Ride-hailing platforms face the two important challenges: (i) there are spatial demand imbalances that require some repositioning (empty routing) of drivers; (ii) the control of supply is partially decentralized in that drivers strategically decide whether to join the network, and if so, whether, and where, to reposition when not serving riders. We study the following question for such ride-hailing networks: Under decentralized repositioning, how effective are driver wage policies in achieving the optimal centralized performance benchmark? 
We consider a stationary fluid model of a ride-hailing network in a game-theoretic framework with riders, drivers, and the platform. We show how the effectiveness of supply-side financial incentives under decentralized repositioning depends on (i) the network’s spatial (travel time) configuration, (ii) spatial driver wage flexibility, and (iii) the congestion-sensitivity of travel times.