The previous work related to eigenvalue analysis in the system dynamics field, 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 reference 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 reference 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. A routine to estimate the weights of any linear model and
compute the elasticity of those weights to model links is developed and made available at http://
iops.tamu.edu/faculty/roliva/research/sd/.