Aggregation operators and fuzzy systems modeling
Fuzzy Sets and Systems
Distances between intuitionistic fuzzy sets
Fuzzy Sets and Systems
An h-index weighted by citation impact
Information Processing and Management: an International Journal
Journal of the American Society for Information Science and Technology
Decider: A fuzzy multi-criteria group decision support system
Knowledge-Based Systems
Fuzzy Sets and Systems
A GRA-based intuitionistic fuzzy multi-criteria group decision making method for personnel selection
Expert Systems with Applications: An International Journal
Expert Systems with Applications: An International Journal
Intuitionistic Fuzzy Aggregation Operators
IEEE Transactions on Fuzzy Systems
Engineering Applications of Artificial Intelligence
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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.