A Quasi-experimental Estimate of the Impact of P2P Transportation Platforms on Urban Consumer Patterns
Zhe Zhang (Carnegie Mellon University);Beibei Li (Carnegie Mellon University)
Abstract
With the pervasiveness of mobile technology and location-based computing, new forms of smart urban transportation, such as Uber & Lyft, peer-to-peer 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 take advantage of a novel and individually-detailed dataset and use econometric and casual analysis methodsto examine how such peer-to-peer car sharing services may affect consumer mobility and consumption patterns.
