Modeling assistance is available at the conference to enable modelers to discuss their specific modeling questions with modeling coaches. Modeling assistance opportunities include two public workshops, as well as the possibility of assistance at any time during the conference. Assistance is available for modelers with all levels of modeling ability, from beginner to advanced, with questions about a specific model that modelers are developing or studying, or to better understand something in a book, an article, or a software package. Modeling questions may deal with problem articulation, formulation of a dynamic hypothesis, formulation of a simulation model, model testing, or policy design and evaluation. Modelers should bring whatever materials they need to describe their question,including pencil and paper, books, posters, or laptop computers. Spectators are welcome to observe modeling assistance during the two public sessions.
The Global Systems Simulator addresses the issues of sustainability and carrying capacity at a global scale - the same issues addressed by the Jay Forrester's World model. The current version of the GSS is a prototype intended as proof of concept for a much different approach to modeling. Systems models are seen as explicit extensions of the mental models we use to interpret the signals received by our sensory apparatus and to navigate in the real world - extensions that enable us to perceive the long term and systemic consequences of potential actions. The approach has its roots in the activity analysis of Koopmans, Leontief, and Georgescu-Roegan, the system dynamics of Forrester, the control theory of Mesarovic, the general system theory of Weiner and Laszlo, the principle of uncertainty of Prigogine, and the cognitive theory of Bateson, Maturana and Varella. The GSS is implemented using the whatIf? software technology, a platform developed by Robbert Associates for large scale simulation modeling. The workshop will demonstrate these concepts using the Global Systems Simulator.
Hsinchu Science Park is an example of hi-technology industry development in Taiwan. Its rapid growth has brought tremendous economic benefits, though not without social and environmental impacts, resulting in conflict between economic growth and sustainable development of the science city. This study establishes a system dynamic model using STELLA programming language to simulate different development scenarios of Hsinchu Science City. Our analysis reveals that the development of the science city should comply with the objectives of (1) maximizing the profits from industries in the science park, (2) minimizing the damages incurred by the science park on its mother city, (3) decrease in consumption of natural resources, (4) reduction in environmental pollution, and (5) attention to relevant social problems.
The demand for water in Southern Taiwan has increased significantly in recent years because of industrial growth and increasing living standards. However, due to the financial reasons, only a limited scale of existing surface water facilities can be expanded in a river basin. Therefore, it often requires a suitable strategy to consider the fixed costs and operating costs for expansion. On the other hands, the conjunctive use of surface water and groundwater can enhance the reliability of water supplies by providing independent sources so that research on conjunctive use is important, especially with reference to fixed and operating costs. In light of above reason, resolving the tension between water deficit and economic profit, while ensuring the sustainable development of water resources is very urgent for government authorities. Accordingly, this investigation proposes a process of integrating the system dynamics and impact analysis for evaluating water strategy systematically and quantitatively, with reference to water shortage and economic profit as they pertain to the planning and management of regional water resources.
Simulation-based learning environments, often called management flight simulators or Microworlds, are excellent tools for giving people without modeling experience an intuitive understanding of complex systems. Learning environments let them experience the dynamics of complex systems without the hurdle of having to build models "from scratch". This workshop will deal with the design of learning environments, their user interfaces, underlying models, and workshop formats for experiencing with them. Special attention will be paid to methods of displaying information to help users understand causes of the behavior they encounter and thereby make better decisions and learn more quickly. The presenter will show a number of examples from his own work, but is also eager to make the workshop interactive and would like to hear about other people's experiences with learning environments and from people with models they are interested in turning into learning environments.
The U.S. health care system faces serious problems of high cost, limited access, unequal treatment, and inadequate health protection. Though these problems have persisted for decades and various reforms have been attempted, the overall impact of reform efforts has been only modest. This paper examines potential types of reform and the history of reform efforts. Causal-loop diagrams are presented which together comprise a theory to explain what created the set of problems that exist and why efforts at reform have largely failed. Different philosophical bases for reform and the need for an eclectic approach are discussed, and a sequential bootstrapping approach to comprehensive reform is outlined. The diagrams and discussion of this paper are intended as a starting point for further collaborative work on health care reform among system dynamics practitioners and health policy experts, leading to simulation modeling and further insights.
Microfinance institutions (MFIs) provide credit, savings, and other financial services to the poor and must successfully manage large volumes of small transactions. SymBanc is a system dynamics simulator designed to introduce students to the complexities of managing a Microfinance Institution (MFI) or to engage experienced practitioners in a discussion of the key determinants of success in such a dynamic environment. The simulator allows students and practitioners to grow an MFI from a single branch to a large network by making a variety of decisions about target market, staffing and facilities, loan and savings product design, and sources of external funding. Detailed feedback enables them to fine-tune their strategies during a simulation. This paper begins with some background on Microfinance Institutions and then presents the structure of the model underlying SymBanc and results of typical simulations. Initial experience using SymBanc and future enhancements contemplated for it are also described.
We were at the Lyons Pub. Peterson walked in with a presentable young man.
This is Randy, she said, pulling up a chair. Hes just back from Egypt. Ordering a beer, Peterson fished a photo from her pocket. Doesnt Randy look grand in front of the Sphinx?
Sedgewick turned to the young man Tell us about your trip.
Randy smiled in recollection. I stayed at Le Meridien in Giza. Costs a bloody fortune, but its worth it. Has a swim-in bar, dont you know.
And the Sphinx? Sedgewick prompted.
Randys expression turned weighty. Big. Damn big.
So youve never actually been to Egypt. Sedgewick said sadly. And, never seen the Sphinx.
Like Randy, many of us return from a model without true insight. In this workshop well deeply explore a model or two. You will see how eigenanalysis complements and speeds traditional approaches to understanding models. Math-phobics and math-lovers are equally welcome.
This report builds on a previous epidemiological model of a pneumonic plague outbreak that incorporated three behavioral responses as exogenous drivers and evaluated their importance in allowing us to replicate the actual outbreak (Heinbokel& Potash, ISDC-2003). The current paper describes our subsequent efforts to incorporate those critical and controlling behavioral dimensions into this model as critical feedback loops. We conceptually deconstructed the event into four segments: becoming aware of the outbreak, deciding to act in response, choosing a specific response, and returning to normal behavior. We utilized current psychological theories, such as the Psychometric Paradigm and Brunswiks Lens Model, to build small, conceptually clear, transferable, and combinable behavioral submodels to simulate the first three segments involving information and social networks, social trust, and risk perceptions. We believe these modeling efforts comprise first steps in a critical process of translating current, frequently static, risk theories to dynamically responsive vehicles that can be flexibly and quantitatively applied to reliably aid in understanding and influencing responses to such public health threats, other extreme events, and other dynamic risk scenarios in general.