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中国管理科学

中国管理科学 ›› 2022, Vol. 30 ›› Issue (11): 250-259.doi: 10.16381/j.cnki.issn1003-207x.2020.0474

• 论文 • 上一篇    下一篇

基于证据推理和前景理论的交叉效率排序方法研究

王旭1, 王应明2,3, 王亮2, 蓝以信2, 张兴贤4   

  1. 1.重庆师范大学经济与管理学院，重庆401331；2.福州大学决策科学研究所，福建 福州350116；3.教育部空间数据挖掘与信息共享重点实验室, 福建 福州350116； 4.铜陵学院建筑工程学院，安徽 铜陵244061
  • 收稿日期:2020-03-22 修回日期:2020-09-17 出版日期:2022-11-20 发布日期:2022-11-28
  • 通讯作者: 王应明(1964-)，男(汉族)，江苏海安人，福州大学经济与管理学院，教授，博士生导师，研究方向：决策理论与方法，Email:msymwang@hotmail.com. E-mail:msymwang@hotmail.com
  • 基金资助:
    国家自然科学基金资助项目(71901071，61773123，71701050)；福建省社科研究基地重大研究项目(FJ2020MJDZ016)，福建省自然科学基金资助项目(2021J01569,2021J01568)；全国统计科学研究重点项目(2022LZ12)；安徽省教育厅高校优秀青年人才支持计划项目(gxyqZD2020105)

Study on Cross-efficiency Ranking Based on Evidential Reasoning and Prospect Theory

WANG Xu1, WANG Ying-ming2,3, WANG Liang2, LAN Yi-xin2, ZHANG Xing-xian4   

  1. 1. School of Economics & Management, Chongqing Normal University, Chongqing 401331, China; 2. Decision Sciences Institute, Fuzhou University, Fuzhou 350116, China；3. Key Laboratory of Spatial Data Mining & Information Sharing of Ministry of Education, Fuzhou University, Fuzhou 350116, China; 4. School of Architecture and Engineering, Tongling University, Tongling 244061, China
  • Received:2020-03-22 Revised:2020-09-17 Online:2022-11-20 Published:2022-11-28
  • Contact: 王应明 E-mail:msymwang@hotmail.com

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摘要： 针对由交叉效率评价策略和交叉效率集结方法的多样性而造成评价结果不一致的问题，提出利用证据推理方法和前景理论，综合各个交叉效率评价策略的评价结果，实现对决策单元的统一评价。首先，分别将选用的交叉效率评价策略以及各个评价策略中的他评效率设置成一级指标和二级指标，依据算数平均和前景理论分别确定一、二级指标的权重；其次，依据他评效率确定二级指标置信度，利用证据推理方法将各个交叉效率评价策略的他评效率综合转换成决策单元被评价为有效的置信度。决策者可通过比较决策单元被识别为有效的置信度的大小来判断决策单元交叉效率的大小，进而实现对决策单元的排序；最后，通过案例验证和说明本文提出方法的有效性和实用性。

关键词: 数据包络分析；证据推理；置信度；交叉效率排序；前景理论

Abstract: There has a lot of researches on cross-efficiency based on data envelopment analysis (DEA), and different DEA cross-efficiency models usually lead to different decision making units (DMUs) rankings and conclusions. To avoid the biased performance evaluation caused by biased DEA cross-efficiency model and make a comprehensive assessment on DMUs, an alternative combined with prospect theory and evidential reasoning approach is proposed to integrate the cross-efficiencies of DMUs, which are obtained from several DEA cross-efficiency models, and the cross-efficiencies are converted into the belief degree to support the evaluated DMU being efficient. The weights of integrated efficiencies are obtained by prospect theory, which considers the expected gains and loss of decision makers. The rankings and comparisons of DMUs are determined by the final belief degrees. The higher the belief degree is, the better the DMU ranks. An assessment of 7 departments in a university is made with the proposed approach. It is found that the proposed approach integrates the evaluations of DMUs under aggressive, benevolent and neutral cross-efficiency models well, and leads a comprehensive conclusion.

Key words: data envelopment analysis; evidential reasoning; belief degree; cross-efficiency ranking; prospect theory

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