A subgroup dominance-based benefit of the doubt method for addressing rank reversals: A case study of the human development index in Europe
被引:17
作者:
Su, Weihua
论文数: 0引用数: 0
h-index: 0
机构:
Zhejiang Gongshang Univ, Coll Stat & Math, Hangzhou 310018, Peoples R ChinaZhejiang Gongshang Univ, Coll Stat & Math, Hangzhou 310018, Peoples R China
Su, Weihua
[1
]
Chen, Sibo
论文数: 0引用数: 0
h-index: 0
机构:
Anhui Polytech Univ, Sch Math & Phys, Wuhu 241000, Peoples R ChinaZhejiang Gongshang Univ, Coll Stat & Math, Hangzhou 310018, Peoples R China
Chen, Sibo
[2
]
Zhang, Chonghui
论文数: 0引用数: 0
h-index: 0
机构:
Zhejiang Gongshang Univ, Coll Stat & Math, Hangzhou 310018, Peoples R ChinaZhejiang Gongshang Univ, Coll Stat & Math, Hangzhou 310018, Peoples R China
Zhang, Chonghui
[1
]
Li, Kevin W.
论文数: 0引用数: 0
h-index: 0
机构:
Univ Windsor, Odette Sch Business, Windsor, ON N9B 3P4, CanadaZhejiang Gongshang Univ, Coll Stat & Math, Hangzhou 310018, Peoples R China
Li, Kevin W.
[3
]
机构:
[1] Zhejiang Gongshang Univ, Coll Stat & Math, Hangzhou 310018, Peoples R China
[2] Anhui Polytech Univ, Sch Math & Phys, Wuhu 241000, Peoples R China
Rank reversal;
Benefit of the doubt;
Subgroup dominance;
Human development index;
Composite indicators;
COMPOSITE INDICATORS;
CONSTRUCTION;
PERFORMANCE;
EFFICIENCY;
DEA;
D O I:
10.1016/j.ejor.2022.11.030
中图分类号:
C93 [管理学];
学科分类号:
12 ;
1201 ;
1202 ;
120202 ;
摘要:
The benefit of the doubt (BoD) is a non-parametric weighting method that aims to maximize the relative composite indicator value of each decision-making unit (DMU). A well-known issue of BoD-based ranking of DMUs is the rank reversal problem when DMUs are deleted or added. The fundamental reason for rank reversals is that deleting (or adding) a DMU influences the generated weight by changing the frontier surface. To address the rank reversal problem, this paper proposes a subgroup dominance-based BoD model (SD-BoD). Based on the individual weights obtained from a classic BoD model, a dominance-based pairwise comparison mechanism is put forward to ensure comparability of different DMUs. Moreover, motivated by the data envelopment analysis idea, we construct a sequential frontier surface partition technique and establish a DMU ranking framework based on subgroup dominance, which helps reduce weight variation due to DMU addition or deletion. Finally, the effectiveness of the SD-BoD method is illustrated by comparing and analyzing the Human Development Indices of the 28 European regions.(c) 2022 Elsevier B.V. All rights reserved.
机构:
Bundeswehr Univ Munich, Res Ctr RISK, Werner Heisenberg Weg 39, D-85577 Neubiberg, GermanyBundeswehr Univ Munich, Res Ctr RISK, Werner Heisenberg Weg 39, D-85577 Neubiberg, Germany
Bross, Lisa
Wienand, Ina
论文数: 0引用数: 0
h-index: 0
机构:
Fed Off Civil Protect & Disaster Assistance, Provinzialstr 93, D-53127 Bonn, GermanyBundeswehr Univ Munich, Res Ctr RISK, Werner Heisenberg Weg 39, D-85577 Neubiberg, Germany
Wienand, Ina
Krause, Steffen
论文数: 0引用数: 0
h-index: 0
机构:
