The complexity, multidimensionality, and persistence of the COVID-19 pandemic have prompted both researchers and policymakers to turn to transdisciplinary methods in dealing with the wickedness of the crisis. While there are increasing calls to use systems thinking to address the intricacy of COVID-19, examples of practical applications of systems thinking are still scarce. We revealed and reviewed eight studies which developed causal loop diagrams (CLDs) to assess the impact of the COVID-19 pandemic on a broader socioeconomic system. We find that major drivers across all studies are the magnitude of the infection spread and government interventions to curb the pandemic, while the most impacted variables are public perception of the pandemic and the risk of infection. The reviewed COVID-19 CLDs consistently exhibit certain complexity patterns, for example, they contain a higher number of two- and three-element feedback loops than comparable random networks. However, they fall short in representing linear complexity such as multiple causes and effects, as well as cascading impacts. We also discuss good practices for creating and presenting CLDs using the reviewed diagrams as illustration. We suggest that increasing transparency and rigor of the CLD development processes can help to overcome the lack of systems thinking applications to address the challenges of the COVID-19 crisis.
The complexity, multidimensionality, and persistence of the COVID-19 pandemic have prompted both researchers and policymakers to turn to transdisciplinary methods in dealing with the wickedness of the crisis. While there are increasing calls to use systems thinking to address the intricacy of COVID-19, examples of practical applications of systems thinking are still scarce. We revealed and reviewed eight studies which developed causal loop diagrams (CLDs) to assess the impact of the COVID-19 pandemic on a broader socioeconomic system. We find that major drivers across all studies are the magnitude of the infection spread and government interventions to curb the pandemic, while the most impacted variables are public perception of the pandemic and the risk of infection. The reviewed COVID-19 CLDs consistently exhibit certain complexity patterns, for example, they contain a higher number of two- and three-element feedback loops than comparable random networks. However, they fall short in representing linear complexity such as multiple causes and effects, as well as cascading impacts. We also discuss good practices for creating and presenting CLDs using the reviewed diagrams as illustration. We suggest that increasing transparency and rigor of the CLD development processes can help to overcome the lack of systems thinking applications to address the challenges of the COVID-19 crisis.
The future of the Arctic region is a subject of heated debates in both scientific and policy circles. The region has an enormous economic potential as a storehouse of mineral resources and as a provider of shorter and more cost-effective transportation between Europe and Asia. The Arctic is therefore an essential strategic element of the domestic and foreign policies of all Arctic states. In addition, there is an increasing economic interest in the region on the part of non-Arctic states. However, at present, the future of the Arctic region development remains highly uncertain. Scenario building is a suitable methodology to imagine alternative plausible futures of such a complex and multi-dimensional process and to elaborate successful and robust development strategies. This paper provides an overview of the scenario frameworks of Arctic futures presented in the literature and analyses key factors that determine these scenarios. Overall, we find a growing interest of the international foresight research community in the Arctic region that is evident from a number of thorough scenario-building exercises published recently. At the same time, we observe two drawbacks. First, the existing studies lack a numerical element, that is, the overwhelming majority of the scenario frameworks that can be found in the literature are fully qualitative. Quantitative estimates would strengthen the scenario narratives and enrich communication, which make them a useful addition to support a qualitative scenario framework. Second, the existing studies use a mixture of both internal and external factors to describe the underlying uncertainty. This limits the number of factors that can be taken into consideration and may be confusing for a potential user of these scenario frameworks due to the lack of a systemic view. Such a confusion can happen, for example, if some of the external factors underpinning a particular scenario suddenly develop in a direction that was not anticipated within the scenario framework. The effect of such a change on the set of scenarios and the validity of the scenarios despite this change will be of interest to the user, and a clear systems perspective would be conducive to address these questions. Separating internal and external factors in a scenario building exercise is particularly useful given that the volatility of the global geopolitical, geoeconomic and environmental dynamics is only increasing. It is our intention to address these two drawbacks in a scenario building exercise within the "Emerging trade routes between Europe and Asia" scenario-building project led by IIASA within the Northern Dimension Institute (NDI) Think Tank Action co-funded by the European Union and coordinated by Aalto University, Finland.
