Selection strategy of uniform expert evaluation scale in group decision making
研究了专家评价量表对群体决策结果的影响，提出统一专家评价量表策略，帮助决策者获得期望的备选方案最终得分，适用于大样本且小样本下精度仍高。
The scoring habits of experts are embodied in expert evaluation scale (EES). We show that many inaccurate consensus and ranking results can occur in group decision making (GDM) problems without considering EES. To remove the impacts of EESs, we propose the definition of EES and the uniform EES (UEES) strategy. Then, we prove the influence of the selection of UEES strategy on two consistency measures and two aggregation operators. In real-world GDM problems, a decision maker (DM) usually hopes that the final scores of alternatives are subject to his/her desired distribution. Therefore, a novel ranking method by UEES strategy is proposed to obtain DM’s desired final scores. Finally, a numerical example is used to clarify the effectiveness of the proposed method, and a simulation experiment shows that the proposed method is more suitable for large sample cases but the accuracy is still at a high level under small sample cases.