Understanding model behavior using the Loops that Matter method

Abstract

The relationship between structure and behavior is central to system dynamics, but effective tools required to understand that relationship still elude us. The current state of the art in the field of loop dominance analysis relies on either practitioner intuition and experience or complex algorithmic manipulation in the form of eigenvalue analysis or pathway participation metrics. This article presents a new and distinct numeric method based on a different measure, the loop score, to determine the contribution of a loop to a model's behavior at each instant in time. This allows us to discover the origin of model behavior. The method was inspired by observations of the patterns in the changes of the values of variables during simulations and has been tested and refined using empirical evaluation on a variety of models. The method also offers a promising approach to the visualization and aggregation of simulation results.