however, its impact is still not clear. The results from this study are based on current research to test the impact of this new travel mode in Seattle through the difference-indifferences analysis. This thesis could help policymakers to forecast the future transportation demand by estimating the commuters of different commute mode choice within the effects of this new travel option on commuting. According to past studies, peer-to-peer ridesharing could reduce driving alone demand but its impact on public transit is not clear. This thesis analyzes the impacts of peer-to-peer ridesharing on driving alone and public transit to commuting controlling for socio-demographic factors. In addition, it studies the different impact of peer-to-peer ridesharing within the different sociodemographic factors through Cluster analysis. III This thesis collects 143 census tract data of Seattle from 2010-2016 as the study sample. Through the difference-in-differences analysis and the dynamic coefficient robustness test, this thesis measures the impacts of peer-to-peer ridesharing in Seattle. Then, this thesis divides 143 census tracts into three clusters through the K-mean Cluster analysis and studies the different impact of peer-to-peer ridesharing on commute mode across these clusters.
For more information, please visit: https://digital.lib.washington.edu/researchworks/handle/1773/43168
