Substance flow analysis (SFA) is a frequently used industrial ecology technique for studying societal metal flows, but it is limited in its ability to inform us about future developments in metal flow patterns and how we can affect them. Equation-based simulation modeling techniques, such as dynamic SFA and system dynamics, can usefully complement static SFA studies in this respect, but they are also restricted in several ways. The objective of this article is to demonstrate the ability of agent-based modeling to overcome these limitations and its usefulness as a tool for studying societal metal flow systems.
The body of the article summarizes the parallel implementation of two models—an agent-based model and a system dynamics model—both addressing the following research question: What conditions foster the development of a closed-loop flow network for metals in mobile phones? The results from in silico experimentation with these models highlight three important differences between agent-based modeling (ABM) and equation-based modeling (EBM) techniques. An analysis of how these differences affected the insights that could be extracted from the constructed models points to several key advantages of ABM in the study of metal flow systems. In particular, this analysis suggests that a key advantage of the ABM technique is its flexibility to enable the representation of societal metal flow systems in a more native manner. This added flexibility endows modelers with enhanced leverage to identify options for steering metal flows and opens new opportunities for using the metaphor of an ecosystem to understand metal flow systems more fully.