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Ticket queues are systems that issue tickets to customers upon their arrival. Although ticket queues are preferred by many service providers, there is limited research on ticket queues, especially on customer perceptions of, preferences for, and behavior in these systems. We conducted a series of surveys to understand customer preferences and patience in a ticket queue and a physical queue (stand-in-line system) and to investigate whether the assumptions used in analytical queuing models for customer abandonment behavior are realistic. Study results indicate that subjects generally prefer ticket queues over physical queues and have greater patience in ticket queues than they do in physical queues. In addition, we observe that subjects are willing to wait longer than they initially were, assuming that they already have spent some time waiting in line. Using the survey results, we ran a series of simulation models by adjusting the traditional queuing assumptions and showed the impact of customer behavior on system performance measures in ticket and physical queues. Our results can assist managers, in determining the type of queue to implement under various service settings, and researchers, in modeling more realistic queuing systems.

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Ticket queues are prevalent in service industries. They enhance customer satisfaction by eliminating physical lines but may compromise efficiency. Existing studies offer mixed results on the cause and magnitude of such inefficiency. These results, however, are based on simplistic customer behaviors. Taking a holistic approach, we examine how realistic customer behaviors drive ticket queue performance. Our empirical studies reveal that (i) customers are capable of adapting their patience to the waiting context and (ii) they use dynamic updating to improve forecasting and decision making over time. Once we model these two behaviors, we find the ticket queue inefficiency is much smaller than the literature predicted. By testing and highlighting the central role of realistic customer behaviors, this paper advances our understanding on ticket queue theory and practice.

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