Mediated Modeling A System Dynamics Approach To Environmental Consensus Building
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Mediated Modeling
Author: Marjan Van den Belt
language: en
Publisher: Washington, DC : Island Press
Release Date: 2004-04
Mediated modeling is an innovative new approach that enhances the use of computer models as invaluable tools to guide policy and management decisions. Rather than having outside experts dispensing answers to local stakeholders, mediated modeling brings together diverse interests to raise the shared level of understanding and foster a broad and deep consensus. It provides a structured process based on system dynamics thinking in which community members, government officials, industry representatives, and other stakeholders can work together to produce a coherent, simple but elegant simulation model. Mediated Modeling by Marjan Van Den Belt is a practical guide to participatory modeling for both practitioners and students, one that is firmly theoretically grounded in the field of systems dynamics and environmental modeling. Five in-depth case studies describe the successful use of the technique in a variety of settings, and a final chapter synthesizes the lessons highlighted by the case studies. Mediated Modeling's step-by-step description of the techniques and practical advice regarding implementation offer a real-world solution for all those seeking to make sound decisions about the environment.
Handbook of Research methods and Applications in Environmental Studies
Author: Matthias Ruth,
language: en
Publisher: Edward Elgar Publishing
Release Date: 2015-08-28
This Handbook presents methods to advance the understanding of interdependencies between the well-being of human societies and the performance of their biophysical environment. It showcases applications to material and energy use; urbanization and tech
Agent-Based Modeling of Environmental Conflict and Cooperation
Conflict is a major facet of many environmental challenges of our time. However, growing conflict complexity makes it more difficult to identify win-win strategies for sustainable conflict resolution. Innovative methods are needed to help predict, understand, and resolve conflicts in cooperative ways. Agent-Based Modeling of Environmental Conflict and Cooperation examines computer modeling techniques as an important set of tools for assessing environmental and resource-based conflicts and, ultimately, for finding pathways to conflict resolution and cooperation. This book has two major goals. First, it argues that complexity science can be a unifying framework for professions engaged in conflict studies and resolution, including anthropology, law, management, peace studies, urban planning, and geography. Second, this book presents an innovative framework for approaching conflicts as complex adaptive systems by using many forms of environmental analysis, including system dynamics modeling, agent-based modeling, evolutionary game theory, viability theory, and network analysis. Known as VIABLE (Values and Investments from Agent-Based interaction and Learning in Environmental systems), this framework allows users to model advanced facets of conflicts—including institution building, coalition formation, adaptive learning, and the potential for future conflict—and conflict resolution based on the long-term viability of the actors’ strategies. Written for scholars, students, practitioners, and policy makers alike, this book offers readers an extensive introduction to environmental conflict research and resolution techniques. As the result of decades of research, the text presents a strong argument for conflict modeling and reviews the most popular and advanced techniques, including system dynamics modeling, agent-based modeling, and participatory modeling methods. This indispensable guide uses NetLogo, a widely used and free modeling software package, to implement the VIABLE modeling approach in three case study applications around the world. Readers are invited to explore, adapt, modify, and expand these models to conflicts they hope to better understand and resolve.