A Heuristic-Based Airport Shopping Behavior Model with Agent-Based Simulation

In recent years, the source of airport revenue has significantly changed. Accordingly, many airports have adjusted their strategies and focused on increasing retail revenue to improve financial sustainability. However, there is a lack of application of shopping behavior models to airport retail development. This paper aims to fill this gap by presenting a heuristic-based shopping behavior model. First, this paper briefly reviews the existing literature on heuristics for modelling shopping behavior. Second, research data collected at a case study airport is used to calibrate and validate the proposed agent-based simulation model. The Mean Absolute Percentage Error of the model stands at 5.3% on total footfall across all retail shops. The validation result demonstrates the feasibility of the proposed model in simulating the heuristic used by shoppers in airport retail. The proposed model provides an excellent foundation for future scenario studies on airport retail.