Eigenvalue Analysis of System Dynamics Models: Another Perspective

Previous work related to eigenvalue analysis in the system dynamics field has primarily focused on linking the model structure to the modes of behavior -- i.e. the eigenvalues. While the system eigenvalues define the characteristics of the system’s behavior modes (e.g., exponential growth, expanding oscillations), these behavior modes are not equally represented in all model variables, making it difficult to link the behavior of the behavior mode to the behavior of a particular variable. In this study we propose an alternative perspective and explicitly explore the significance that each behavior mode has on the system state variables. We achieve this by decomposing the behavior of a variable into a sum of the weighted behavior modes in the system (represented by the eigenvalues). We argue that focusing on the weights, rather than on the eigenvalues, is a more efficient way to develop policy recommendations and compute the elasticity of the weights to the gain on any link the model allowing for a more efficient and discriminate way to identify policies.