Developing Robust Climate Policies: A Fuzzy Cognitive Map Approach

Part of the International Series in Operations Research & Management Science book series (ISOR, volume 241)


Climate change has been considered one of the most significant risks for sustainability in our century; in order to move towards low-carbon and climate resilient economies, fundamental changes must take place. In this direction, the European Union has set ambitious goals regarding the transition of its Member States to low carbon societies, but the policy strategies to promote this transition must be socially acceptable and supported. So far, climate policies have been evaluated using quantitative methods, including general equilibrium and integrated assessment models but, despite their undoubted contribution to climate modeling, both the quantitative frameworks used for studying climate change and its impacts and those aiming at policy optimization or evaluation feature significant uncertainties and limitations. In order to overcome these issues, a Fuzzy Cognitive Map based approach is proposed, aiming to directly involve stakeholders and assess human knowledge and expertise. The suggested methodological framework can significantly support climate policy making, by supplementing quantitative models and exploring impacts of selected sets of policies, based on qualitative information deriving from a structured stakeholder engagement process. Finally, an innovative approach of incorporating the concept of time into the methodology is proposed and evaluated, in the aim of enhancing the robustness of transition pathways.


Climate Policy Threshold Function Stakeholder Engagement Dynamic Stochastic General Equilibrium Hyperbolic Tangent Function 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.



The most important part of this research is based on the H2020 European Commission Project “Transitions pathways and risk analysis for climate change mitigation and adaptation strategies—TRANSrisk” under grant agreement No. 642260. The sole responsibility for the content of this chapter lies with the authors. It does not necessarily reflect the opinion of the European Commission.


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© Springer International Publishing Switzerland 2016

Authors and Affiliations

  1. 1.School of Electrical and Computer EngineeringNational Technical University of AthensAthensGreece

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