The Impact of Peer-to-peer Ridesharing on Travel Mode: Empirical Study of Uber Effects on Travel Mode in Seattle
Abstract
This study explores the impact of peer-to-peer ridesharing on transportation dynamics, particularly in Seattle, using a difference-in-differences analysis. The aim is to provide insights for policymakers to anticipate future transportation demand by assessing commuters' mode choices in light of this new travel option. Previous research suggests that peer-to-peer ridesharing may decrease solo driving but its effect on public transit is unclear. This thesis aims to clarify these impacts while controlling for socio-demographic factors and examining variations across different demographic clusters through cluster analysis. Data from 143 census tracts in Seattle from 2010-2016 are analyzed using difference-in-differences analysis and dynamic coefficient robustness tests to measure the effects of peer-to-peer ridesharing. The census tracts are further divided into three clusters using K-means clustering to assess how the impact of peer-to-peer ridesharing varies across different demographic groups.
