Providing a Framework for the Screening and Prioritisation of Decision Making Criteria using Fuzzy Delphi and Fuzzy Best-Worst Techniques

Abstract

Several techniques are utilised for screening and prioritising various criteria or items, including the Delphi technique and the analytical hierarchy process (AHP). Such techniques' calculations are dependent on expert views, however, and consequently, any error or contradiction in experts' viewpoints influences the calculation results. Although the talents and abilities of experts are employed for comparisons in classical Delphi approaches, such quantification of expert opinion cannot fully capture human thinking styles, and decision-making in the actual world must thus be enhanced by the use of fuzzy sets that operate in a manner more in line with the ambiguity and uncertainty of human thought and language. Any Analytical Hierarchical Process requires specialists to perform pairwise comparisons to make choices, and due to the huge number of criteria and potential errors connected with criteria priority decisions, it is feasible that the overall consistency will suffer as a result. Fuzzy sets are used to decrease error levels, and this study thus aimed to screen and prioritise criteria for solving complex decision-making problems by using both fuzzy Delphi and fuzzy best-worst (FBWM) techniques. Solving the multiplicity of rounds of the Delphi technique and the inconsistency produced by the AHP approaches are among the traditional difficulties associated with the Delphi method and the fuzzy best-worst method, while this paper demonstrates that the fuzzy Delphi technique can be employed to screen criteria in a single round, thus addressing the Delphi technique rounds issue, while FBWM offers solution for reducing the number of criteria comparisons.