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Societal ageing is a messy problem with diverging stakeholder views regarding the desirability of policy measures. In this paper, we use a System Dynamics model representing the Dutch demographic and social security system to investigate... more
Societal ageing is a messy problem with diverging stakeholder views regarding the desirability of policy measures. In this paper, we use a System Dynamics model representing the Dutch demographic and social security system to investigate if and when Dutch governmental retirement and healthcare contributions become unaffordable. Following the Robust Decision Making approach, we then design and test policies for reducing the societal costs of ageing, taking into account societal support for these policies. We find that unaffordable societal ageing costs are mainly caused by declining productivity levels and increasing life expectancy: permanent increases in productivity are required to sustain the current social security level. We also find that the recently adopted Dutch retirement age policy is insufficiently robust and that focusing on increasing the actual instead of the formal retirement age may generate more public support. Copyright © 2015 John Wiley & Sons, Ltd.
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Research Interests: Business, Entrepreneurship, Economics, Technology, Renewable Energy, and 13 moreInnovation Policy, Biomass, Energy Policy, Combustion, Multidisciplinary, Transitions, Conceptual Model, Infrastructures, Energy transition, Action (Physics), Taverne, Interaction Pattern, and Technological Forecasting and Social Change
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Background: The current outbreak of the Ebola Virus (EBOV) is characterized by inadequate intervention capacities. In this theoretical paper, we research what the influence of limitations in the intervention capacity are on the effective... more
Background: The current outbreak of the Ebola Virus (EBOV) is characterized by inadequate intervention capacities. In this theoretical paper, we research what the influence of limitations in the intervention capacity are on the effective reproduction number, and what the effectiveness would be of a more proactive approach in expanding the intervention capacities. Methodology: We use a transmission model extended with dynamical intervention capacities of isolation, health workers, tracing officers, and eventually vaccines. We generate a set of plausible scenarios explaining the current reported Ebola Virus Disease (EVD) cases taking into account a bandwidth for potential underreporting. We use these scenarios to test the effectiveness of a more proactive approach in extending intervention capacities. Results and conclusions: We show that a reactive approach in extending intervention capacities leads to under-capacity for isolating EVD cases. This under-capacity can lead to a signific...
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Static input-oriented sampling approaches are often used for generating model-based scenarios. However, for models of deeply uncertain and dynamically complex issues, there is no guarantee that such approaches reveal the total behavioral... more
Static input-oriented sampling approaches are often used for generating model-based scenarios. However, for models of deeply uncertain and dynamically complex issues, there is no guarantee that such approaches reveal the total behavioral spectrum that could be generated by simulating them. In this paper, we present an adaptive output-oriented sampling approach for exploring the full behavioral spectrum that could be generated by computational models in view of generating interesting, even previously undiscovered, scenarios. In this paper, we use a resource scarcity model to illustrate the approach, show the difference between static sampling and adaptive sampling, and demonstrate the usefulness for scenario discovery of the latter combined with other methods. We show that this approach can be used for revealing the behavioral spectrum of models, identifying regions of the input space that generate particular behaviors, and selecting (sets of) scenarios that are representative in terms of output and input spaces. We introduce adaptive sampling to explore the output spectrum of simulation models.We use roughness to characterize the dynamic complexity of transient scenarios.We show that adaptive sampling supports scenario discovery and exemplar selection.Using a resource scarcity model, we identify strengths, weaknesses/improvements.
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Due to their wicked nature, transportation issues may be efficiently dealt with by means of models. Many approaches are available for policy making, among which system dynamics. Developed for planning purposes, existing models represent... more
Due to their wicked nature, transportation issues may be efficiently dealt with by means of models. Many approaches are available for policy making, among which system dynamics. Developed for planning purposes, existing models represent the system at a macroscopic level, wherein traffic dynamics are not properly accounted for. A possible solution to cope with it consists of using a cellular approach for the network. Furthermore, recent software developments enable to model smaller-scale phenomena within a macroscopic model and make model compression possible. This paper investigates the extent to which these new developments can be applied for traffic modeling and what its advantages are compared to more conventional ones such as four-step models. The elementary building blocks are introduced and combined in order to develop a small model of interest, which is the northern section of the Great Ring (‘Grote Ring’ or ‘Grand Ring’) of Brussels. This was chosen because level of congesti...
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In this chapter, we discuss and demonstrate the use of ‘on the spot’ and ‘on the map’ scenario exploration and policy-support in workshop settings. First we justify the need for exploratory model-based policy workshops. Then we present... more
In this chapter, we discuss and demonstrate the use of ‘on the spot’ and ‘on the map’ scenario exploration and policy-support in workshop settings. First we justify the need for exploratory model-based policy workshops. Then we present some methods and techniques needed for these workshops. Special attention is paid to new techniques we believe are crucially needed for this kind of interactive workshop if time is of the essence, namely (1) techniques to quickly generate small but diverse ensembles of alternative scenarios, and (2) techniques to visualize whole-system dynamics on maps by means of geospatial animations. We subsequently describe a workshop related to the 2015–2016 European refugee crisis for which this approach and these techniques were developed and used. Finally, we discuss shortcomings and improvements to deal with these shortcomings and conclude.
