Capacity adjustment in a service facility with reactive customers and delays: simulation and experimental analysis

In this paper, we apply system dynamics to model a queuing system wherein the manager of a service facility adjusts capacity based on his perception of the queue size; while potential and current customers react to the managers' decisions. Current customers update their perception based on their own experience and decide whether to remain patronizing the facility, whereas potential customers estimate their expected waiting time through word of mouth and decide whether to join the facility or not. We simulate the model and analyze the evolution of the backlog of work and the available service capacity. Based on this analysis we propose two alternative decision rules to maximize the manager's cumulative profits. Then, we illustrate how we have developed an experiment to collect information about the way human subjects taking on the role of a manager in a lab environment face a situation in which they must adjust the capacity of a service facility