System dynamics, systems thinking, and soft OR

TLDR

System dynamics, systems thinking, and soft OR aim to understand and improve systems, yet the latter often lack explicit modeling and rely on subjective intuition after describing the real world. The study proposes a bidirectional collaboration where systems thinking and soft OR provide participant‑derived insights to system dynamics, while system dynamics offers rigorous modeling and simulation to enhance the former. System dynamics proceeds by translating descriptions into mathematical models, simulating them to explore dynamics, evaluating alternative policies, and guiding policy choice and implementation.

Abstract

System dynamics, systems thinking, and soft operations research (soft OR) all aspire to understanding and improvement of systems. In all, the first step interprets the real world into a description used in following stages. In system dynamics, description leads to equations of a model, simulation to understand dynamic behavior, evaluation of alternative policies, education and choice of a better policy, and implementation. Case studies, systems thinking, and soft OR usually lack the discipline of explicit model creation and simulation and so rely on subjective use of unreliable intuition for evaluating the complex structures that emerge from the initial description of the real system. Nevertheless, systems thinking and soft OR, with emphasis on eliciting information from-real-world participants, should contribute useful insights to system dynamics. Conversely, the model creation and simulation stages of system dynamics should contribute rigor and clarity to systems thinking and soft OR.