A Quasi-experimental Estimate of the Impact of P2P Transportation Platforms on Urban Consumer Patterns

Zhe Zhang, Beibei Li

Abstract: With the pervasiveness of mobile technology and location-based computing, new forms of smart urban transportation, such as Uber & Lyft, have become increasingly popular. These new forms of urban infrastructure can influence individuals' movement frictions and patterns, in turn influencing local consumption patterns and the economic performance of local businesses. To gain insights about future impact of urban transportation changes, in this paper, we utilize a novel dataset and econometric analysis methods to present a quasi-experimental examination of how the emerging growth of peer-to-peer car sharing services may have affected local consumer mobility and consumption patterns.