Abstract:At the University of Bergen in Norway, educating students to use computer models and to think systemically about social and economic problems began in the 1970s. The International Masters Program in System Dynamics was established in 1995, and a Ph.D. program began a few years later. Student enrolment doubled in 2010 with the establishment of the European Master Program in System Dynamics. International diversity has been a hallmark of the Bergen program; each year, students come from about 30 different countries and more than 95% of the degrees have been awarded to students from outside of Norway. However, a Bergen systems education is not confined to a classroom in Norway. Projects in developing countries, emerging economies, and developed countries have taken the systems perspective and modeling tools on the road and, increasingly, online. Whatever the delivery mode, the goal is the same: capacity building among international students, planners and managers, and local stakeholders. This paper describes the Bergen program and its impact on systems thinking and modeling throughout the world.

The conventional method of teaching macroeconomics to undergraduates relies on static graphs, an approach with documented pedagogical problems. In contrast, the feedback method uses causal loop diagrams and interactive computer simulation models. This paper describes the feedback method and four experiments that tested its effectiveness. Two experiments examined student preferences for methods of learning macroeconomics (e.g., using static graphs or a causal loop diagram), and a significant majority preferred the feedback method. In the third experiment, students showed more understanding of GDP when they had access to a stock-and-flow feedback diagram of the economy. In the final experiment, students using causal loop diagrams displayed more understanding of business cycle dynamics than those with access to a conventional aggregate supply-and-demand graph. Searching for feedback structure in the economy and using computer simulation to connect structure with behavior appears to be a promising method for learning macroeconomics.

More often than not, system dynamics model-based public policy analysis is limited to testing parameter changes instead of designing and testing new stock-and-flow policy structures. That is problematic because improvements in behaviour require improvements in structure. This paper considers how the public policy implementation literature could improve the operational thinking skills required for designing policy structure for public sector models. A familiar model of a public health problem is used to illustrate the recommended approach. And an instructional training strategy is offered for teaching and learning to think operationally during the policy-design stage of modelling.

Global industrial metal markets have experienced a drastic price decline over the past years. In this paper we link the dynamics of raw material markets and commodity price fluctuations to a delayed adjustment of supply. Drawing on the classical cobweb theorem we show how the implementation of this theorem using system dynamics may yield a valuable explanation, not only for the recent price decline, but also for possible future price movements. Starting from a simple cobweb model of general industrial markets, we couple the price‐adjusting mechanics to the global copper market and demonstrate how a simple market model can be merged with a physical material flow model. This model captures both market dynamics and technical aspects of raw material processing, recycling and substitution and adds an explanation for the widely accepted fact that the cost structure of the copper industry cannot explain current price levels. Finally, we compare the system dynamics forecasting model with a traditional econometric forecasting method and found the system dynamics model to be more intuitive and better suited to capture and convey the structural market fundamentals. Copyright © 2017 System Dynamics Society

& Various methodologies have been used to model the epidemiology and economics of aquatic diseases, including input-output models, benefit-cost analysis, linear programming, compartment models based on differential equations, and spatial models. Despite the virtues of each of these models, there is a need to develop a more integrated approach to the epidemiology and economics of disease that better represents and captures existing feedback mechanisms that can influence the success of disease control interventions and their cost-effectiveness. In this paper, we motivate the use of system dynamics (SD) modeling in the context of sea lice control in Norwegian farmed salmon. Separate models of sea lice and salmon growth were designed and integrated to capture the feedbacks between them. Different simulation scenarios highlight the benefits of the approach. Model results indicated that changing the timing and type of treatment vis-a`-vis current practices can markedly reduce sea lice infection pressures; such simulated practices are also more cost effective. Our approach further highlights how delays and feedbacks present in these systems influence the success of any disease control protocol, and demonstrates the utility that SD models can play in aquatic health.