Dynamic appointment scheduling with wait-dependent abandonment

This paper provides a formal framework for optimal dynamic appointment scheduling with wait-dependent abandonment in order to reduce the blind wait (wait without queue information) and useless wait (wait but abandon). A discrete-time Markov decision process model is proposed to best balance server utility and experiences of customers waiting for admission. The properties of the optimal policy are investigated both theoretically and numerically. Efficient policies are implemented, the benefit from instituting the appointment system is checked numerically and managerial insights derived. In particular, appointment scheduling is shown to significantly reduce blind and useless wait without sacrificing the server utility when the system is overloaded with long service time and customers are more sensitive to blind wait than known wait (wait with a target). A revenue-oriented system tends to inform earlier appointment times and hence higher effective admission rate than a system taking into account customer experience of wait.