Community Based System Dynamics introduces researchers and practitioners to the design and application of participatory systems modeling with diverse communities. The book bridges community- based participatory research methods and rigorous computational modeling approaches to understanding communities as complex systems. It emphasizes the importance of community involvement both to understand the underlying system and to aid in implementation. Comprehensive in its scope, the volume includes topics that span the entire process of participatory systems modeling, from the initial engagement and conceptualization of community issues to model building, analysis, and project evaluation. Community Based System Dynamics is a highly valuable resource for anyone interested in helping to advance social justice using system dynamics, community involvement, and group model building, and helping to make communities a better place.

This book makes the case for a systems approach to small-scale community development projects. It specifically looks at the application of one branch of systems science, called system dynamics, to develop conceptual models of small-scale communities and address specific issues they might be facing at different scales. A systems approach recognizes that, by definition, communities are complex adaptive systems consisting of multiple subsystems and parts (e.g., individuals, institutions, and infrastructure) that are interconnected, driven by some purpose, follow certain rules, and interact with each other and with their surrounding environment. In order to address community issues and problems, complexity and uncertainty must be embraced and dealt with. Inside, the author emphasizes and shows how to include a system- and complexity-aware approach in the different phases of small-scale community project management. Adopting this approach comes with unique challenges such as dealing with ill-defined problems, considering uncertainty, recognizing that no unique and best solutions to complex problems exist, and accepting satisficing solutions. The text demonstrates the need for community development practitioners to integrate in all stages of their projects: participation, systems thinking, continuous reflection-in-action, and a combination of critical and creative tools.

This book makes the case for a systems approach to small-scale community development projects. It specifically looks at the application of one branch of systems science, called system dynamics, to develop conceptual models of small-scale communities and address specific issues they might be facing at different scales. A systems approach recognizes that, by definition, communities are complex adaptive systems consisting of multiple subsystems and parts (e.g., individuals, institutions, and infrastructure) that are interconnected, driven by some purpose, follow certain rules, and interact with each other and with their surrounding environment. In order to address community issues and problems, complexity and uncertainty must be embraced and dealt with. Inside, the author emphasizes and shows how to include a system- and complexity-aware approach in the different phases of small-scale community project management. Adopting this approach comes with unique challenges such as dealing with ill-defined problems, considering uncertainty, recognizing that no unique and best solutions to complex problems exist, and accepting satisficing solutions. The text demonstrates the need for community development practitioners to integrate in all stages of their projects: participation, systems thinking, continuous reflection-in-action, and a combination of critical and creative tools.

This book is about increasing team performance. It focuses on building system dynamics models when tackling a mix of interrelated strategic problems to enhance team learning, foster consensus, and create commitment. The book is intended to be applied in the organizations of today. As the "command and control" organization evolves into one of decision-making teams, so these teams have become the critical building blocks upon which the performance of the organization depends. The team members face an increased complexity of decision making with the interrelation of several strategic problems. What this means is that people have different views of the situation and will define problems differently. However, research shows that this can in fact be very productive if and when people learn from each other in order to build a shared perspective. Learning in this way might prove to be the only sustainable competitive advantage for organizations in the future. As a result, team leaders want to create "learning teams" and are confronted with issues such as how to: create a situation where people doubt their ideas rather than stubbornly cling to dearly held views create a learning atmosphere rather than trying to "win" the discussion create a shared understanding of a problem in a team foster consensus and create commitment with a strategic decision facilitate Group Model Building Those who will benefit most from Group Model Building: Facilitating Team Learning Using System Dynamics are those who are familiar with systems thinking or organizational learning, or those who are working in groups and are coming up against the common difficulties.

