Agent-Based Modelling of food systems: A scoping review on incorporation of behavioural insights

Abstract

Agent-Based Models (ABMs) offer a flexible and interdisciplinary approach to food system modelling by simulating the interactions of heterogeneous agents within social and environmental contexts. Given their bottom-up structure, the validity of ABMs critically depends on the behavioural assumptions underpinning agent decision-making. This scoping review examines how behavioural assumptions are informed in ABMs applied to food systems by analysing 55 relevant studies. We classify approaches into two categories: data-driven methods and behavioural theory. Our findings reveal that more than a third of the included studies rely on neither behavioural theory nor behavioural data to inform their behavioural assumptions in the model, raising concerns about model validity. The highlighted gaps in the usage of behavioural data and theory to inform ABMs, emphasizes the need for a stronger focus on robust behavioural assumptions in ABMs of food systems.