A fuzzy multi-criteria group decision making method for individual research output evaluation with maximum consensus

Individual research output (IRO) evaluation is both practically and theoretically important. Current research tends to only consider either bibliometric measures or peer review in IRO evaluation. This paper argues that bibliometric measures and peer review should be applied simultaneously to evaluate IRO. Moreover, in real life situations IRO evaluations are often made by groups and inevitably contain evaluators' subjective judgments. Accordingly, this paper develops a fuzzy multi-criteria group evaluation method which considers objective and subjective evaluations, i.e., bibliometric measures and peer review opinions simultaneously. The goals here are to conquer weighting difficulty and achieve maximum group consensus. This requires determining criteria weights, which we do with an intuitionistic fuzzy weighted averaging operator and then determining evaluator weights, which we do with a fuzzy distance-based method. Thereafter, we use a revised TOPSIS method to aggregate the objective and subjective ratings. A practical case study is used to test the feasibility of the methodology. Finally, we discuss the effectiveness of the proposed method.