The future of the Arctic region is a subject of heated debates in both scientific and policy circles. The region has an enormous economic potential as a storehouse of mineral resources and as a provider of shorter and more cost-effective transportation between Europe and Asia. The Arctic is therefore an essential strategic element of the domestic and foreign policies of all Arctic states. In addition, there is an increasing economic interest in the region on the part of non-Arctic states. However, at present, the future of the Arctic region development remains highly uncertain. Scenario building is a suitable methodology to imagine alternative plausible futures of such a complex and multi-dimensional process and to elaborate successful and robust development strategies. This paper provides an overview of the scenario frameworks of Arctic futures presented in the literature and analyses key factors that determine these scenarios. Overall, we find a growing interest of the international foresight research community in the Arctic region that is evident from a number of thorough scenario-building exercises published recently. At the same time, we observe two drawbacks. First, the existing studies lack a numerical element, that is, the overwhelming majority of the scenario frameworks that can be found in the literature are fully qualitative. Quantitative estimates would strengthen the scenario narratives and enrich communication, which make them a useful addition to support a qualitative scenario framework. Second, the existing studies use a mixture of both internal and external factors to describe the underlying uncertainty. This limits the number of factors that can be taken into consideration and may be confusing for a potential user of these scenario frameworks due to the lack of a systemic view. Such a confusion can happen, for example, if some of the external factors underpinning a particular scenario suddenly develop in a direction that was not anticipated within the scenario framework. The effect of such a change on the set of scenarios and the validity of the scenarios despite this change will be of interest to the user, and a clear systems perspective would be conducive to address these questions. Separating internal and external factors in a scenario building exercise is particularly useful given that the volatility of the global geopolitical, geoeconomic and environmental dynamics is only increasing. It is our intention to address these two drawbacks in a scenario building exercise within the "Emerging trade routes between Europe and Asia" scenario-building project led by IIASA within the Northern Dimension Institute (NDI) Think Tank Action co-funded by the European Union and coordinated by Aalto University, Finland.
As governments begin to focus their attention on national well-being, there is an increasing need for enhanced analysis tools that help understand the multifold synergies and trade-offs of policies aiming at well-being. Systems Mapping is one such systems analysis tool. To be useful for policymaking, a systems map (causal loop diagram) should reflect the actual context of the system it models. This working paper discusses further validation and analysis of the National-Well-Being System (NWS) systems map introduced (Ilmola-Sheppard et al., 2020). The original NWS systems map is enhanced in three ways: (i) quantification of the systems map components, (ii) update of the systems map structure depending on the data availability, and (iii) identification of potential leverage points in the system and attachment of responsible institutions to them. Attaching quantitative arguments to the systems map components validates them and can be seen as an intermediate step between a systems map and a system dynamics model. The structure of the systems map is updated based on the availability of viable data sources. Additionally, proxies are introduced if no suitable data sources can be found. This leads to a new version of the systems map, with the number of components reduced from 68 to 65. As the outcome of this procedure, a list of viable OECD and non-OECD data sources covering all systems map components is produced. Such quantification opens up further analysis options, e.g., quantitative assessment of the links between components of the system Identification of potential leverage points in the system and attachment of responsible institutions to them highlights the key components of the system. It offers a better understanding of where institutions might influence national well-being most effectively. In this working paper, responsible institutions in Israel and Austria are used as an example. This exemplifies the practicality of the systems map and shows how a systems map can be adapted to the governmental structure of a country. By identifying data sources behind every component of the systems map, revising the map based on the availability of data, and identifying leverage points as well as possible responsible institutions and decision-makers, this working paper improves on the NWS systems map and highlights its potential to serve as a policy simulation tool.
