Dwindling government resources and demands for increased accountability have challenged nonprofit organizations to meet their primary missions while also creating efficient and effective back-office accounting and information systems. Even though many nonprofits say that accounting and information support systems are mission-critical, they tend to staff these systems weakly and to be less efficient than they could be. The present paper uses a system dynamics model to show how the Limits to Growth and Shifting the Burden systems archetypes help explain this situation. The model runs show that the exercise of leadership is the underlying issuenonprofit managers must challenge organizational cultures and mindsets that act as limiting factors, causing the nonprofits to avoid implementing fundamental solutions to their problems. The paper discusses several action recommendations.
This study reports of an experimental economics analysis of the new proposed Swedish-Norwegian tradable green certificate market (TGC). The green certificate market is a financial instrument to stimulate renewables within the context of liberalized, transnational electricity markets (a kind of market-oriented subsidy scheme). Green certificates are financial assets issued to green producers that can be traded freely. Previous system dynamics studies showed that trading- and investment behaviour were critical factors in analyzing the market dynamics. As a follow-up, this experimental economics study conducted 14 laboratory experiments with about 10 to 20 students per session. A particular feature is that participants handle both short-term trading and long-term investments, which allow us to analyze the interplay between these types of decisions without imposing behavioural assumptions on the model. The laboratory experiment shows that the market is likely to crash, due to the long time delays of supply side adjustment. The study provided new insights concerning agents trading and investment strategies, in particular the performance of various market designs. The mix of trading strategies employed in response to the experiments, are difficult to understand and capture in an SD model.
The paper describes a system dynamics model developed for dynamic analysis of human resource for the agricultural sector in different sources of employment, viz., government, private (including corporate), academic, financial institutes, non-governmental organizations, self employment, and others in India. Besides projecting an overall scenario for continuation of current agricultural education policy and trends, the paper analyses simulated results from the model for the current curriculum with 80:20 proportion of technical to soft skills. The analysis shows that in the coming years the private sector will emerge as a major employer for the graduates of agriculture and allied sciences.
Following several calls for participation in environmental policy, an increasing attention is being dedicated to the development of deliberative platforms for the sustainable governance of our global village. In this paper, we start by adding perspective on the role of participatory modeling within a strong participatory vision for sustainability. We then explore how system dynamics and ecological economics worldviews interlock in promoting participatory modeling approaches to environmental decision-making. Focusing on the synergies between group model-building and mediated modeling, some lessons from two participatory interventions developed in Portugal are extracted. The evaluation of the case studies indicates positive outcomes at the individual and group level, with respect to learning, reaction, commitment, communication and consensus. The outcomes at the organizational level are still more limited. Further research is suggested on the comparison and complementarity between participatory modeling and other deliberative methods.
The planning of investments for the ports of the North Atlantic range (Hamburg, Rotterdam, Antwerp, Le Havre, Goia Tauro) face a strong growth of the market (double over the next 10 years), large economies of scale, congestion in ports and hinterland connections, and strong competition for parts of the European hinterland. Several investment strategies can be followed. The present strategy has resulted in overcapacity. Modeling allows to trace the dynamic impacts from alternative strategies.
Health care in the Netherlands presents a unique mix of governmental and private responsibilities. Costs for long-term care, expensive treatments and uninsurable care for the complete Dutch population are covered by the Exceptional Medical Expenses Act (AWBZ), administered by 32 regional offices. Every health care provider operates under a contract with the regional administration office. Once contracted services are available, insurers are obliged to reimburse providers for these services even if they are not used by clients. In the coming years part of the Dutch health care will be deregulated and several types of care will be offered under market conditions. Whereas costs for care capacity are at present reimbursed by the government, this situation might change in the future. Regional care offices in general have little insight into long-term developments in supply and demand for health care. This paper describes a system dynamics study on demand and supply for a specific type of nursing care, dementia. The model shows how feedback between waiting lists and volume of different types of demand for care, leads to fluctuations in required capacity. The feared overshoot in long term nursing capacity did not materialize in model runs under a range of environmental scenarios.
Modelling the worldwide nuclear reactor park including all supply chain details, i.e. the nuclear fuel cycle, demands for an integrated nuclear energy system model which also includes feedback loops representing physical feedbacks within the system as well as, and most prominently, socio-political feedbacks in the decision-making on the various available deployment pathways for nuclear energy.
Argonne National Laboratory (ANL) started in 2000 with the development of such integrated nuclear energy system models, i.e. DYMOND and more recently DANESS. These models are based on system dynamics modelling used in various industry sectors and allowing to model the full mass-flow chain of time-varying mixes of nuclear reactor plants and associated fuel cycle options. Several other sub-models may then be coupled to the mass-flow kernel to calculate heat loads, economics, life cycle inventory, and several other parameters and feedback decision-making loops important in the assessment of nuclear energy futures.
This paper concerns a project of limited scope to study why innovations in health care often fail to be adopted and how this may be improved. The project consisted of two workshops with participants from different areas of health care. The objective was to identify factors influencing adoption of innovations, relating the factors to each other, and looking for measures to stimulate the adoption of innovations. During the first workshop, possible effects of innovations and prerequisites for adopting innovations were identified and prioritised. This resulted in draft causal loop diagrams. During the second workshop, refined diagrams were used to identify measures for stimulating the adoption of innovations. In addition, a game incorporating the results of the workshops was developed. The main causal mechanisms were translated into the game which can be played by people who work in health care to improve their understanding of some of the dynamics involved.
System dynamics models are being used by more and more businesses to train employees from new hires to veteran managers, communicate strategic change within the company, share mental models between stakeholders and align business perspectives between business units. Advances in computer technologies help this process to a great extent by enabling users to interact with models more effectively and efficiently. This workshop will introduce you to ExTrain(r), one such technology that facilitates the use of simulation models in strategy communication and management training.
The ExTrain(r) is a web-based application platform that serves as a virtual practice field for managers to exercise decision-making power under various business conditions in a risk-free environment. ExTrain(r) applications can be used in individual online simulation sessions or within a facilitated environment with interaction from trainers. Each application is also supported with a facilitation tool that allows trainers to monitor simulation progress, user performance and intervene if necessary.
In this workshop, we will introduce you to the ExTrain(r) platform and its new features from a user perspective. You will also get a chance to learn more about the integration and maintenance of simulation models within ExTrain(r) environment. There will also be a hands-on demonstration of the system where participants will take part in a sample war-game application. Participants will be divided into four teams, each of which will take control of a virtual technology company. Starting on level ground, you will compete for revenue growth while maximizing profit through various business decisions. Facilitation will be provided to help you understand the key business dynamics and formulate your strategy.
This paper describes the process of a combined system dynamics modeling and scenario planning approach. It empirically investigates how envisioning and probing system dynamic modeling has the potential to raise effectiveness of scenario planning for organizational learning and improved decision making. The approach is illustrated by means of a case study that was used to explore the influence of social trends on dynamic interactions between transport behavior and spatial development in Switzerland. In this case study a system dynamics model was developed that served as a communication tool for strategy development and for enhancing goal alignment between different policy sectors at the national level. A qualitative content analysis illustrates how comments from participants of group modeling workshops can be opened up as empirical indicators of stimuli for improved learning. Additionally, it gives empirical evidence that the chosen approach contributes to mitigating four drivers of unexpected decision failure as discriminated by Chermack (2004a): bounded rationality, the tendency to consider only exogenous variables, stickiness and friction of information and knowledge, and mental model with decision premises.