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Exploring carbon futures in the EU power sector
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Many grand challenges are both dynamically complex and deeply uncertain. Combining System Dynamics with Exploratory Modeling and Analysis allows one to generate, explore, identify and analyze all sorts of plausible scenarios related to... more
Many grand challenges are both dynamically complex and deeply uncertain. Combining System Dynamics with Exploratory Modeling and Analysis allows one to generate, explore, identify and analyze all sorts of plausible scenarios related to such issues, and design and test adaptive policies over many scenarios. This paper explains and illustrates different uses of the resulting computational System Dynamics approach by means of an applied case, the outbreak of a new flu strand like the 2009 A(H1N1)n flu. First, we illustrate the use of this approach for generating and exploring different types of plausible pandemic shocks. Second, we illustrate the use of machine learning techniques to analyze contributions and effects of uncertainties, and discover and select scenarios. Finally, we illustrate the use of this approach for supporting the design of robust adaptive policies in order to be prepared for any new flu outbreak, especially those that really require action.
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Lyme disease due to infection with Lyme borreliosis poses an uncertain dynamic threat to the Dutch and their public health system. This risk was used to develop and illustrate two variants of a National Risk Assessment approaches for... more
Lyme disease due to infection with Lyme borreliosis poses an uncertain dynamic threat to the Dutch and their public health system. This risk was used to develop and illustrate two variants of a National Risk Assessment approaches for slumbering/latent risks. This paper explains and illustrates the System Dynamics-based variant using the societal risk posed by Lyme disease. Thousands of plausible evolutions of lyme disease are generated using a System Dynamics model in order to assess the societal risk posed by Lyme disease. The risk is scored in the Dutch National Risk Assessment framework adapted to deeply uncertain dynamically complex risks, and mapped in a new type of risk diagram developed for uncertain complex risks in order to compare the risk posed by Lyme disease to other plausible risks. Finally, scenario discovery techniques are used to identify a small set of representative scenarios that could be used in a capability analysis.
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Dynamically complex multi-dimensional societal issues are societal issues characterised by complex time evolutionary behaviour on multiple dimensions, and very often also by many uncertainties, multiple views and parties concerned, and... more
Dynamically complex multi-dimensional societal issues are societal issues characterised by complex time evolutionary behaviour on multiple dimensions, and very often also by many uncertainties, multiple views and parties concerned, and different ethical aspects. It will be argued here that stand-alone system dynamics often needs to be complemented with other methodologies or disciplines –for example multiple criteria decision analysis and/or ethics– in order to support the selection of appropriate strategies when dealing with such issues. This paper looks at the combination of system dynamics, multiple criteria decision analysis and ethics to support strategy selection in case of such dynamically complex multi-dimensional societal issues, with special attention paid to the capacity of the multi-methodology to deal with multiple dimensions, multiple time scales, multiple parties and views, uncertainty and
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The residential sector accounts for 30% of the total energy consumed by all sectors on average worldwide. This significant share makes an energy transition in the residential sector one of the most important frontiers of sustainability... more
The residential sector accounts for 30% of the total energy consumed by all sectors on average worldwide. This significant share makes an energy transition in the residential sector one of the most important frontiers of sustainability transitions. Netherlands aims to achieve a remarkable reduction in the energy consumption in residential buildings with policies mainly aiming at new constructions, and little attention is being paid to the existing dwelling stock. However, the existing dwelling stock creates an inertia against a transition. Although this is a widely accepted issue, the extent of such an inertia has not been analyzed explicitly. In that respect, we aim to conduct a preliminary study in order to demonstrate the importance of the existing dwelling stock, and the inertia it can cause during an energy transition process. Besides, we also aim to explore effectives of certain policy options that can alleviate this inertia. For that purpose, a simulation model is developed a...
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The meeting of the oldest profession with modern slavery is the topic of this paper. After a brief introduction to prostitution and prostitution-related human trafficking, this paper focuses on the Dutch policy debate. A System Dynamics... more
The meeting of the oldest profession with modern slavery is the topic of this paper. After a brief introduction to prostitution and prostitution-related human trafficking, this paper focuses on the Dutch policy debate. A System Dynamics simulation model related to the Dutch situation developed to explore and provide insights related to the effects of proposed policies is presented in this paper. Using the simulation model, a ‘quick and dirty’ policy analysis is first of all performed, and preliminary conclusions are drawn. These preliminary conclusions are further tested under uncertainty, using two different but relatively similar simulation models. The main conclusions are that demand side measures are necessary, but not sufficient. The topic is so complex and uncertain that simple (combinations of) basic policies will not hold in all circumstances, which is why this topic requires further exploration and policy testing under deep uncertainty.
