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

  • Mohammed Al-Siyabi
  • Gholam R. Amin
  • Shekar Bose
  • Hussein Al-Masroori
Original Research
  • 86 Downloads

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.

Keywords

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

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Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2018

Authors and Affiliations

  • Mohammed Al-Siyabi
    • 1
  • Gholam R. Amin
    • 2
  • Shekar Bose
    • 1
  • Hussein Al-Masroori
    • 3
  1. 1.Department of Natural Resource Economics, College of Agricultural and Marine SciencesSultan Qaboos UniversityMuscatOman
  2. 2.Faculty of BusinessUniversity of New Brunswick at Saint JohnSaint JohnCanada
  3. 3.Department of Marine Science and Fisheries, College of Agricultural and Marine SciencesSultan Qaboos UniversityMuscatOman

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