A clear definition of system dynamics modeling can provide shared understanding and clarify the impact of the field. We introduce a set of characteristics that define quantitative system dynamics, selected to capture core philosophy, describe theoretical and practical principles, and apply to historical work but be flexible enough to remain relevant as the field progresses. The defining characteristics are: (1) models are based on causal feedback structure, (2) accumulations and delays are foundational, (3) models are equation‐based, (4) concept of time is continuous, and (5) analysis focuses on feedback dynamics. We discuss the implications of these principles and use them to identify research opportunities in which the system dynamics field can advance. These research opportunities include causality, disaggregation, data science and AI, and contributing to scientific advancement. Progress in these areas has the potential to improve both the science and practice of system dynamics. © 2024 The Authors. System Dynamics Review published by John Wiley & Sons Ltd on behalf of System Dynamics Society.

This paper gives a brief introduction to systems thinking and practical insights project managers and business leaders can use in day-to-day interactions. We describe three common systems archetypes: limits-to-growth, fixes-that-fail, and drifting-goals. We illustrate each structure with a description of how system structure drives system behavior in the context of a project-based organization trying to resolve delays. We provide examples of the archetype in other contexts as well as simple suggestions on how to use systems thinking to improve these scenarios. Further reading is suggested with additional sources.

This paper proposes a new theory of non-state actors who engage in irregular warfare to seize territory and govern openly, called emerging-state actors. Emerging-state actors arise in periods of irregular conflict, such as the so-called Islamic State of Iraq and Syria (ISIS). The theory tries to answer “what is/was” the Islamic State because emerging-state actors differ notably from other non-state actors and insurgencies in irregular conflict. Causal diagrams as well as key propositions present the theory. Testing occurs against a system dynamics simulation called the “Emerging-State Actor Model” (E-SAM), loaded with the ISIS historical case in Syria and Iraq. Through experiments the simulation confirms evidence of emerging-state actor behavior as well as a range of contingencies showing their applicability. The novelty of E-SAM as a simulation for irregular conflict is its ability to handle multiple forms of conflict including political grievance, terrorism, insurgencies and emerging-state actors. E-SAM can also simulate multiple actors within each conflict: domestic and foreign state actors, local conflict actors, as well as different ethnographic groups. It can be parameterized with scenarios to simulate a variety of scenarios: ISIS in Libya, Boko Haram in Nigeria, Taliban in Afghanistan and even expatriated ISIS fighters returning to pursue new conflicts such as in Indonesia.

Our research builds upon a theory of emerging-state actors. We look to apply the theory in analyzing intervention and containment policies to use against emerging-state actors, using the Islamic State of Syria & Iraqi (ISIS) as the case study. We show utility across four military applications of simulation: understanding, forecasting and responding to adversary and societal behavior; understanding enemy command and control structures; and analyzing, forecasting and planning courses-of-action (COA). To do this, we created two baseline scenarios—one replicating the historical foreign intervention against ISIS and a counter-factual where no foreign intervention occurred. We then conducted a suite of experiments on contemporary military intervention policies in isolation, combination, at different timing windows and under hypothetical “best case” conditions as well as operationally constrained. Insights of these experiments’ tests include the influence of ethnographic envelopes, timing windows, the importance of actor legitimacy and the marginally diminishing returns of combat actions. Finally, we test a policy based on emerging-state actor theory incorporating these insights against the contemporary policies, historical baseline and two falsification policies. The emerging-state actor COA performs significantly better than others. Our research contributes a simulation, called the Emerging-State Actor Model (E-SAM). This simulation includes military, economic, political, social and information aspects (known asDIME-PMESII simulations) for both researchers and military planners concerned with irregular conflict.

This paper builds confidence in the terror contagion hypothesis that violent radicalization leading to predatory mass violence operates as a system. Within this system, the contingent values of key root causes create channels within which violent ideologies and terrorism emerge. We built a system dynamics simulation model capable of replicating historical reference modes and sophisticated enough to test the contingent values of these propositions. Of 16 propositions, we identified six root-cause propositions that must simultaneously exist, act in concert and explain the dynamics of their interaction which generate a terror contagion. Other propositions can strengthen or weaken an existing contagion but not eliminate it. We use an experiment to demonstrate how changing the contingent values of these propositions creates downward channels. This experiment helps reconcile the swarm vs. fishermen debate over the true root causes of violent radicalization. Within these channels, the contingent values can favor swarm or fishermen manifestations. The simulation and experimentation results enable the future development of the terror contagion hypothesis, provide a testing environment for research on violent radicalization, and provide a pathway to policy development in the combating of terrorism that arises from violent radicalization.