We consider a multi-class multi-server queueing system, in which customers of different types have heterogenous preferences over the many servers available. A service provider designs a menu of service classes that balances maximizing the customers’ average service reward and minimizing customers’ average waiting time. Customers act as rational self-interested utility maximizing agents when choosing which service class to join. We study the problem under heavy traffic conditions.

We consider a first-come-first-serve single-server system in which heterogeneous customers. Customers are both payment and lead-time sensitive and are heterogeneous in both immediate service valuation and lead-time sensitivity. The service provider considers incentive-compatible price/lead-time menus based on the system congestion to maximize revenue. The optimal policy suggests the timing to offer a state-independent inflated lead-time option which may be easy to implement in practice.

Recent empirical observations find that the service time at the non-dedicated service provider is significantly prolonged compared with that at the dedicated service provider. This study models these empirical observations by developing stochastic models to assess the impact of the prolonged service time and other parameters (system workload and asymmetry level) on flexibility configurations. We obtain conditions characterizing the optimal flexibility design in the parameter space.