Cross-efficiency aggregation method based on prospect consensus process

被引:47
作者
Chen, Lei [1 ]
Wang, Ying-Ming [1 ,2 ]
Huang, Yan [1 ,3 ]
机构
[1] Fuzhou Univ, Sch Econ & Management, Decis Sci Inst, Fuzhou 350108, Fujian, Peoples R China
[2] Fuzhou Univ, Minist Educ, Key Lab Spatial Data Min & Informat Sharing, Fuzhou 350108, Fujian, Peoples R China
[3] Fujian Agr & Forestry Univ, Coll Comp & Informat Sci, Fuzhou 350002, Fujian, Peoples R China
基金
中国国家自然科学基金;
关键词
Data envelopment analysis; Efficiency aggregation; Prospect theory; Consensus process; Convergence; DATA ENVELOPMENT ANALYSIS; GROUP DECISION-MAKING; PORTFOLIO SELECTION; DEA; RANKING; REPRESENTATION; AVERSION; MODEL; OWA;
D O I
10.1007/s10479-019-03491-w
中图分类号
C93 [管理学]; O22 [运筹学];
学科分类号
070105 ; 12 ; 1201 ; 1202 ; 120202 ;
摘要
The arithmetic average method is usually adopted to aggregate cross-efficiency in traditional cross-efficiency methods. However, this method not only underestimates the importance of self-evaluation, but also ignores the subjective preference of decision-makers. This paper thus introduces prospect theory to describe the subjective preference of decision-makers in the aggregation process when they face gains and losses, then a new method is constructed to aggregate cross-efficiency. Based on the differences between the psychological expectations and aggregation results, the expectations are constantly adjusted until a consensus on aggregation results is reached. An aggregation result that is more acceptable to all decision-making units can then be obtained. Finally, the proposed method is applied to aggregate the cross-efficiency of 27 industrial robots to illustrate its effectiveness and convergence.
引用
收藏
页码:115 / 135
页数:21
相关论文
共 45 条
[1]   GANGLESS CROSS-EVALUATION IN DEA: AN APPLICATION TO STOCK SELECTION [J].
Amin, Gholam R. ;
Oukil, Amar .
RAIRO-OPERATIONS RESEARCH, 2019, 53 (02) :645-655
[2]   Group cross-efficiency evaluation in data envelopment analysis: An application to Taiwan hotels [J].
Ang, Sheng ;
Chen, Menghan ;
Yang, Feng .
COMPUTERS & INDUSTRIAL ENGINEERING, 2018, 125 :190-199
[3]   Are employee stock option exercise decisions better explained through the prospect theory? [J].
Bahaji, Hamza .
ANNALS OF OPERATIONS RESEARCH, 2018, 262 (02) :335-359
[4]   Estimating parametric loss aversion with prospect theory: Recognising and dealing with size dependence [J].
Balcombe, Kelvin ;
Bardsley, Nicholas ;
Dadzie, Sam ;
Fraser, Lain .
JOURNAL OF ECONOMIC BEHAVIOR & ORGANIZATION, 2019, 162 :106-119
[5]   An alternative neutral approach for cross-efficiency evaluation [J].
Carrillo, Marianela ;
Jorge, Jesus M. .
COMPUTERS & INDUSTRIAL ENGINEERING, 2018, 120 :137-145
[6]   MEASURING EFFICIENCY OF DECISION-MAKING UNITS [J].
CHARNES, A ;
COOPER, WW ;
RHODES, E .
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH, 1978, 2 (06) :429-444
[7]   An investment analysis for China's sustainable development based on inverse data envelopment analysis [J].
Chen, Lei ;
Wang, Yingming ;
Lai, Fujun ;
Feng, Feng .
JOURNAL OF CLEANER PRODUCTION, 2017, 142 :1638-1649
[8]   A dynamic approach for emergency decision making based on prospect theory with interval-valued Pythagorean fuzzy linguistic variables [J].
Ding, Xue-Feng ;
Liu, Hu-Chen ;
Shi, Hua .
COMPUTERS & INDUSTRIAL ENGINEERING, 2019, 131 :57-65
[9]   Consensus reaching in social network group decision making: Research paradigms and challenges [J].
Dong, Yucheng ;
Zha, Quanbo ;
Zhang, Hengjie ;
Kou, Gang ;
Fujita, Hamido ;
Chiclana, Francisco ;
Herrera-Viedma, Enrique .
KNOWLEDGE-BASED SYSTEMS, 2018, 162 :3-13
[10]   Consensus building in multiperson decision making with heterogeneous preference representation structures: A perspective based on prospect theory [J].
Dong, Yucheng ;
Luo, Nan ;
Liang, Haiming .
APPLIED SOFT COMPUTING, 2015, 35 :898-910