As governments begin to focus their attention on national well-being, there is an increasing need for enhanced analysis tools that help understand the multifold synergies and trade-offs of policies aiming at well-being. Systems Mapping is one such systems analysis tool. To be useful for policymaking, a systems map (causal loop diagram) should reflect the actual context of the system it models. This working paper discusses further validation and analysis of the National-Well-Being System (NWS) systems map introduced (Ilmola-Sheppard et al., 2020). The original NWS systems map is enhanced in three ways: (i) quantification of the systems map components, (ii) update of the systems map structure depending on the data availability, and (iii) identification of potential leverage points in the system and attachment of responsible institutions to them. Attaching quantitative arguments to the systems map components validates them and can be seen as an intermediate step between a systems map and a system dynamics model. The structure of the systems map is updated based on the availability of viable data sources. Additionally, proxies are introduced if no suitable data sources can be found. This leads to a new version of the systems map, with the number of components reduced from 68 to 65. As the outcome of this procedure, a list of viable OECD and non-OECD data sources covering all systems map components is produced. Such quantification opens up further analysis options, e.g., quantitative assessment of the links between components of the system Identification of potential leverage points in the system and attachment of responsible institutions to them highlights the key components of the system. It offers a better understanding of where institutions might influence national well-being most effectively. In this working paper, responsible institutions in Israel and Austria are used as an example. This exemplifies the practicality of the systems map and shows how a systems map can be adapted to the governmental structure of a country. By identifying data sources behind every component of the systems map, revising the map based on the availability of data, and identifying leverage points as well as possible responsible institutions and decision-makers, this working paper improves on the NWS systems map and highlights its potential to serve as a policy simulation tool.
Kyrgyzstan is facing a strategically important period in its history. The government's ambition of reindustrializing is affecting its engagement with various international organizations and donors. As these plans will lead to societal transition and affect such areas as social development, national economy, and environment, a careful consideration of their impacts is required, especially given the country's need to achieve sustainable development. At the same time, the geographical position of Kyrgyzstan puts it at the cross-roads of three distinct regional economic connectivity processes: the Eurasian Economic Union (EAEU), the China-led Belt and Road Initiative (BRI), and various connectivity initiatives and projects taking place under the umbrella of the European Union (EU). A major issue is the extent to which Kyrgyzstan can leverage these processes to boost its economic revitalization plans and decarbonize its economy in line with international climate change mitigation and energy security policies, while ensuring a reliable energy supply. As a result, novel governance mechanisms need to be established that address the possible impacts of these economic connectivity processes; this is especially important given the frequently diverging perceptions and opinions of the various Kyrgyz and foreign stakeholders involved in industrial policymaking. Perceptual heterogeneity influences the development of solutions based on compromise and participatory governance that are crucial to implementing different industrial policy options; it also impacts the nature of the economic relationship between Kyrgyzstan and other countries in the Central Asian region. The aim of this paper is to understand the implications of perceptual heterogeneity for the various connectivity processes in Kyrgyzstan, their benefits, and their impacts. The methodology of this paper includes a variety of methods such as surveys and interviews with key stakeholders, scenario development, and participatory workshops in various regions of the ...
Kyrgyzstan is facing a strategically important period in its history. The government's ambition of reindustrializing is affecting its engagement with various international organizations and donors. As these plans will lead to societal transition and affect such areas as social development, national economy, and environment, a careful consideration of their impacts is required, especially given the country's need to achieve sustainable development. At the same time, the geographical position of Kyrgyzstan puts it at the cross-roads of three distinct regional economic connectivity processes: the Eurasian Economic Union (EAEU), the China-led Belt and Road Initiative (BRI), and various connectivity initiatives and projects taking place under the umbrella of the European Union (EU). A major issue is the extent to which Kyrgyzstan can leverage these processes to boost its economic revitalization plans and decarbonize its economy in line with international climate change mitigation and energy security policies, while ensuring a reliable energy supply. As a result, novel governance mechanisms need to be established that address the possible impacts of these economic connectivity processes; this is especially important given the frequently diverging perceptions and opinions of the various Kyrgyz and foreign stakeholders involved in industrial policymaking. Perceptual heterogeneity influences the development of solutions based on compromise and participatory governance that are crucial to implementing different industrial policy options; it also impacts the nature of the economic relationship between Kyrgyzstan and other countries in the Central Asian region. The aim of this paper is to understand the implications of perceptual heterogeneity for the various connectivity processes in Kyrgyzstan, their benefits, and their impacts. The methodology of this paper includes a variety of methods such as surveys and interviews with key stakeholders, scenario development, and participatory workshops in various regions of the ...
