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

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

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

12 Citations (Scopus)


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
Publication statusAccepted/In press - Apr 13 2018


  • 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


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