Queue Server Efficacy in the Retail Industry: A Behavioral Study Inspired by behavioral operations and supply chain management this research explores the queuing behavior in retail operations. Customers frequently experience waiting for service in a queue at retail stores. Customer waiting time has a psychological and economic costs. Traditional mathematical models of queuing systems do not consider these psychological costs. Retail stores face the challenge of optimizing queue performance with thin profit margins and high labor costs. This leads to dissatisfied customers who may switch to competitive service offerings with efficient queue management systems. This research focuses on managing the queue server, to increase the efficacy in retail counter queues. A leading Sri Lankan supermarket chain acts as the focal company for this research. A behavioral study was conducted and servers who operate the cash register are the subjects. We observe serversu0027 behavior using a carefully planned field study, where we identify issues and factors that should be addressed in order to increase server efficiency. We find several factors that affect queue serversu0027 efficacy such as speed and the quality of the machines and equipment at queue server points, unawareness of incentives for efficient service, delays due to the erroneous entry of products, the workload of the queue server and queue serveru0027s job satisfaction.

Simulation Model to Evaluate Effectiveness of Queue Management Tool in Supermarket Retail Chain As part of its continuous process to improve operational excellence and productivity, a retail company in Asia trialed the usage of a commercial retail tool, known as Queue Buster, to improve queue management processes in its physical stores. We employed Queuing Theory to determine the effectiveness of implementing the Queue Buster. Specifically, we constructed a queuing simulation model based on input parameters derived from queuing data collected at a pilot store. Three main performance metrics  Wait Time, System Time and System Length were measured for two different queue systems, with and without the implementation of Queue Buster. Simulation results demonstrated improvement to all three performance metrics when Queue Buster is implemented. Using the system, we proposed an optimal range of trigger point i.e. the number of customers in the queue where retail chains should start employing Queue Buster to achieve optimal results. Sensitivity Analysis was also performed at various InterArrival Time to test the robustness of the model.