Waiting for service is an undesirable, but inevitable, part of everyday life. For businesses, it negatively influences customer satisfaction, loyalty, and service quality perception.
In order to reduce the waiting times in shops, research was carried out to find improvements for queuing system and employee scheduling. The research yielded several improvements to reduce waiting times, such as the introduction of service appointments, changing to employee scheduling, and increasing the number of workstations.
Researchers developed a discrete event simulation model of shops in order to evaluate suggested improvements.
To avoid the difficulties with model validation due to data scarcity, a model calibration procedure was proposed. The calibration method is based on the idea that service times increase during low-demand hours and decrease during high-demand hours.
The results show that the proposed model calibration procedure enables the generation of realistic values for the selected KPIs. This allows analysis of queuing system KPI. Also, it is possible to evaluate improvement suggestions.