Dynamic Global Vegetation Models (DGVMs) are invaluable for understanding the biosphere. However, as currently implemented by the international research community, these models suffer from a challenging accumulation of uncertainty. This project aims to address this problem by developing the foundations of a new generation of models centered on a “missing law” – adaptation and optimization principles rooted in natural selection. More
The Systemic Risk and Network Dynamics project will examine how different types of systems, ranging from financial to ecological and beyond, are at risk of cascades of failures. As well as assessing this risk, this cross-cutting project will develop tools to help prevent such events. More
This IIASA Futures Initiative deals with the complex issues of economic cooperation between countries of the Eurasian continent. More
This research project funded through the Systems Analysis Forum (SAF) aims to better understand the interaction between labour flows and capital flows in an economy. This work will help to improve the assessment of welfare dynamics and evaluate policies that can lead to higher levels of economic welfare. More
This research project funded through the IIASA’s Systems Analysis Forum (SAF) explores methods of finding efficient, consensus-enabling solutions reconciling competing goals of diverse agents with potentially unequal bargaining positions. More
A research project which uses social simulation as a new method to examine stakeholder cognition and interaction, and explores how gaming-based empirical observations may be used in quantitative analysis. More
The Platform Value Now project funded by Finland’s Strategic Research Council focuses on understanding the fast emerging platform economic ecosystems, their value creation dynamics and requirements of the supportive institutional environment. It analyzes economic ecosystems with systems tools and develop new methods for platform-centric economic ecosystems management. More
The transition to a low carbon economy by 2050 will involve irreversible step-changes in the cultural, economic and natural domains. COMPLEX develops new modelling tools and decision-support systems to support communities across Europe working to make the transition to a low-carbon economy. More
This joint project of the National Science Foundation of China (NSFC) and the International Institute for Applied Systems Analysis (IIASA) develops an integrated methodology for investigating the interplay between urban development and ecological stress in rural mountain areas in China. More
The project, which provides policy advice to Ukraine, investigates how the complex linkages and differences between agriculture, energy, and water security can be sustainably developed and coordinated at both the spatial and temporal scales, given the potential systemic risks involved. More
This project jointly run by STEPI (Science and Technology Policy Institute, Seoul, Korea) and ASA, IIASA aims to provide foresight into possible consequences of several major shocks which may hit the economy of South Korea. More
ClimTrans2050 addresses the requirement to design and implement mitigation and adaptation measures to meet very long term greenhouse gas (GHG) emission reduction commitments. More
The objective of this 1-year, call-winning proposal is to advance our insights in retrospective learning in order to better handle (reduce?) uncertainty in prognostic scenarios; in particular, to provide a reference (standard), which is readily understandable and which prognostic modelers can use in order to inform experts as well as non-experts about the “predictive” power, and its limitation, of their models. To our knowledge, such a reference is not applied at all. More
The focus of this 2-year research is on learning, more specifically, on the spatio-temporal assessment of uncertainty in GHG emission inventories and how our knowledge increases in terms of predictability across space and time, and whether our insights into learning will eventually allow to better handle (reduce?) uncertainty in prognostic emission scenarios or, more generally, scenarios of global change. More
Monitoring resilience – Development of a software-supported method for the network-based analysis and measurement of social cohesion and resilience of critical systems using Austria as an example The inevitability of surprises is a key feature in systems thinking, and the ability to persist through disturbances is a function of resilience. This project links resilience concepts from diverse scientific disciplines to develop a measure of resilience for Austria’s critical systems. More
The research initiative aims at increasing the systemic understanding about the impact of global trends and unforeseeable shocks on the Finnish national economy and regional economies as well as producing science-based tools for practical policy planning, which will support sustainable regional growth in the volatile global environment; such planning that minimizes the need for the special corrective actions in the future and that maximizes the sustainability of regions. More
This research project focuses on analysis of resource productivity as one of the major drivers of economic growth, closely associated with environmental pressures and playing an increasingly significant role in Asia and in Latin America. More
The International Foresight Academy is the first organization to bind together Foresight activities around the globe and from contrasting cultural and political contexts. As the Mapping Report of the European Foresight Monitoring Network (2009) has documented, Foresight is used differently in various regions of the world. Foresight activities vary according to sponsors and customers, meth- ods used, topics explored, actors involved etc. They vary also with regard to their functions in political strategy formulation of modern democracies. More
Within this EU-funded project, a dynamic stochastic optimization model was proposed to support robust management of energy provision in public buildings. More
This project contributes to the theory of optimal control and to the literature on endogenous economic growth. In pursuit of this dual aim the project contains a theoretical part that develops a methodology for finding approximate solutions to the type of optimization problem formulated above and an applied part in which this methodology is used to find an optimal allocation of labor and exhaustible resource in a model of endogenous growth constrained by a non-renewable resource. More
The Project develops a cross-disciplinary modeling and assessment framework. It consists of two parts: Dream Valley simulator and A3 framework. The Dream Valley simulator simulates complex dynamical systems, while the A3 framework implements and tests methods for forecasting their future behaviors. More
Last edited: 19 June 2017
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