Expertise-based experts importance weights in adverse judgment

The objective of this research was to propose the use of expertise levels of experts to determine the experts' importance weights since there has been no research that determines the 'importance weight' using the expertise level as a whole. The significance of this research was the integration of three concepts, namely: the expert's expertise level, FPR's Additive Consistency and the Induced-OWA operator to obtain the expert's importance weight in adverse judgment situation. The Expertise level of an expert in adverse judgment situation is determined by his/her own assessment on a set of alternatives and defined as 'the ability to differentiate consistently' and expressed as the ratio between Discrimination and Inconsistency. The experts provided their preferences using FPR (Fuzzy Preference Relations) since FPR has Additive Consistency property to replicate each element of FPR matrix. Experts were sorted according to their expertise level and the experts' importance weights followed the OWA (Ordered Weighted Averaging) operator's weights which were determined by parameterization using Basic Unit-Interval Increasing Monotonic functions. The experts' importance weights model illustrated by a numerical example, and it concluded that the higher the expert's expertise level, the higher his/her importance weight.