Quantifying qualitative information on risks: Development of the QQIR method

The method for quantifying qualitative information on risks (QQIR) bridges the gap between qualitative and quantitative risk assessment methods. It employs fuzzy set theory and results in deriving customized probability density functions (PDFs) for stochastic applications in risk assessment and financial modeling. The QQIR method uses fuzzy sets for capturing expert opinions on uncertain information and it uses the fuzzy weighted average method for aggregating that information. The aggregated opinion then is converted proportionally into a PDF with respect to the possibility-probability consistency principle and the uncertainty-invariance principle. This paper describes the construction of the proposed QQIR method and explains the underlying operations and principles used. The different competing possible methods and principles that exist in fuzzy set theory and could have been chosen for designing the QQIR method will be introduced and numerically tested in detail to determine which method best fits the purposes of making the QQIR method work. The paper refers to possible applications of the method that have been published by the writers and concludes with a summary and limitations of the QQIR method. The QQIR method is generic and has been successfully validated and applied to the impact of political risks on infrastructure projects.