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

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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.

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Authors and Affiliations

  1. Department of Natural Resource Economics, College of Agricultural and Marine Sciences, Sultan Qaboos University, Muscat, Oman

    Mohammed Al-Siyabi & Shekar Bose

  2. Faculty of Business, University of New Brunswick at Saint John, Saint John, NB, E2L 4L5, Canada

    Gholam R. Amin

  3. Department of Marine Science and Fisheries, College of Agricultural and Marine Sciences, Sultan Qaboos University, Muscat, Oman

    Hussein Al-Masroori

Authors
  1. Mohammed Al-Siyabi
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  2. Gholam R. Amin
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  3. Shekar Bose
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  4. Hussein Al-Masroori
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Corresponding author

Correspondence to Gholam R. Amin.

Appendix 1

Appendix 1

See Table 3.

Table 3 Data set and DEA scores for 97 fishers
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Al-Siyabi, M., Amin, G.R., Bose, S. et al. Peer-judgment risk minimization using DEA cross-evaluation with an application in fishery. Ann Oper Res 274, 39–55 (2019). https://doi.org/10.1007/s10479-018-2858-3

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