Peer-judgment risk minimization using DEA cross-evaluation with an application in fishery

One of the shortcomings in the standard data envelopment analysis (DEA) self-evaluation models is the flexibility of choosing favorable DEA weights on inputs and outputs. This study uses the potential of DEA cross-efficiency evaluation and proposes a new mean–variance goal programming model for mini...

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Bibliographic Details
Published inAnnals of operations research Vol. 274; no. 1-2; pp. 39 - 55
Main Authors Al-Siyabi, Mohammed, Amin, Gholam R., Bose, Shekar, Al-Masroori, Hussein
Format Journal Article
LanguageEnglish
Published New York Springer US 01.03.2019
Springer
Springer Nature B.V
Subjects
Analysis
Business and Management
Combinatorics
Data envelopment analysis
Decision making
Fisheries
Fishery management
Goal programming
Methods
Operations research
Operations Research/Decision Theory
Original Research
Risk
Risk management
Standard data
Studies
Theory of Computation
Oman
Peer-judgment
Risk minimization
Fishery
Mean–variance goal programming
Cross-efficiency evaluation
Data envelopment analysis
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Summary:One of the shortcomings in the standard data envelopment analysis (DEA) self-evaluation models is the flexibility of choosing favorable DEA weights on inputs and outputs. This study uses the potential of DEA cross-efficiency evaluation and proposes a new mean–variance goal programming model for minimizing the risk of changing DEA weights for identification of high performed decision making units. The applicability of the proposed method in this paper is demonstrated through an application in Oman fishery, to address peer-judgment risk in fisheries. The suggested model also provides a list of fishers with maximum cross-efficiency scores.
ISSN:0254-5330
1572-9338
DOI:10.1007/s10479-018-2858-3