Data-Driven Simulation Modeling of the Checkout Process in Supermarkets: Insights for Decision Support in Retail Operations

Abstract

We build a realistic agent-based model for simulating customer decisions of picking a checkout line at a supermarket that is calibrated to actual point of sale (POS) data from a major European retail chain. It is implemented on the open-access NetLogo simulation platform and is freely available to academics and practitioners interested in testing how different checkout zone layouts, as well as queue management and feedback strategies impact the overall efficiency of the checkout process. In particular, we show that when customers pick a line by minimizing the expected waiting time, not only is this choice beneficial for the customers themselves, as it leads to shorter waiting times in queues, but also for the supermarket management, since it yields shorter working times of the cashiers. As such, we provide guidance as to the feedback that could be provided to customers entering the checkout zone.

Keywords

• Agent-based simulation
• checkout process
• customer analytics
• decision support
• NetLogo
• queue management system