The gender productivity gap in the ride-hailing market

Abstract

The gender productivity gap in the ride-hailing market has not been well studied due to the difficulty in obtaining driver demographics and trajectory data. To address this gap, we use six-day long trajectory data of around 20,000 ride-hailing drivers from China, infer their gender from their names, and estimate gender disparity in productivity (daily earnings or passenger-carrying distance per unit working time) using the panel fixed effect regression models. The results indicate that the gender gap in productivity of ride-hailing drivers does exist, but it disappears if we compare male and female drivers with the same driving behavior (i.e., same driving speed), average trip lengths, and vehicle fuel type. The Blinder-Oaxaca decomposition shows that most productivity gap is driven by average driving speed and average trip length. These results suggest that although the productivity gap exists in the ride-hailing market, the reasons behind the gap are not worrisome for ride-hailing companies. Thus, these companies can encourage the participation of female drivers without compromising on operational performance, which could help sustain exclusive services like matching female riders with only female drivers and increase demand by making a female-centric safe brand.