Blending Capacity on a Rideshare Platform: Independent and Dedicated Drivers
研究网约车平台混合使用全职员工和独立司机的策略，发现工资适中、独立司机和乘客市场大时混合模式可行，且司机保留工资的不确定性促使平台雇佣更多全职司机并提高基础价格。
A rideshare platform acts as an aggregator that connects riders with ride providers (drivers). The drivers are independent workers who share a part of their revenue with the principal, who owns the platform. While drivers have flexible schedules, the fairness of labor contracts and control exercised by the principal have come into question lately. Suggested options include treating the drivers as employees and/or safeguarding a minimum income for them. We study a rideshare platform with blended driver capacity: full time employees with a fixed wage rate, and independent drivers who are paid a share of revenue. We examine a scenario where the principal establishes the number of employee drivers, revenue sharing, and a base price for the platform; and the independent drivers then determine whether to join the platform. We identify economic equilibrium for two different demand rationing strategies: preference for employee drivers, and equal opportunity for all drivers (driver‐agnostic). We find that a blended platform capacity becomes viable if the wage rate is moderate, pool of independent drivers is large, and the ride‐seeker market is large. We show that the unpredictability of driver's reservation value motivates the principal to hire more employee drivers and to increase the base price. Our result that a driver‐agnostic demand rationing causes fewer independent drivers to join the platform is somewhat counterintuitive and is explained by how revenue sharing affects demand rationing. We find that the ride seekers prefer preferential demand rationing over driver‐agnostic rationing.