Empirical studies on the impact of booking status on customers’ choice behavior in online appointment systems

We consider customers' choice behavior in online appointment systems. In three online experiments, we investigate whether and to what extent customers are impacted by the number of available slots by asking subjects to choose between two providers of several service areas with different occupancy rates. In line with previous literature, we find some evidence that customers infer quality from a utilized system compared to an empty schedule; that is, any demand (very few booked appointments) is preferred to no demand (empty booking schedule). A too-small offer set, in contrast, shows congestion and leads to an opposed scarcity effect because customers expect the provider to be in a rush, the waiting room to be crowded, and further value flexibility in the choice of the appointment time. We contribute to the literature by analyzing the interaction of the two nonlinear effects and further find that the presence of the quality-inference effect depends on the type of service. For a standardized service, we find no evidence of the quality-inference effect. For nonstandardized services, however, we find an inverse U-shaped preference in the number of offered slots, showing that customers prefer a medium utilization of the service provider. We find that this is a robust representation of customers' preferences, even if other quality signals, such as star ratings and prices, are available.