Aggregation in system dynamics

Abstract

AbstractStochastic aspects of systems have generally been ignored in most system dynamics studies except for purposes of sensitivity testing. Yet any model that claims to be more than simply a phenomenological description of a system must treat the underlying stochasticity explicitly in terms of its contribution to the dynamics. Recent work in chemical, biological, and hydrodynamic systems has shown that the aggregation of stochastic effects can lead to novel behavior (self‐organization in dissipative systems).In this paper, an analogy between models of these physical systems and system dynamics models is developed, in which dynamic models are seen to be an approximation (to lowest order in an expansion in system size) to a stochastic model for the system. The theoretical results derived for the physical system models are evaluated for their application to system dynamics models. A research strategy to elaborate this approach to analyzing a more general class of systems is proposed.