Most queueing models for service system design assume the servers work at fixed (possibly heterogeneous) rates. However, real-life service systems are staffed by people, and people may change their service speed in response to incentives such as compensation. In this project we employee game theory to model the speed choice of servers in large systems. Based on the servers’ strategic behavior, we optimize the service system performance.
This research has both practical and theoretical impacts. Practically, most call centers use flat hourly salary. Managers need an effective payment scheme to incentivize the agents to provide fast service with good quality. With performance based payment, the service speed could be different, so is the staffing level. The related questions are investigated in this project and the results can be applied. Theoretically, we employee game theory and approximation techniques to model the server behavior in large systems. We show that in different conditions, different regimes, especially a mixed regime which is not work-conserving, could emerge under a first-best policy.