Relationship between Bike-sharing and Ride-sharing Platform

Abstract

App-based bike sharing platforms are quickly reshaping the landscape of urban transportation dynamics. In this study, I investigate in which direction does the bike-sharing platform affect the demand for ride-sharing platform, through the lenses of platform interaction. To precisely measure the effect, I exploit spatiotemporally staggered expansions of Citi Bike, the largest bike-sharing mobility in New York City, as a natural experiment design and examine the treatment effect on ride-sharing platforms (i.e., Uber and Lyft) and Yellow taxi demand in NYC all together. The result of geographically nearest neighbor matching, a novel identification strategy I suggest, also highlights my findings, along with 0.38 billion individual trip records. This research contributes to the research stream of sharing economy in IS. To my knowledge, this study is one of the first attempts to observe the interaction between App-based sharing platforms. Unquestionably, the importance of understanding how people connect the multiple sharing mobilities has been growing ever than before. I assert this study lays the foundation stone of research regarding sharing-to-sharing mobility.