Does self-interest enhance social welfare? Effectiveness of user-crowdsourced content in a mobile navigation app

Waze, a mobile navigation app, attracts user engagement by connecting its users with others while driving. In this context, user engagement crowdsources primary information, follow-up feedback, and collective confirmation. This paper addresses whether and how user contribution leads to the desirable effects on social welfare by relieving traffic jams around urban areas. Utilizing large-scale data on Waze users' behaviors and locations, we apply a spatial panel data approach to estimating the welfare value of user-crowdsourced content. Empirical results indicate that user contribution reduces the duration of traffic congestion in New York City. A welfare analysis estimates that user contribution saves 2.28% of annual total congestion cost per driver, $2,533, in the city. These social-welfare consequences are achieved by user contribution that is effective in saving social and economic costs and improving the mobility of urban transportation. We discuss implications for practice of mobile app design and policy on urban transportation.