Improving Loops that Matter

Abstract

AbstractThe Loops that Matter (LTM) approach to understanding behavior has proven easy to use and broadly applicable, but it has a shortcoming in its original formulation. This is because the original formulation treats the impact of a flow on a stock relative to the net flow, so that all scores tend to get very large in magnitude as a stock approaches equilibrium, but how big depends strongly on how the flows are specified. By reformulating the link scores from a flow to a stock, this topological dependency is removed. The mathematics behind this approach makes clear the relationship of LTM to the Pathway Participation and Loop Impact analysis methods. The result of this, when applying the analysis to a variety of models, is that the determination of the structure responsible for behavior is clearer, and more clearly tied to work already documented using other techniques. © 2023 The Authors. System Dynamics Review published by John Wiley & Sons Ltd on behalf of System Dynamics Society.