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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.

AbstractWhen developing system dynamics models, particularly in economics and finance, we have repeatedly encountered requirements to analyze terminal conditions. We believe that this holds more generally for modeling social problems, too. In this article, we show how to solve system dynamics models when some level variables have predetermined terminal conditions. With the method presented, it is possible to determine consistently the initial states of the level variables given the terminal state conditions.

AbstractSystem dynamics research has made numerous contributions to a range of management subfields, including operations, organization behavior, marketing, behavioral decision making, and strategy. In this paper, we focus on the role for system dynamics research in making important progress on the defining issue in the field of strategy: why are some firms more profitable than others? Strategy researchers are eager for dynamic theories that explain the evolution of performance differences among firms and are increasingly looking to managerial decision making as the source of dynamics. This interest in dynamics and decision making creates an enormous opportunity for system dynamics researchers as carefully grounded behavioral theories of dynamics flow naturally from the research methods of system dynamics. Building and testing theories that explain longitudinal patterns of performance differences among firms would be an enormous step forward where mainstream strategy approaches have struggled. We identify four promising research paths along these lines for system dynamics research in the field of strategy. Copyright © 2009 John Wiley & Sons, Ltd.