The problem of empty houses in Taiwan continues to concern the public. The Government currently conducts housing survey to detect the number of empty houses every year. But, no systematic analysis of the monitoring and early warning programme has been undertaken to improve the situation. This study formulated dynamics and genetic artificial Neural Network models for the monitoring and early warning system stimulating. Several strategy scenarios were conducted. The research findings showed that economic strategy has a more positive and profound impact than financial one; combined strategy often has a better policy assessment compared to a single strategy. The method developed in this study is a comprehensive and systematic approach to achieve the sound housing market in Taiwan.
Health system reform is a national priority in the U.S., but it is increasingly being pursued through a mosaic of local initiatives. More and more concerned leaders in cities, towns, and regions across the country are working within their local health systems to achieve better health, better care, lower cost, and greater equity. Such ambitious and widely dispersed ventures, however, are hard to plan, unwieldy to manage, and slow to spread. Further progress could occur if diverse stakeholders were better able to play out intervention scenarios, weigh trade-offs, set aside schemes that are unlikely to succeed, and enact strategies that promise the most robust results. Through the Rippel Foundations ReThink Health initiative, veteran leaders and creative methodologists are learning what it takes to spark and sustain system-wide improvements in different settings. Interactive simulation modeling and game-based learning support innovators by bringing greater structure, evidence, and creativity to the action planning process. In this paper we provide an overview of the ReThink Health Dynamics simulation model by providing a summary of its structure, intervention options, data sources, user interface, experiences in pilot sites, initial insights, evaluation plan, and possibilities for further development and diffusion.
Organ transplantation is a lifesaving procedure for many people. However, the lack of organs from deceased donors makes it unavailable for many additional people who need it. A commissioned study was undertaken to estimate deceased donor potential in the US. Organ procurement and transplantation take place in the context of a complex system of organizations and policies. This system can both constrain and enhance the realization of deceased donor potential. A system dynamics model is being developed to help identify how that systems behavior affects the availability of deceased donor organs and how particular strategic policy options might increase the number available for transplantation. The structure and data sources for the model are described along with illustrative tests of those strategic options.
Fast growing electricity demand in Indonesia has threatened countrys economic development pace. However, government owned Electricity Company cannot cope with this growing demand. As a result they rely on Independent Power Producer (IPP) which harm government budget. In the mean time, government realizes this growing issue and tries to do something by building more power plants. On the other hand, their plan on building new coal and oil based power plant is meeting a lot of resistance from NGO and parliament. On top of it, government cannot afford continue funding electricity from IPP. The situation is increasingly become worse if government does nothing about the issue. Therefore, understanding and smooth communication is needed to provide solution for the issue. A system dynamics based game is built to foster communication between stakeholders, in order to help them visualize dynamics and feedback loop inside Indonesias electricity system. In the first development phase the game tested on group of students and showed good result on improving their understanding on current electricity issues.
Quantifying the strength of causal loops on a stock can help bring insights into the relationship between model structure and behavior. This paper uses mathematics to derive loop strengths in a number of generic small models using the relationship between the second and first derivative from the Pathway Participation Metric method. The loop strengths are plotted in a System Dynamics (SD) simulator together with the stocks to help explain behavior in the Limits to Growth, Predator-Prey, Diffusion and SIR models among others. Issues such as loop dominance, flow dominance and the change of polarity of higher order loops are used to explain behavior. In particular the identity of the causal loops in the Diffusion and SIR models are discussed and compared with previous work. Finally a numerical method for computing loop strengths and identifying dominant loops within an SD simulator is presented and applied to the Yeast Model. It is hoped that the paper will inspire others to use loop strengths in their analysis and understanding of SD models