We study advance selling and upgrading in a priority queue setting that emerges in the amusement park industry. Waiting sensitive customers who purchase cheaper advance tickets may suffer from demand uncertainty when consuming the service. Customers can purchase regular tickets in advance and upgrade to fast-track tickets on-site. We find if there are some offline customers who cannot purchase in advance, then allowing upgrading generates more revenue for the service provider.

We consider a system where customers have to go through two service stages. We study the fully-observable model, in which queue-length information of both queues is available at arrival: customers observe the state of the entire system and decide whether to join or not. To learn the value of information we compare the fully observable system with the partially observable system in which, instead of observing the full system state, customers observe queue length only at arrival to each queue.

We study a queueing system with returns where at each service completion epoch, the decision maker can choose to reduce the probability of return for the departing customer at a cost that is convex increasing in the amount of reduction in the return probability. We characterize the structure of optimal long-run average and bias-optimal transient control policies for associated fluid control problems. Our results provide insights on the design of post-service intervention programs.