Investigating the Relocation Behavior of Ride-sourcing Drivers

Abstract

In the business model of ride-sourcing platforms, drivers are individual service suppliers offering door-todoor transport services to riders. Drivers freely adopt their own relocation strategies including waiting, cruising freely, or following the platform recommendations. These decisions can substantially impact the balance between supply and demand, and consequently affect system performance such as match rate, empty mileage, and traffic congestion. To this end, we conducted a stated choice experiment to investigate the searching behavior of ride-sourcing drivers in the current system setting and examine novel policies. A unique dataset of 576 ride-sourcing drivers working in the US was collected and a choice modeling approach was used. The results suggest that ride-sourcing drivers’ relocation strategies significantly vary between different groups of drivers depending on their employment status, working experience, daily operations, among others. We discuss the implications of our findings for various platform policies on realtime information sharing and platform repositioning guidance.