Understanding Driver Agency in RideSharing
Iyadunni Adenuga, Benjamin Hanrahan
TL;DR
This paper investigates driver agency in ridesharing, arguing that opaque algorithmic management undermines drivers' perceived control. It adopts Value-Sensitive Design and an empirical qualitative study (7 driver interviews) to elicit concrete design suggestions. The authors propose Co-opRide, a driver-centered mobile app featuring profile-based ride preferences, a community and complaints system, transparent ratings, and a Bayesian Belief Network–driven matching engine with probability-based incentives and a Total Cost of Ownership pricing framework. The work demonstrates how explicit control, transparency, and peer support can enhance trust, satisfaction, and productivity for drivers, and outlines future work to quantify impact on drivers, riders, and platform operators.
Abstract
Agency is an important human characteristic that users of automated complex technologies are usually denied. This affects the user's experience leading to decreased satisfaction and productivity. In this paper, we consider the ridesharing context and interviewed 7 drivers to understand the controls that would improve the agency they feel. The results show that they desire transparency, community and an effective ability to seek redress.