EXPRESS: Incentivizing flexible workers in the gig economy: The Case of ride-hailing

On-demand platforms like ride-sharing services rely heavily on economic incentives to attract, retain, and manage independent workers who have significant discretion over whether and where to work. Using an analytically tractable spatial model, we explore the impact of different pricing and commission strategies on customer demand, driver entry and retention, and their location choices. Our model yields several unique results and actionable insights. We find that flexible commission policies are more effective than fixed commission policies in allocating drivers efficiently across locations, reducing bottlenecks, and improving driver retention. We also show that commission-based interventions are more effective than price interventions in responding to labor market changes, as they directly affect driver incentives without distorting customer demand. Finally, if fairness-sensitive customers are prevalent in the market, then fixed pricing, combined with flexible commissions, becomes the optimal rule. Simulations based on actual ride patterns from New York City and Los Angeles confirm our insights.