Similarity-Trust Network For Clustering Based Consensus Group Decision Making Model

Trust relation, as defined in Social Network Analysis(SNA), is one of the recent notions considered in de-cision making. This inspired our integration of trustrelation in constructing a similarity–trust network. Si-milarity of experts' preferences is analyzed inclusivelywith trust relation by defining a new combinationfunction of both attributes. The agglomerative hier-archical clustering approach is applied to group expertsinto subclusters based on the constructed similarity—trust degrees. The centrality concept from SNA is thenused to determine the expert's similarity–trust cen-trality (STC) index, which is the basis for the con-struction of a new aggregation operator, STC‐inducedordered weighted averaging operator, to fuse the in-dividual experts' preferences into a collective one, fromwhich the consensus solution is derived. An analysis ofresults with different levels of trust degree is carriedout. We show that this new idea is promising and re-levant to be used in solving certain consensus groupdecision‐making problems.