Integrating group Delphi, analytic hierarchy process and dynamic fuzzy cognitive maps for a climate warning scenario

Purpose - The purpose of this paper is to present the common use of Delphi method, analytic hierarchy process (AHP) and dynamic fuzzy cognitive maps (DFCM) for development of future scenarios in correlation with climate warnings. Design/methodology/approach - The developed global model is based on a cognitive map composed of 28 factors. Among these factors two are independent, namely human consciousness and living standard. These two factors represent the most important levers of control within the designed model. Two approaches to scenario development have been applied, so that the comparison of the results between conventional fuzzy method and dynamic fuzzy method could give some further insights about global climate development and sustainability, as well as about differences between the two approaches. Findings - Results of the first model (no-time-delay in cause-effect relation) show that in general there is no absolute convergence to a single vector C(tn + 1) for various initial values for C(0). But an interesting phenomenon of cyclical convergence of the model was observed, which coincides with the empirical research results that observe cycles in the climate change awareness and environmental impact. In the second model, time-delay in the adjacency matrix was considered during the iteration. An interesting phenomenon of cyclical convergence of this model was observed as well. In two antimetric cases the authors have observed the phenomenon of two cycles, where the second, final cycle is developing after the occurrence of the first. Practical implications - The paper can be of interest for foresight practitioners and policy makers who want to employ a hybrid approach to scenario development and use it as a learning device. Originality/value - The paper presents a different approach, based on dynamic fuzzy cognitive maps, to future scenarios development related to climate warning.