The Dual Effects of Team Contest Design on On-Demand Service Work Schedules

Abstract

Emerging on-demand service platforms (OSPs) have recently embraced teamwork as a strategy for stimulating workers' productivity and mediating temporal supply and demand imbalances. This research investigates the team contest scheme design problem considering work schedules.
Introducing teams on OSPs creates a hierarchical single-leader multi-follower game. The leader (platform) establishes rewards and intra-team revenue-sharing rules for distributing workers' payoffs. Each follower (team) competes with others by coordinating the schedules of its team members to maximize the total expected utility. The concurrence of inter-team competition and intra-team coordination causes dual effects, which are captured by an equilibrium analysis of the followers’ game. To align the platform's interest with workers' heterogeneous working-time preferences, we propose a profit-maximizing contest scheme consisting of a winner's reward and time-varying payments. A novel algorithm that combines Bayesian optimization, duality, and a penalty method solves the optimal scheme in the non-convex equilibrium-constrained problem. Our results indicate that teamwork is a useful strategy with limitations. Under the proposed scheme, team contest always benefits workers. Intra-team coordination helps teams strategically mitigate the negative externalities caused by over-competition among workers. For the platform, the optimal scheme can direct teams' schedules toward more profitable market equilibria when workers have inaccurate perceptions of the market.

Keywords: On-demand service platforms, Team competition, Payment scheme design, Quasi-variational inequality