Technology Adoption, Digital Inequality and Worker Productivity: The Case of Mobile Hailing Apps

Jul 01 2015
  • Co-authored with Yanwen Wang and Ting Zhu.


The taxi industry has undergone dramatic changes in recent years with the introduction of mobile application based cab hailing systems. New mobile applications, such as UBER and Lyft, have changed the way the taxi industry works. Meantime in many countries and regions including New York City, Las Vegas, Canada and Germany are hot debates as to imposing or lifting bans on UBER and similar mobile hailing apps. Supporters argue that mobile hailing apps are welfare-enhancing, as they lead to more efficient customer-and-driver allocations and help increase taxi drivers' productivity. The oppositions hold viewpoints that mobile hailing apps, as a new technology, may create digital divide as well as digital inequality against low-skilled taxi drivers thus increasing social disparities.

In this paper we provide evidence to confront two arguments about (1) whether mobile hailing apps increase an average driver's productivity and (2) whether the use of mobile hailing apps affects productivity disparities among taxi drivers. To investigate the two questions we take leverage of a natural experiment setting in a metro city where mobile hailing apps were regulated to be only adopted by the city's registered taxi drivers. We collected a 1TB data set on 6,000 taxi drivers' minute-by-minute trip geolocations before and after the introduction of two major cab hailing apps.

We build a productivity function and an unobserved mobile hailing app adoption decision separately for each taxi driver, and estimate with MCMC Bayesian method. We find that the adoption of mobile hailing apps has significantly increased drivers' productivity, although the advantage diminishes over time as more and more drivers adopt it. At the same time, the use of mobile hailing apps is found to have actually reduced the productivity gap between high and low-skilled taxi drivers. The pattern holds after controlling for observed and unobserved heterogeneity in the adoption decision of cab hailing apps. Our results are of great interest to public policy makers as to better evaluate the the impacts of mobile hailing services.

Keywords: Mobile Hailing Apps, Productivity, Productivity Disparity, Technology Adoption