Analytical and empirical investigations of ticket queues: Implications for system performance, customer perceptions and behavior

This dissertation investigates the system performance, customer perceptions of and behavior in ticket queues, the new generation of queuing systems that issue tickets to customers upon their arrival, using analytical and empirical approaches. Ticket queues are widely used by service providers to manage customer flows. In this dissertation, we present three studies with the goals of generalizing system representations of ticket queues, investigating the validity of the assumptions used in the analytical models, and providing empirical support for the analytical model results.;The first essay proposes a Markov chain (MC) model for multi-server ticket queues with state-dependent balking and state-independent reneging customers. This study aims at analyzing the system performance of a multi-serve ticket queue and benchmarking ticket and physical (stand-in-line) queue performances. We develop exact analytical results for key system performances with customer abandonment (including both customer balking and reneging behavior), and present efficient and accurate heuristics to analyze large systems. The heuristics prove to be robust and accurate approximations.;A ticket queue differs from a corresponding physical queue in terms of the amount of information available to customers. The lack of information for the number of existing customers in the ticket queue system results in naive customer abandonment behavior and worsens system performances compared to those in the corresponding physical queue. In order to close the performance gap, we propose to provide different types of information to ticket queue customers. We find that for each type of information provided, the customer balking probability decreases while the customer reneging probability increases, and the overall service completion rate improves. Therefore, providing information does not necessarily guarantee an improvement in each system performance measures. The queuing system managers should consider this trade-off when they are providing information to customers.;The second essay generalizes the model developed in the first essay by considering state-dependent reneging behavior of ticket queue customers. The reneging behavior of a customer depends on his/her ticket position in the system. The literature on progress towards the goal and on the escalation of commitment suggests that the reneging rate will be an increasing function of one's ticket position. On the other hand, the view that the time spent in line makes customers more impatient will suggest the reneging rate should be a decreasing function of the ticket position. Our analysis can incorporate either an increasing or a decreasing function of the reneging rate in the model. In conclusion, the second essay provides the framework to analyze multi-server ticket queues with state-dependent abandonment and provides insight into developing more realistic ticket queue models.;Although certain system performances deteriorate in ticket queues compared to those in physical queues, we observe that ticket queues are popular systems in both private and public sectors. This dilemma motivates us to obtain insights into the customer perceptions of and behavior in different queue arrangements, and to investigate whether the assumptions and results of our analytical models hold. The third essay investigates the perceptions of and behavior in ticket queues empirically using a series of surveys. Our results indicate that subjects generally prefer a ticket queue arrangement over a physical queue arrangement, and the level of preference is amplified in high traffic intensity or high service value settings. In addition, we find that the subjects are willing to wait longer in the ticket queue setting than they are in the physical queue setting, which contradicted one of the assumptions we used in the first two essays. On the other hand, we validated the existence of the sunk cost effect in waiting scenarios, which provides support for our assumption in the analytical pieces that customers become more patient after they join and spend some time in line. Finally, we identify the factors effective in the subjects' decisions to prefer the ticket queue setting over the physical queue setting and show the impact of the context of the wait on the preference of and behavior in different waiting lines. Our results suggest that the analytical models used in the literature should incorporate the abandonment behavior of customers to reflect reality. We also identify and recommend the type of queues to be implemented under different service settings as a decision support to system managers.;In summary, we analyze, obtain insights into and compare the performances of ticket and the physical queues from both the analytical and empirical points of view in this dissertation. Our findings could assist system managers in designing better queuing arrangements, and matching an appropriate type of queue with the services provided.