Optimal Contract Design for Ride-Sourcing Services Under Dual Sourcing

To cope with the uncertainty of labor supply from freelance/self-scheduling drivers, some ride-sourcing platforms recruit contractual drivers, who are paid a fixed salary for prespecified work schedules. This paper develops an aggregate modeling framework to examine the practicability of such a dual-sourcing strategy. We investigate the optimal contract design of dual sourcing under demand uncertainty, varying price sensitivity of freelancers, and heterogeneity in drivers' risk attitude. Our results uncover the conditions under which dual sourcing benefits both the platform and drivers. We show that the platform's staffing and pricing decisions are most responsive to freelancers' price sensitivity. When the price sensitivity stays adequately low, both the platform and drivers can be better off under dual sourcing compared to the self-scheduling counterpart. On the contrary, with moderate price sensitivity, freelancers will be made worse off by dual sourcing. The dual-sourcing contracts are most effective in markets where drivers are risk-averse