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

Mohammed Al-Siyabi, Gholam R. Amin, Shekar Bose, Hussein Al-Masroori

Research output: Contribution to journalArticle

2 Citations (Scopus)

Abstract

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.

Original languageEnglish
Pages (from-to)1-17
Number of pages17
JournalAnnals of Operations Research
DOIs
Publication statusAccepted/In press - Apr 13 2018

Fingerprint

Risk minimization
Evaluation
Fisheries
Peers
Data envelopment analysis
Evaluation model
Goal programming
Decision making units
Oman

Keywords

  • Cross-efficiency evaluation
  • Data envelopment analysis
  • Fishery
  • Mean–variance goal programming
  • Peer-judgment
  • Risk minimization

ASJC Scopus subject areas

  • Decision Sciences(all)
  • Management Science and Operations Research

Cite this

Peer-judgment risk minimization using DEA cross-evaluation with an application in fishery. / Al-Siyabi, Mohammed; Amin, Gholam R.; Bose, Shekar; Al-Masroori, Hussein.

In: Annals of Operations Research, 13.04.2018, p. 1-17.

Research output: Contribution to journalArticle

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