Expertise-Based Ranking of Experts in Multicriteria Group Decision Making with Different Preference Representation Formats

The group decision-making (GDM) is a process of aggregating the preference information of each decision maker in a group into a collective opinion under certain decision criteria. When a decision is made by decision makers (DMs), the group decision or group opinion is a result of the integration of the individual opinions by a mathematical aggregation. An important thing in the integration of the individual opinions is which DMs’ opinions should be of importance in the aggregation process. The group opinion is heavily influenced by the level of expertise of the DMs. In real-life group decision making (GDM) problems, preference relations given by decision makers (DMs) are often heterogeneous because of their expertise and different decision habits. The expertise level of the DMs can be estimated using the ‘the ability to differentiate consistently’, a ratio between discrimination and inconsistency. Each expert has different expertise in different criteria and has his/her limited capacity in constructing of pairwise comparison preference relations. In this paper, we focus on a method to assess expertise-based ranking of experts in GDM with multiple criteria and different preference representation formats. The combination of expertise as ‘the ability to differentiate consistently’ and the consistency of various types of preference relations is discussed, when experts give their judgements for alternatives in various types of preference relations, such as multiplicative preference relations (MPRs), utility values, preference orderings, even incomplete FPRs or MPRs, including FPRs under certain criterion. Then, since the experts have the limited capacity in constructing of pairwise comparison preference relations in GDM with multiple criteria, we propose a expertise-based ranking method using the adjacent pairwise comparison technique in order to reduce the number of judgements. Finally, expertise-based ranking of experts is applied to aggregate the individual opinions into a group opinion by developing into experts’ importance weights in GDM. Numerical analyses show that proposed method is simple than the previous methods and can fill up some gaps in GDM.