This book allows the reader to acquire step-by-step in a time-efficient and uncomplicated the knowledge in the formation and construction of dynamic models using Vensim. Many times, the models are performed with minimal current data and very few historical data, the simulation models that the student will design in this course accommodate these analyses, with the construction of realistic hypotheses and elaborate behavior models. That's done with the help of software Vensim that helps the construction of the models as well as performing model simulations. At the end of the book, the reader is able to: - Describe the components of a complex system. - Diagnose the natural evolution of the system under analysis. - Create a model of the system and present it using the simulation software. - Carry out simulations with the model, in order to predict the behavior of the system. Content Environmental Area 1. Population Growth 2. Ecology of a Natural Reserve 3. Effects of the Intensive Farming 4. The Fishery of Shrimp 5. Rabbits and Foxes 6. A Study of Hogs 7. Ingestion of Toxins 8. The Barays of Angkor 9. The Golden Number Management Area 10. Production and Inventory 11. CO2 Emissions 12. How to Work More and Better 13. Faults 14. Project Dynamics 15. Innovatory Companies 16. Quality Control 17. The impact of a Business Plan Social Area 18. Filling a Glass 19. A Catastrophe Study 20. The Young Ambitious Worker 21. Development of an Epidemic 22. The Dynamics of Two Clocks Mechanical Area 23. The Tank 24. Study of the Oscillatory Movements 25. Design of a Chemical Reactor 26. The Butterfly Effect 27. The Mysterious Lamp Advanced Exercises (Vensim PLE PLUS) 28. Import data from an Excel file 29. Building Games and Learning Labs 30. Interactive models 31. Input Output Controls 32. Sensitivity Analysis Annex I. Guide to creating a model II. Functions, Tables and Delays III. Frequently Asked Questions FAQs IV. Download the models of this book The author Juan Martín García is teacher and a worldwide recognized expert in System Dynamics, with more than twenty years of experience in this field. Ph.D. Industrial Engineer (Spain) and Postgraduated Diploma in Business Dynamics at Massachusetts Institute of Technology MIT (USA). He teaches Vensim online courses in http://vensim.com/vensim-online-courses/ based on System Dynamics.

This new interdisciplinary work presents system dynamics as a powerful approach to enable analysts build simulation models of social systems, with a view toward enhancing decision making. Grounded in the feedback perspective of complex systems, the book provides a practical introduction to system dynamics, and covers key concepts such as stocks, flows, and feedback. Societal challenges such as predicting the impact of an emerging infectious disease, estimating population growth, and assessing the capacity of health services to cope with demographic change can all benefit from the application of computer simulation. This text explains important building blocks of the system dynamics approach, including material delays, stock management heuristics, and how to model effects between different systemic elements. Models from epidemiology, health systems, and economics are presented to illuminate important ideas, and the R programming language is used to provide an open-source and interoperable way to build system dynamics models. System Dynamics Modeling with R also describes hands-on techniques that can enhance client confidence in system dynamic models, including model testing, model analysis, and calibration. Developed from the author’s course in system dynamics, this book is written for undergraduate and postgraduate students of management, operations research, computer science, and applied mathematics. Its focus is on the fundamental building blocks of system dynamics models, and its choice of R as a modeling language make it an ideal reference text for those wishing to integrate system dynamics modeling with related data analytic methods and techniques.

The current literature on dynamic systems is quite comprehensive, and system theory’s mathematical jargon can remain quite complicated. Thus, there is a need for a compendium of accessible research that involves the broad range of fields that dynamic systems can cover, including engineering, life sciences, and the environment, and which can connect researchers in these fields. The Handbook of Research on Modeling, Analysis, and Control of Complex Systems is a comprehensive reference book that describes the recent developments in a wide range of areas including the modeling, analysis, and control of dynamic systems, as well as explores related applications. The book acts as a forum for researchers seeking to understand the latest theory findings and software problem experiments. Covering topics that include chaotic maps, predictive modeling, random bit generation, and software bug prediction, this book is ideal for professionals, academicians, researchers, and students in the fields of electrical engineering, computer science, control engineering, robotics, power systems, and biomedical engineering.