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The main goal of this paper is to explore the transition of the EU-25 electricity generation system towards a more sustainable system characterised by lower CO2 emissions by means of a system dynamics model of the EU-25 electricity... more
The main goal of this paper is to explore the transition of the EU-25 electricity generation system towards a more sustainable system characterised by lower CO2 emissions by means of a system dynamics model of the EU-25 electricity generation sector. In this paper, the model and the resulting dynamics are explored by means of base case simulations, policy simulations, scenario analyses and (univariate and multivariate) sensitivity analyses. Finally, some conclusions, ex-post criticisms and directions for future research are discussed.
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Radicalization and deradicalization are deeply uncertain dynamic processes. Exploring and analyzing many plausible futures and assessing the robustness of policies to reinforce desirable evolutions seem more useful for such processes than... more
Radicalization and deradicalization are deeply uncertain dynamic processes. Exploring and analyzing many plausible futures and assessing the robustness of policies to reinforce desirable evolutions seem more useful for such processes than trying to predict their precise development over time and optimize the associated policy response. This paper illustrates how the combination of System Dynamics Modeling and Exploratory Modeling and Analysis could be helpful for exploration and decision making in case of deeply uncertain dynamic issues such as de/radicalization processes. In this paper, different System Dynamics models about radical and non-radical activism are presented and analyzed, both separately and jointly, but always under deep uncertainty. The different models are treated as alternative dynamic assumptions about how/why activism may become more or less extremist/harmful. These dynamic assumptions are included as structural/model uncertainties and are combined with many othe...
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This paper presents a small exploratory System Dynamics model related to the dynamics of the 2009 flu pandemic, also known as the Mexican flu, swine flu, or A(H1N1)v. The model was developed in May 2009 in order to quickly foster... more
This paper presents a small exploratory System Dynamics model related to the dynamics of the 2009 flu pandemic, also known as the Mexican flu, swine flu, or A(H1N1)v. The model was developed in May 2009 in order to quickly foster understanding about the possible dynamics of this new flu variant and to perform rough-cut policy explorations. Later, the model was also used to further develop and illustrate the use of Exploratory System Dynamics models as scenario generators for Exploratory Modelling and Analysis. The paper starts with an introduction to, and a description of, the exploratory System Dynamics model, followed by a discussion of plausible behaviours, sensitivity, what-if and policy analyses. The model is subsequently used to illustrate the Exploratory System Dynamics Modelling and Analysis approach: base case behaviours are discussed, followed by sensitivity, what-if and policy analyses. Finally some concluding remarks and policy recommendations are formulated.
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System Dynamics (SD) is a method to describe, model, simulate and analyze dynamically complex issues and/or systems in terms of the processes, information, organizational boundaries and strategies. Quantitative SD modeling, simulation and... more
System Dynamics (SD) is a method to describe, model, simulate and analyze dynamically complex issues and/or systems in terms of the processes, information, organizational boundaries and strategies. Quantitative SD modeling, simulation and analysis facilitates the (re)design of systems and design of control structures (Wolstenholme 1990). SD is in fact the application of the principles and techniques of control systems to organizational and social-economic-environmental-. . . problems. SD starts from the assumption that the behavior of a system is largely caused by its own structure. System structure consists of physical and informational aspects as well as the policies and traditions important to the decision-making process in a system (Roberts 1988). Hence, in order to improve undesirable behaviors, the structure of the system needs to be changed. SD allows to identify desirable system changes and test them in a ‘virtual laboratory’. The SD approach was developed at the end of the ...
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In this ever more complex, interconnected, and uncertain world, leadership is needed more than ever. But the literature and most leaders largely ignore dynamic complexity and deep uncertainty: only futures characterized by ever faster... more
In this ever more complex, interconnected, and uncertain world, leadership is needed more than ever. But the literature and most leaders largely ignore dynamic complexity and deep uncertainty: only futures characterized by ever faster change, ever more (required) flexibility, and ever more scarcity (especially in terms of highly qualified human resources) are taken into account. Plausible consequences of dynamic complexities and deep uncertainties are ignored and robustness of strategies for dealing with many different futures is hardly ever considered. But what if this future does not materialize? This paper describes a System Dynamics-based leadership flight simulator and the experiential serious gaming workshop it was tailor-made for. During the first part of the workshop, participants play the part of the leader of an organization but in rather different virtual worlds (scenarios) in order to experience the impact of long-term dynamic complexity and deep uncertainty on leadershi...