Licence to Simulate: When Agent-Based Models Are More Fiction than Function

Agent-based models are increasingly used to study supply chain systems due to their capacity to capture decentralised behaviour, heterogeneity, and emergent dynamics. However, the mere use of agent-based simulation platforms does not necessarily imply that the models fully exploit the agent-based paradigm. Although this concern, namely, the potential misuse of agent-based models, has been frequently raised in the literature, no previous study has precisely quantified how frequently this issue occurs, especially in the supply chain domain. To address this gap, a systematic review of 58 academic contributions was conducted to evaluate the extent to which agent-based models applied to supply chain contexts adhere to the fundamental principles of agent-based simulation. Specifically, the reviewed works were classified into two categories: Green Flag models, representing coherent and appropriate implementations of agent-based models, and Red Flag models, which fail to capture the essential characteristics of agent-based simulation. The classification was based on key discriminating factors such as the type and number of simulated entities or agents, the nature of agent interactions, and the incorporation of system-level dynamics. Further nuance is provided by two subtypes of Green Flag models: those featuring intelligent agents, and those based on responsive or reactive entities, which might generate emergent dynamics. Our results reveal that almost 64% of the analysed agent-based contributions lack key characteristics to justify the use of agent-based models. Hence, the paper also provides conceptual tools to aid in distinguishing between different agent-based approaches. In conclusion, the present work offers both a theoretical framework and a practical evaluation guide to support the development of future models and to foster critical analysis within the field.