Modeling Dynamics Systems: Lessons for a First Course (third edition) provides a set of materials that enable educators at the secondary and college levels to teach a one-semester or one-year course in System Dynamics modeling. These lessons are also useful for trainers in a business environment. Developed for beginning modelers, the lessons contained in this book can be used for a core curriculum or for independent study. The lessons include some of the classic System Dynamics problems (population change, resource sustainability, drug pharmacokinetics, spread of an epidemic, urban growth, supply and demand, and more). Feedback analysis is integral to the lessons. Guidelines for an independent project and an outline for a technical paper explaining the creation process and structure of the final model, together with scoring guides for both the model and the paper, are included. Participants in the workshop will have a chance to build some simple models (participants should bring laptops) and gain a sense of the progression leading to a more sophisticated model. Student work will be demonstrated and can also be viewed at www.ccmodelingsystems.com. New materials in the third edition (oscillations, transfer of loop dominance, mapping systems in the news, ) of this book will be presented.
This paper describes work in progress on Houdini: a system dynamics model of the Dutch housing market focused on explaining institutional structures leading to high price increases and obstructing new supply and on
This paper presents an application of system dynamics to understand the behavior of the AH-64 Advanced Aircraft Course at the U.S. Army Aviation Center of Excellence. This course trains Army lieutenants and warrant officers as combat aviators. In the last several years, a large bubble of students awaiting the different phases of training has developed because of organizational and process problems within the course. This paper presents a system dynamics model of the course and recommends policy changes to eliminate the backlog of students awaiting training. The model incorporates both the organizational aspects of the course, including personnel and equipment; as well as the processes within the course. Base on output from the system dynamics model, the best course of action for the U.S. Army Aviation Center of Excellence is to add additional days to the course to account for weather and increase the number of hours available for training on a daily basis. This policy enables the center to eliminate the bubble of students and stabilize the process of training combat aviators.
From June through October 2008 the National Guard Bureau (NGB)J8 conducted a capability based assessment (CBA) to determine National Guard (NG) capability gaps for Defense Support to Civil Authorities (DSCA). A major DCSA mission that the NGB Capability Assessment and Development Process (CADP) focused on was Chemical, Biological, Radiological, Nuclear, and high-Explosive Consequence Management (CBRNE CM) response. As expected, the most difficult portion of the CBA was defining and quantifying the gap in NG specialized CBRNE CM capabilities (CERFPs). Initially, NGB developed a simple allocation model that captured the total number of CERFPs employed based on subject matter expertise. However, NGB-J8 developed a more objectively quantifiable model that would systemically document and consistently apply assumptions. Repeatability was essential to defining and quantifying NGB CBRNE CM capability gaps. NGB-J8 determined a System Dynamics Model would be the best approach for developing this model.
Automated sensitivity analysis approaches in system dynamics focus primarily on model parameters. Although table functions are often subjectively approximated, they do not form the focus of most sensitivity analyses. Recently, a promising approach that allows automation of sensitivity analysis on functions was proposed by Hearne (2010), but the applicability of this method to system dynamics table functions has not been studied, yet. In this study, the new method is applied to a simple system dynamics model. In the light of the observations a number of shortcomings are identified and a set of extensions to address these are proposed and then tested. The results of experiments with the original and the extended method demonstrate that the method can be used easily and efficiently for table functions. The extensions are shown to be valuable in creating a more comprehensive method, but they also raise the research issue of the trade-off between their added value and the cost of dealing with increased complication. Apart from our experimental results, the article also puts forth a set of directions along which the approach can be improved further. Despite the issues requiring further research, the method holds promise for routine implementation.
How can simulation be sold to policy decision makers? How can simulation be sold to other social scientists that do not accept simulation as a complement to accepted techniques (Repenning, 2003)?
Simulation provides a means to gain insight into the past behaviour and future trajectories of complex social systems. The simulation process is one of discovery: individual mental models are communicated, formalised, and simulated under a range of scenarios. There are two main approaches to social simulation: system dynamics, centred on the feedback perspective, and agent based computational modelling, which uses the individual and their interactions as the basic building block. This short paper describes a new simulation tool that can accommodate both perspectives, and where all model building is achieved using an equation-based approach. The system design is summarised and an example based on the SIR model is described.
Social-ecological resilience is an increasingly central paradigm for understanding sustainable resource management. While previous works on resilience have observed that sudden shocks or gradual stressors may force a system over a critical threshold, natural variations may have similar results. This paper aims to better understand the effect of environmental variability on the resilience of fishery systems, and the important role that social institutions play. To explore these issues, we build a System Dynamics Model of the mollusc fishery of the indigenous Seri people in the Gulf of California, Mexico. This model includes the dynamics of the two dominant species of penn shell in the fishery (Atrina tuberculosa and Pinna rugosa), several institutional rules that the Seri use, and a number of key stochastic variables derived from empirical data. We find that modeling with multiple species, rather than the standard one-species model, uncovers more resilience in the system. However, while we expected stochasticity to be detrimental to resilience, we find that endogenous environmental variability can also increase resilience. We examine possible reasons for this finding, and discuss additional insights our study revealed about managing multiple-species artisanal fisheries.