Industrial development is often considered to be a major engine of economic growth. Kyrgyzstan is an open, small, landlocked, developing economy in Central Asia. In 2018 the Government of Kyrgyzstan decided to elaborate a new industrial development strategy that would facilitate economic growth, reduce the country's dependence on foreign financing, and increase the welfare of inhabitants. This paper presents a set of plausible scenarios of industrial development of Kyrgyzstan to 2040. The scenarios were used as a basis for a Strategy for the Sustainable Development of Industry in Kyrgyzstan for 2019–2023, prepared by co-authors of this paper in collaboration with local experts in 2018. This strategy was officially adopted by the Government of Kyrgyzstan in September 2019. To construct scenarios, we used an approach developed by Roland Berger and Leipzig Graduate School of Management (HHL) Center for Strategy and Scenario Planning within the Intuitive Logics scenario planning paradigm. This approach relies on a systematic step-by-step scenario-building process that can be carried out when time and resources are limited. We augmented this approach by revealing and utilizing causal relationships among drivers. We also considered a denser spectrum of scenarios. The outcomes of each scenario-planning step were validated in consultations with local stakeholders. We also designed a monitoring dashboard based on well-established publicly available development indicators. These can help policymakers identify which scenario the system under consideration is tending toward, so that necessary policy interventions can be executed in a timely manner.
Industrial development is often considered to be a major engine of economic growth. Kyrgyzstan is an open, small, landlocked, developing economy in Central Asia. In 2018 the Government of Kyrgyzstan decided to elaborate a new industrial development strategy that would facilitate economic growth, reduce the country's dependence on foreign financing, and increase the welfare of inhabitants. This paper presents a set of plausible scenarios of industrial development of Kyrgyzstan to 2040. The scenarios were used as a basis for a Strategy for the Sustainable Development of Industry in Kyrgyzstan for 2019–2023, prepared by co-authors of this paper in collaboration with local experts in 2018. This strategy was officially adopted by the Government of Kyrgyzstan in September 2019. To construct scenarios, we used an approach developed by Roland Berger and Leipzig Graduate School of Management (HHL) Center for Strategy and Scenario Planning within the Intuitive Logics scenario planning paradigm. This approach relies on a systematic step-by-step scenario-building process that can be carried out when time and resources are limited. We augmented this approach by revealing and utilizing causal relationships among drivers. We also considered a denser spectrum of scenarios. The outcomes of each scenario-planning step were validated in consultations with local stakeholders. We also designed a monitoring dashboard based on well-established publicly available development indicators. These can help policymakers identify which scenario the system under consideration is tending toward, so that necessary policy interventions can be executed in a timely manner.
Environmental modelling is a commonly used tool to assist the policy dimension of sustainability problems. Model evaluation is an important process in such decision-making contexts to ensure credibility, and it is often considered a purpose-dependent activity. Models are increasingly used for the purpose of scenario generation to deal with non-probabilistic uncertainties. This change in the model purpose implies a change in the evaluation process, and may require different validation techniques. In this paper, we investigate the existing validation viewpoints and approaches, and compare the general modeling context to the scenario generation purpose in particular. We employ three methods for this investigation: (i) A literature review about validation in environmental modeling, (ii) a text-mining analysis on a large dataset of validation-related publications, and (iii) an online survey conducted among model developers and users in academia, governmental and non-governmental policy organizations, and industry. The results indicate a data-orientation for systematic validation, and that conventional validation approaches are adopted even for models used for the purpose of scenario exploration. Future studies can develop a validation framework for models used specifically for generating scenarios and decision-making under non-probabilistic uncertainty.
Environmental modelling is a commonly used tool to assist the policy dimension of sustainability problems. Model evaluation is an important process in such decision-making contexts to ensure credibility, and it is often considered a purpose-dependent activity. Models are increasingly used for the purpose of scenario generation to deal with non-probabilistic uncertainties. This change in the model purpose implies a change in the evaluation process, and may require different validation techniques. In this paper, we investigate the existing validation viewpoints and approaches, and compare the general modeling context to the scenario generation purpose in particular. We employ three methods for this investigation: (i) A literature review about validation in environmental modeling, (ii) a text-mining analysis on a large dataset of validation-related publications, and (iii) an online survey conducted among model developers and users in academia, governmental and non-governmental policy organizations, and industry. The results indicate a data-orientation for systematic validation, and that conventional validation approaches are adopted even for models used for the purpose of scenario exploration. Future studies can develop a validation framework for models used specifically for generating scenarios and decision-making under non-probabilistic uncertainty.
