Birgit Kopainsky

A system dynamics approach for examining mechanisms and pathways of food supply vulnerability

Understanding vulnerabilities in complex and interdependent modern food systems requires a whole-system perspective. This paper demonstrates how one systems approach, system dynamics, can help conceptualize the mechanisms and pathways by which food systems can be affected by disturbances. We describe the process of creating stock-and-flow maps and causal loop diagrams from the graphical representation of a problem and illustrate their use for making links and feedback among the human health, food, and environmental health sectors visible. These mapping tools help structure thinking about where and how particular systems might be affected by different disturbances and how flows of material and information transmit the effects of disturbances throughout the system. The visual representations as well as the process of creating them can serve different purposes for different stakeholders: developing research questions, identifying policy leverage points, or building collaboration among people in different parts of the system. They can serve as a transition between mental models and formal simulation models, but they also stand on their own to support diagrammatic reasoning: clarifying assumptions, structuring a problem space, or identifying unexpected implications of an unplanned disturbance or an intentional policy intervention. The diagrams included here show that vulnerability of a national food system does not only or automatically result from exogenous shocks that might affect a country. Rather, vulnerability can be either intensified or reduced by the interaction of feedback loops in the food system, and buffered or amplified by the structure of stocks and flows.

A Blend of Planning and Learning: Simplifying a Simulation Model of National Development

Simulation models provide decision support to long-term planning processes. The Bergen Learning Environment for National Development (BLEND) is a game based on a simplified version of Millennium Institutes Threshold 21 model (T21) that sensitizes policy makers in sub-Saharan African nations to the need for simulation-based decision support. The simplification eliminates or aggregates details about individual policy sectors and maintains cross-sector relationships. Validation indicates that the full and the simplified T21 model generate very similar behavior patterns for a wide range of policy scenarios. Pilot tests demonstrate that the simplified T21 model contributes to the learning goals of BLEND. The debriefing employs causal loop diagrams and simulation for structural explanations of the behavior observed during the game. BLEND workshops with repeated runs of the game, full debriefing sessions and different formats of instructional support will contribute further to research on dynamic decision making and learning about tasks with great complexity.

Effect of Prior Exploration as an Instructional Strategy for System Dynamics

In complex simulation-based learning environments, participants’ learning and performance may suffer due to demands on their cognitive processing, their struggle to develop adequate mental models, failure to transfer what is learned to subsequent learning or activities, and fear of failure. This study investigates an instructional strategy addressing those four problems, which we call prior exploration strategy. It was implemented in a simulation requiring participants to optimize a developing nation’s per capita income. The prior exploration strategy allows participants to manipulate and see the results of a simulation model in practice mode before they manage a similar simulation in a more final mode. The strategy was assessed in an experiment comparing participants using the prior exploration strategy with participants studying equivalent content in a non-exploratory fashion. The dependent variables were performance within the simulation and improvement of participants’ understanding. The prior exploration strategy significantly improved participants’ performance, as measured by per capita income. It also significantly improved some aspects of the participants’ understanding (e.g., their understanding of the nation’s debt accumulation), but not others (e.g., their understanding of the need to balance the nation’s health, education, and infrastructure investments; those that appear to have complex interrelations).

Application of the Malaria Management Model to the Analysis of Costs and Benefits of DDT versus Non-DDT Malaria Control

Introduction DDT is considered to be the most cost-effective insecticide for combating malaria. However, it is also the most environmentally persistent and can pose risks to human health when sprayed indoors. Therefore, the use of DDT for vector control remains controversial. Methods In this paper we develop a computer-based simulation model to assess some of the costs and benefits of the continued use of DDT for Indoor Residual Spraying (IRS) versus its rapid phase out. We apply the prototype model to the aggregated sub Saharan African region. For putting the question about the continued use of DDT for IRS versus its rapid phase out into perspective we calculate the same costs and benefits for alternative combinations of integrated vector management interventions. Results Our simulation results confirm that the current mix of integrated vector management interventions with DDT as the main insecticide is cheaper than the same mix with alternative insecticides when only direct costs are considered. However, combinations with a stronger focus on insecticide-treated bed nets and environmental management show higher levels of cost-effectiveness than interventions with a focus on IRS. Thus, this focus would also allow phasing out DDT in a cost-effective manner. Although a rapid phase out of DDT for IRS is the most expensive of the tested intervention combinations it can have important economic benefits in addition to health and environmental impacts that are difficult to assess in monetary terms. Those economic benefits captured by the model include the avoided risk of losses in agricultural exports. Conclusions The prototype simulation model illustrates how a computer-based scenario analysis tool can inform debates on malaria control policies in general and on the continued use of DDT for IRS versus its rapid phase out in specific. Simulation models create systematic mechanisms for analyzing alternative interventions and making informed trade offs.

