Gig or Employee? Platform's Joint Staffing and Pricing Decisions Under Hybrid‐Staffing Mode

ABSTRACT In the rapidly evolving landscape of on‐demand services, platforms are increasingly adopting a hybrid‐staffing mode that combines full‐time employees with part‐time gig workers. This approach leverages the stability of full‐time employees and the flexibility of gig workers, enabling platforms to efficiently meet fluctuating consumer demands. To identify optimal staffing and pricing strategies, we develop a model analyzing these joint decisions. Our findings highlight several key insights. First, the platform's staffing choice is influenced by the salary cost of employees and the labor pool size of gig workers. When both factors are moderate, a hybrid‐staffing mode is optimal. Additionally, as the frequency and level of demand surge increase, the platform is more inclined to adopt a hybrid‐staffing approach. Second, within the hybrid‐staffing framework, gig workers can fulfill multiple roles. They not only act as supplementary resources during peak hours but also maintain operational flexibility in both high‐ and low‐demand states in some cases. This dual role necessitates adaptive staffing and pricing strategies, which may exhibit non‐monotonic patterns in response to market changes. Third, the platform consistently benefits from a hybrid‐staffing mode, achieving higher profit compared to a single‐staffing mode. Moreover, this mode enhances labor and consumer welfare, consistently outperforming the gig‐only approach. Our study offers valuable insights for platforms to optimize hybrid staffing and pricing strategies, emphasizing the impact on stakeholder welfare within the ecosystem.