东北大学学报:自然科学版 ›› 2018, Vol. 39 ›› Issue (5): 746-749.DOI: 10.12068/j.issn.1005-3026.2018.05.028

• 管理科学 • 上一篇    下一篇

基于评价者信服力的群体评价方法

宫诚举, 郭亚军, 郑红, 李伟伟   

  1. (东北大学 工商管理学院, 辽宁 沈阳110169)
  • 收稿日期:2016-12-01 修回日期:2016-12-01 出版日期:2018-05-15 发布日期:2018-05-25
  • 通讯作者: 宫诚举
  • 作者简介:宫诚举(1991-),男,黑龙江牡丹江人,东北大学博士研究生; 郭亚军(1952-),男,辽宁开原人,东北大学教授,博士生导师.
  • 基金资助:
    国家自然科学基金资助项目(71671031,71701040,71473033); 教育部人文社会科学研究青年项目(17YJC630067).

A Group Evaluation Method Based on the Convincing Force of Evaluators

GONG Cheng-ju, GUO Ya-jun, ZHENG Hong, LI Wei-wei   

  1. School of Business Administration, Northeastern University, Shenyang 110169, China.
  • Received:2016-12-01 Revised:2016-12-01 Online:2018-05-15 Published:2018-05-25
  • Contact: GONG Cheng-ju
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摘要: 针对群体评价中专家权重的计算问题,从对专家信息重视程度的角度出发,提出一种基于评价者信服力的群体评价方法,旨在探讨提高群体评价结果可信度的方法.结果表明,该方法在保证评价者评价信息完整性的同时能够综合评价者的经验信息和评价过程中的信息,从而保证评价结果的准确性.首先设定评价情景并提出研究假设,并对评价支持者和评价需求者进行区分;然后构建评价者信服力的计算模型并对模型的有效性进行说明;最后利用非线性规划模型计算各被评价对象的评价结果.

关键词: 群体评价, 评价者信服力, 经验信息, 评价需求者, 非线性规划模型

Abstract: Aimed at how to determine expert weights in group evaluation, a group evaluation method based on the convincing force of evaluators was proposed from the perspective of the attention degree of expert information in order to improve the credibility of evaluation results. It was found that this method not only guarantees the completeness of evaluators’ evaluation information, but also integrates evaluators’ experience information and other information in the evaluation process to ensure the accuracy of evaluation results. Firstly, the evaluation context was set and the research hypotheses were made, and then a distinction between evaluators and evaluation requestors was made. Secondly, the computational model of convicing force was constructed and its validity was expounded upon. Finally, a nonlinear programming model was used to calculate the final evaluation result of every evaluated object.

Key words: group evaluation, convicing force of evaluators, experience information, evaluation requestor, nonlinear programming model

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