System Dynamics and Simulation/Gaming

Purpose. This article summarizes the nine contributions to the symposium on system dynamics. The goal of the symposium is to investigate how research in system dynamics is contributing to simulation-gaming, and how the more general field of simulation-gaming is influencing work in system dynamics. Summary of articles. We summarize the nine contributions. They include five articles on basic research in learning and teaching principles for system dynamics, three articles on interactive learning environments, and a final critical reflection article which summarizes the other eight and suggests future research needs. Conclusion. The main problem still to be addressed is improvement in and measurement of learning and performance.

Systems Education at Bergen

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.

Learning about Dynamic Problems with Computer Simulators: A Case of System Dynamics Simulation Models

A vast body of research shows that people by and large fail to understand and manage dynamic environments. Given the increasing complexity of our world, there is an urgent need to develop more effective ways to present dynamic problems. Many studies propose computer simulators as virtual learning environments to help people understand and manage complex problems. Still, experimental data show that simulators often carry problems from reality into the virtual laboratory. An analysis from the perspective of cognitive load theory suggests that learning about complex problems could be improved by enhancing descriptions with simulation elements that would facilitate interactive exploration of the problem dynamics. We develop such an applet, featuring dynamics generated by a non-linear accumulation rate and review experimental results testing its effectiveness.

Effects of Structural Transparency in System Dynamics Simulators on Performance and Understanding

Prior exploration is an instructional strategy that has improved performance and understanding in system-dynamics-based simulators, but only to a limited degree. This study investigates whether model transparency, that is, showing users the internal structure of models, can extend the prior exploration strategy and improve learning even more. In an experimental study, participants in a web-based simulation learned about and managed a small developing nation. All participants were provided the prior exploration strategy but only half received prior exploration embedded in a structure-behavior diagram intended to make the underlying model’s structure more transparent. Participants provided with the more transparent strategy demonstrated better understanding of the underlying model. Their performance, however, was the equivalent to those in the less transparent condition. Combined with previous studies, our results suggest that while prior exploration is a beneficial strategy for both performance and understanding, making the model structure transparent with structure-behavior diagrams is more limited in its effect.

Participatory System Dynamics Mapping for Collaboration and Socioecological Integration in the Lake Tana Region

This chapter presents a system map of causal links and feedback loops among social and ecological components in the Lake Tana region. The map was collaboratively developed by twenty-seven regional researchers, managers, and development experts who participated in a one-day systems mapping workshop entitled “Strengthening Links between Policy and Research for Sustainable Development in the Lake Tana Basin ” held in Bahir Dar, Ethiopia in November 2014. The chapter describes the map development process, content of the map, participant perspectives on the value of the process and the workshop outcomes, and steps for building on the workshop.

Social Dynamics Overriding Utility Evaluations for Good and Bad: Implications for the Design of Sustainable Food Security Policies in Sub-Saharan African Countries

Sub-Saharan African economies depend heavily on agriculture. Seed from improved varieties and other inputs are imperative to the transformation of the agricultural sector from subsistence farming to small-scale commercial agriculture and thus to increasing food security on the continent. Farmers make the decision to adopt seed from improved varieties based on a number of seed attributes. These range from tangible attributes such as input costs and yield to intangible attributes such as trust in seed from improved varieties. In the course of adoption decisions, social dynamics involving trust can over-ride objective evaluations of tangible attributes. This makes it difficult to design sustainable adoption policies in an intuitive way. For this purpose we develop a system dynamics model and combine it with conjoint analysis. Conjoint analysis allows us to elicit smallholder farmers’ choice preferences in detail and to add precision to the structure of the model. The simulation framework helps to improve our understanding concerning the dynamic implications of accumulation processes relating to trust and skill. We test this approach with empirical data for maize in Malawi. Model simulations demonstrate that effective adoption stimulation policies should focus on measures that build trust in improved maize varieties instead of increasing their potential yield even further and in this way contribute to food security.