Incentivizing áexible workers in the gig economy: The case of ride-hailing

Creating the right incentives for a áexible workforce lies at the heart of the gig economy. For most companies, a key question is how to best connect a limited number of independent workers in their platforms with service-seeking consumers through the right pricing and matching mechanisms. We focus on ride-hailing where drivers have signiÖcant discretion over where and when to work across di§erent locations. Building a spatial model, we study how a platform can create incentives for independent drivers via prices and commissions, and how such policies a§ect driversísearch behavior across a network of locations. Contrary to common perception, we Önd that the áexibility of the commissions, and not the áexibility of prices, plays a dominant role in resolving local demand and supply mismatch. This is because location based price hikes at the bottlenecks negatively distort the local demand and generally do a poor job in incentivizing drivers towards such locations. Adjusting the commissions, on the other hand, does not interfere with the local demand; creates better incentives for the drivers, and therefore is more suitable to mitigate the e§ects of bottlenecks. Simulations based on actual ride patterns from New York City and Los Angeles conÖrm our insights.