The Swedish wolf population has rebounded from near extinction in the 1960s to around 365 individuals in 2020, after the implementation of the Hunting Act (jaktlagen) in 1966. This recent increase in the wolf population has evoked a serious divide between "pro-wolf" and "anti-wolf" Swedish citizens. Despite the continuous efforts by the Swedish government to reconcile this antagonism, the conflicts are persistent with a sign of impasse. In this paper, we present a modelling tool, which can bring transparent and "structured dialogue to the opposing positions." This approach includes a stylized framework for quantitative modelling of stakeholders' satisfaction levels regarding their preferred size of the wildlife population in question, based on the concept of satisfaction functions. We argue that this framework may contribute to conflict resolution by bringing a common understanding among stakeholders, facilitate a societal discourse, and potentially help to assess likely support for conservation policies. We present a showcase application of this modeling tool in the context of the conflict over the Swedish wolf conservation policies. The model is informed using a thorough literature review as well as interviews, which identified relevant stakeholder groups and respective drivers of their attitudes towards wolves.
The Swedish wolf population has rebounded from near extinction in the 1960s to around 365 individuals in 2020, after the implementation of the Hunting Act (jaktlagen) in 1966. This recent increase in the wolf population has evoked a serious divide between "pro-wolf" and "anti-wolf" Swedish citizens. Despite the continuous efforts by the Swedish government to reconcile this antagonism, the conflicts are persistent with a sign of impasse. In this paper, we present a modelling tool, which can bring transparent and "structured dialogue to the opposing positions." This approach includes a stylized framework for quantitative modelling of stakeholders' satisfaction levels regarding their preferred size of the wildlife population in question, based on the concept of satisfaction functions. We argue that this framework may contribute to conflict resolution by bringing a common understanding among stakeholders, facilitate a societal discourse, and potentially help to assess likely support for conservation policies. We present a showcase application of this modeling tool in the context of the conflict over the Swedish wolf conservation policies. The model is informed using a thorough literature review as well as interviews, which identified relevant stakeholder groups and respective drivers of their attitudes towards wolves.
Policymakers are confronted with hard-to-address questions, such as • What is the ultimate impact of very different policies on the well-being of citizens? • How to anticipate, which policies will promote well-being the most and which ones will lead to tough trade-offs? • How to focus scarce resources and maximize the positive impact on the well-being of citizens? Economic growth is ceasing down, and, moreover, in most of the developed countries additional growth does not promote the well-being of citizens as much as it used to. But what is well-being? According to a dictionary, well-being is a state of feeling happy, healthy or prosperous. In 1980s, a group of sociologists, philosophers and economists led by Amartya Sen and Martha Nussbaum suggested a framework to understand well-being beyond the economic indicators , such as the GDP. In fact, in the modern world, wellbeing itself becomes a prerequisite for economic growth and for social and economic stability. Governments begin to focus their attention directly on the multi-dimensional national well-being including and going beyond economic and material aspects. They look for new under-utilized resources that would raise the national well-being even despite weak economic growth. To discover effective and efficient solutions, one needs to maximize synergies and reduce losses from trade-offs . Systems analysis offers tools to do so. This challenge was presented to the International Institute for Applied Systems Analysis (IIASA) by the National Economic Council of Israel in 2018. In response, IIASA developed a pilot version of a systems description of the national well-being system that covers four major subsystems: economic subsystem, natural subsystem, human capacity subsystem, and social subsystem, each described by a set of indicators. This Working Paper presents the results of this pilot work. We rely on the OECD well-being framework as a basis to measure multi-dimensional well-being and work with 68 factors, of which 39 represent the OECD indicators. Based on evidence we collate from solid scientific literature, we connect these 68 factors by causal relationships and obtain a comprehensive systems map of the National Well-being System (NWS) (a causal loop diagram) comprising 208 directed links between factors. This systems map allows to trace all indirect effects and feedback loops between factors in a systematic fashion thus helping acquire a holistic understanding about the national well-being system. Empirical evidence clearly indicates that systems thinking is difficult to practice when causal interconnections become more complex, especially when it involves indirect effects and feedback loops. As a formal tool from qualitative systems analysis, our NWS map can assist policymakers to reveal trade-offs and synergies, reduce the problem's "wickedness" and discipline a dialogue. This version 1.0 can and should be developed further. This includes expert validation and fine-tuning, as well as customizing it to particular national and policy contexts. Eventually, our ambition is to develop a policy simulation tool that enables comparison of different policy options and their ultimate impact on well-being. We invite interested parties to join us in this endeavour!
