Creating policy designs to prevent reneging in queues in quick-service systems using a simulation-based experiment

• Main Author: Tirona, Emilie Dionisio
• Format: text
• Language: English
• Published: Animo Repository 2012
• Online Access: https://animorepository.dlsu.edu.ph/etd_masteral/4299
• Institution: De La Salle University

The reneging of people from queues in service systems is quite common in real situations. Managing queues is a dilemma for managers who wish to improve service operations and increase its return on investment. Some aspects of the waiting line system can be influenced by anchors. Anchors do not physically affect the waiting line system, but are informational non-operational elements that influence customers perception of the waiting time. Maister offered eight principles that served as generic managerial advice to service organizations about how to improve aspects of their service encounters which they can use to influence the customers waiting experience. With these principles, he aims to promote the psychological considerations involved in managing customers acceptance of waiting time to get the highest satisfaction level from customers. While the principles that Maister developed serves as a good eye opener that there are indeed ways that managers can influence the customers waiting experience, it lacks strategic guide as to when and how managers will utilize these principles. Five key variables are known to be significant in affecting the decisions made by customers during waiting times in majority of the experiments made by different authors across different scenarios: Queue Length, Inform Expected Length of Wait, Timing of the Reason for Delay, Type of Distraction, and Elapsed Waiting Time. This study looked into these variables to see how they can be used and altered to make a policy design. A policy design will serve as a guide as to when and how to manage the queue, depending on the conditions of that queue. The type of system considered in this study was a quick-service, one where the transaction is done over the counter between the customer and the service provider. Waiting time is defined to start as soon as the customer joins a queue until the initial interaction with the service provider. The software Scratch was used to create a visual simulation of the scenarios containing these variables. After doing the initial experiment, the significant variables that came out were Queue Length, Inform Expected Length of Wait, Timing of the Reason for Delay and Type of Distraction. All levels of these variables were then used in the final experiment. The significant variables that came out from the final experiment were Queue Length, Inform Expected Length of Wait, and Timing of the Reason for Delay. These factors along with the raw data results from Scratch were then used to come up with policy designs. The scenarios where participants reneged were given special attention so that these policy designs may effectively address these conditions and prevent the customers from reneging in the future. There were six (6) policy designs that were created for service providers to use if and when those conditions came up. Based on the validation results, all but one of the policy designs created were found to be effective in making the customers stay in the line and wait for service completion. Lastly, in the questionnaire where the participants were asked if the statement I leave the waiting line when actual waiting takes more time than I expected to wait was true or false for them, 43% said True, but did not actually renege. While during the validation runs, it was 64%. This shows another limitation of verbal or written scenarios, where people say they will do something, until it is actually already happening in reality and they did not do what they said they would. It was only when they actually experienced the wait during the experiment that showed how they really felt about the statement.