System Dynamics

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Community Based System Dynamics

Author: Peter S. Hovmand
language: en
Publisher: Springer Science & Business Media
Release Date: 2013-11-09
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.
System Dynamics

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.
System Dynamics Modeling with R

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.