Substantial development of counties needs to use the resources in an efficient way. One indicator that shows the degree of efficient use of energy resources is energy intensity. Statistics show that Irans energy intensity was in a bad situation during past years and if this manner of using energy resources continues, it will get worse. In this study a system dynamics approach is used to model changes of energy intensity in residential sector in Iran. By implementation and simulation of this model we found some reasons of this problem in Iran. Then we tried to introduce some policies to make steady improvement in energy intensity in the future.
Due to increasing market dynamics, Production Planning and Control (PPC) has become more challenging for manufacturing companies. Production plans have to adapt quickly to changing market demands. It is often stated that (1) conventional PPC methods cannot satisfyingly handle unpredictable events, disturbances and market dynamics and that (2) in practice the complexity of centralised architectures tends to grow rapidly with size, resulting in deterioration of fault tolerance, and flexibility. To manage the increasing dynamics inside and outside a production system, autonomous control (AC) of shop floor logistics is a promising approach. The paper gives an overview of the modelling and analysis of AC strategies for production logistics. A universal shop floor model, built with Vensim DSS, is introduced. AC strategies are discussed and implemented. The particularities of modelling a production logistic scenario are presented. Based on the simulation results the logistics performance as well as the influence on the systems behaviour is assessed. The main focus lies on the comparison of the effects of the different autonomous control strategies on the logistics performance of the system and its behaviour. To achieve this goal, sensitivity analysis is used to compare the robustness of the logistic system while interchanging the AC strategies.
Causal loop diagram largely influences the effectiveness of system dynamics. The complex interpretive nature of management problems makes it difficult to recognize all the existing causal loop relations. In order to build system dynamics models for ill-defined problems, "Group Model-Building" is developed. As discussed by Vennix, one source of these messy situations is different perceptions of individuals. In this paper, we develop an interpretive approach to drawing causal loop diagrams assuming that there are different perceptions about same concepts and the analyst is closely engaged with finding most agreed causal relationships.
Falls are a serious problem for older adults, often causing severe injuries leading to loss of independence and high cost. Although high effort was already put in research, the situation concerning prediction and prevention is unsatisfactory from practical point of view. A small interdisciplinary team attempt to address the issue in a holistic view using a system dynamics based approach. A simple model was developed based on workshops with experts, which is able to simulate commonly observed circumstances. This leads us to the opinion, that limited success of research up to now is caused by the fact, that modelling approaches used in common are not sufficient for the complexity of the underlying problem. A system dynamics approach would cope much better with this challenge, leading to better predictions and case specific interventions.
With respect to the career decisions of IT professionals around 2000 a system dynamic model using real data demonstrates how individual market orientation leads on the whole to high unemployment rates in the IT labor market. In the context of the gender equity program of the Civil Service in Germany system dynamic analysis elucidate likewise using real data the significant difference between the institutionally and the individually perceived reality.
Mental illness is a major social problem. In the United States, the vast majority of mental health services and supports are provided through nonprofit organizations. Recent changes in the field of mental health such as the implementation of evidence-based practices, funding cuts, and statewide policy initiatives such as transformation have increased financial pressures on these nonprofits. Yet few dynamic models exist for understanding the impact of these changes on nonprofit mental health organizations and their performance. This paper seeks to address this gap by presenting a model of financial performance of nonprofit mental health organizations. The purpose of this model is to identify some of the key mechanisms driving nonprofit financial performance. The model is based on the longitudinal financial data of 65 nonprofit organizations providing mental health services or supports in a large metropolitan community, and key informant interviews with executive leaders from a subset organizations participating in a three-year longitudinal study. A simulation model is presented along with implications for state policy makers, managers of nonprofit organizations, funders, and organizational scholars.
Recent discussions in system dynamics have raised questions about the scientific acceptability of system dynamics and impact of system dynamics on social problems. This paper describes two different projects in the area of mental health services researcha research study recognized for its science and consulting project making an impact on the policy processand the institutional structures forming the university-agency-state partnerships. Together, the two projects helped create a community with greater awareness of system dynamics, interest in asking new questions from a system dynamics perspective, and motivation to pursue additional system dynamics projects related to research and policy. Key features of the individual projects, Center for Mental Health Services Research, Alliance for Building Capacity, and the community are discussed. The paper concludes with implications for future work in mental health services research and system dynamics in the nonprofit sector.
Micro-lending has been introduced as an effective antipoverty tool in recent decades. However not all of micro-lending institutes are successful both in accomplishing their mission and in loan recovery. According to World Banks focus note (2006), less than a quarter of its projects that funded micro-lending were judged successful. This paper describes a specific type of micro-lending (Grameen way of micro-lending invented by Mohammad Yunus, Nobel Peace Prize winner 2006). Then it summarizes the differences of conventional bank and Grameen Bank. Also this paper illustrates the important loops that make the Grameen successful both in the loan recovery and in accomplishing its mission. The final contribution of this paper is to develop a system dynamics model to test some Grameen policies that researchers believe are the key elements of Grameens success. I find support for the fact that small loan size which is designed to match the clients knowledge maximizes Grameens capital. Also the model finds that investing some portion of Grameens capital, giving loan to groups of people and choosing appropriate interest rate are crucial for Grameen Bank.
This paper presents an analysis of systems thinking interventions in educational settings. Although these interventions have been implemented in K-12 classrooms since the mid 1980s, there is still no clear definition of systems thinking or identification of the best method to test the effectiveness of interventions or methods for teaching systems thinking The goal of this paper is to answer the question: how can we best assess the effectiveness of systems thinking interventions in education? This question begs three sub questions: (1) what is systems thinking, (2) what systems thinking interventions are being used in education, and (3) how have the effect of interventions been measured? The purpose of answering these questions was to propose methods for assessing systems thinking interventions. The analysis of systems thinking interventions in the classroom yielded an initial set of guidelines for measuring and raising a persons level of systems thinking.
Public documents identify broad strategies for reducing the burden of cardiovascular disease in the U.S., but they do not specify how best to allocate limited resources. Such specific guidance is lacking in part because of gaps in data on intervention costs and effect sizes, but also because the many factors contributing to cardiovascular risk interact through pathways and stock-flow structures that defy simple calculation. The U.S. Centers for Disease Control and Prevention (with support from the National Institutes of Health) is using SD modeling to better understand these complexities and to evaluate potential intervention strategies in terms of their impacts on adverse events and costs over the coming decades. The project considers interventions that might be undertaken at a city or county level, including interventions to improve health care, physical activity, nutrition, mental health, tobacco control, and indoor and outdoor air quality. Construction of the model has involved working with subject matter experts as well as collaborating with the Austin/Travis County, Texas, health department, which has gathered a broad spectrum of local data on population health and interventions over the past several years. This collaborative effort is helping to translate the science of cardiovascular disease into a form that is policy relevant and that can help many communities do a better job of allocating their public health resources.