Bundeswehr Univ Munich, Res Ctr RISK, Werner Heisenberg Weg 39, D-85577 Neubiberg, GermanyBundeswehr Univ Munich, Res Ctr RISK, Werner Heisenberg Weg 39, D-85577 Neubiberg, Germany
机构:
Rutgers State Univ, Dept Stat, Rutgers, New Brunswick, NJ USARutgers State Univ, Dept Stat, Rutgers, New Brunswick, NJ USA
Chen, Rong
Ji, Yuanyuan
论文数: 0引用数: 0
h-index: 0
机构:
Shanghai Acad Social Sci, Res Ctr Econometr, Shanghai, Peoples R ChinaRutgers State Univ, Dept Stat, Rutgers, New Brunswick, NJ USA
Ji, Yuanyuan
Jiang, Guolin
论文数: 0引用数: 0
h-index: 0
机构:
Shanghai Acad Social Sci, Res Ctr Econometr, Shanghai, Peoples R ChinaRutgers State Univ, Dept Stat, Rutgers, New Brunswick, NJ USA
Jiang, Guolin
Xiao, Han
论文数: 0引用数: 0
h-index: 0
机构:
Rutgers State Univ, Dept Stat, Rutgers, New Brunswick, NJ USARutgers State Univ, Dept Stat, Rutgers, New Brunswick, NJ USA
Xiao, Han
Xie, Ruoqing
论文数: 0引用数: 0
h-index: 0
机构:
Shanghai Acad Social Sci, Res Ctr Econometr, Shanghai, Peoples R China
Shanghai Acad Social Sci, Inst Econ, Shanghai, Peoples R ChinaRutgers State Univ, Dept Stat, Rutgers, New Brunswick, NJ USA
Xie, Ruoqing
Zhu, Pingfang
论文数: 0引用数: 0
h-index: 0
机构:
Shanghai Acad Social Sci, Res Ctr Econometr, Shanghai, Peoples R China
Shanghai Acad Social Sci, Inst Econ, Shanghai, Peoples R ChinaRutgers State Univ, Dept Stat, Rutgers, New Brunswick, NJ USA
机构:
Bundeswehr Univ Munich, Res Ctr RISK, Werner Heisenberg Weg 39, D-85577 Neubiberg, GermanyBundeswehr Univ Munich, Res Ctr RISK, Werner Heisenberg Weg 39, D-85577 Neubiberg, Germany
Bross, Lisa
Wienand, Ina
论文数: 0引用数: 0
h-index: 0
机构:
Fed Off Civil Protect & Disaster Assistance, Provinzialstr 93, D-53127 Bonn, GermanyBundeswehr Univ Munich, Res Ctr RISK, Werner Heisenberg Weg 39, D-85577 Neubiberg, Germany
Wienand, Ina
Krause, Steffen
论文数: 0引用数: 0
h-index: 0
机构:
Bundeswehr Univ Munich, Res Ctr RISK, Werner Heisenberg Weg 39, D-85577 Neubiberg, GermanyBundeswehr Univ Munich, Res Ctr RISK, Werner Heisenberg Weg 39, D-85577 Neubiberg, Germany
机构:
Rutgers State Univ, Dept Stat, Rutgers, New Brunswick, NJ USARutgers State Univ, Dept Stat, Rutgers, New Brunswick, NJ USA
Chen, Rong
Ji, Yuanyuan
论文数: 0引用数: 0
h-index: 0
机构:
Shanghai Acad Social Sci, Res Ctr Econometr, Shanghai, Peoples R ChinaRutgers State Univ, Dept Stat, Rutgers, New Brunswick, NJ USA
Ji, Yuanyuan
Jiang, Guolin
论文数: 0引用数: 0
h-index: 0
机构:
Shanghai Acad Social Sci, Res Ctr Econometr, Shanghai, Peoples R ChinaRutgers State Univ, Dept Stat, Rutgers, New Brunswick, NJ USA
Jiang, Guolin
Xiao, Han
论文数: 0引用数: 0
h-index: 0
机构:
Rutgers State Univ, Dept Stat, Rutgers, New Brunswick, NJ USARutgers State Univ, Dept Stat, Rutgers, New Brunswick, NJ USA
Xiao, Han
Xie, Ruoqing
论文数: 0引用数: 0
h-index: 0
机构:
Shanghai Acad Social Sci, Res Ctr Econometr, Shanghai, Peoples R China
Shanghai Acad Social Sci, Inst Econ, Shanghai, Peoples R ChinaRutgers State Univ, Dept Stat, Rutgers, New Brunswick, NJ USA
Xie, Ruoqing
Zhu, Pingfang
论文数: 0引用数: 0
h-index: 0
机构:
Shanghai Acad Social Sci, Res Ctr Econometr, Shanghai, Peoples R China
Shanghai Acad Social Sci, Inst Econ, Shanghai, Peoples R ChinaRutgers State Univ, Dept Stat, Rutgers, New Brunswick, NJ USA