An Integrated Decision Support Model to Assess Reviewers for Research Project Selection

Reviewers play a significant role in research project selection, because their opinions will have great influence on the decision of the projects which will be funded. Current methods mainly focus on the evaluation of reviewers´ competitiveness in a certain research areas, while ignoring the performance of reviewers whether is suitable to review a proposal. In this paper, a group decision support model is proposed to assess reviewers´ performance in peer review process. In the proposed model, competitiveness and relevance of reviewers are considered to evaluate reviewers. It integrates analytic hierarchy process (AHP), scoring method and fuzzy linguistic processing. An illuminating example is used to show the effectiveness of the proposed method. The results find that the proposed method is a reasonable method to assess reviewers, and it can be potentially applied to reviewer evaluation in the National Natural Science Foundation of China (NSFC).