Trapezoidal fuzzy DEMATEL method to analyze and correct for relations between variables in a composite indicator for disaster resilience

Abstract

Indicator systems of disaster vulnerability are important for monitoring and increasing the capacity in risk management. Various composite indicators have been developed to operationalize social vulnerability at national and sub-national level. Problems with relations between the sub-indicators of the composite indicator are a common phenomenon. The fuzzy Decision-Making Trial and Evaluation Laboratory (DEMATEL) method analyzes the structure of complex cause-effect relationships between the sub-indicators based on perceived direct influences. The results provide insight into the composite indicators and can be used to correct the sub-indicator weighting for relations between the sub-indicators and allow the identification of cause- and effect-group sub-indicators which is an important information for selecting mitigation measures in risk management. The fuzzy DEMATEL method is generalized to take into account trapezoidal membership functions. A composite indicator originally developed to determine the disaster resilience in US counties is adapted, operationalized and used to assess the resilience of Germany at county level using corrected weights. Resilience is highest in urban areas and in southern Germany and lowest in rural areas, in particular in eastern Germany.