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

Author

Listed:
  • Mohammed Al-Siyabi

    (Sultan Qaboos University)

  • Gholam R. Amin

    (University of New Brunswick at Saint John)

  • Shekar Bose

    (Sultan Qaboos University)

  • Hussein Al-Masroori

    (Sultan Qaboos University)

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.

Suggested Citation

  • Mohammed Al-Siyabi & Gholam R. Amin & Shekar Bose & Hussein Al-Masroori, 2019. "Peer-judgment risk minimization using DEA cross-evaluation with an application in fishery," Annals of Operations Research, Springer, vol. 274(1), pages 39-55, March.
    • Handle: RePEc:spr:annopr:v:274:y:2019:i:1:d:10.1007_s10479-018-2858-3
    DOI: 10.1007/s10479-018-2858-3
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    References listed on IDEAS

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    Cited by:

    1. Borrás, Fernando & Ruiz, José L. & Sirvent, Inmaculada, 2023. "Peer evaluation through cross-efficiency based on reference sets," Omega, Elsevier, vol. 114(C).
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    3. Xie, Qiwei & Xu, Qifan & Zhu, Da & Rao, Kaifeng & Dai, Qianzhi, 2020. "Fair allocation of wastewater discharge permits based on satisfaction criteria using data envelopment analysis," Utilities Policy, Elsevier, vol. 66(C).

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