A Goal Programming Approach to Constructing Virtual Peers for Cross-Efficiency Evaluation in DEA
Subject Areas : International Journal of Industrial Mathematics
ُSaba Karbalaei
1
,
Maryam Shadab
2
,
saber Saati
3
1 -
2 -
3 -
Keywords: Data Envelopment Analysis, Decision Making Units, Cross-efficiency matrix, Peer, Goal programming.,
Abstract :
Data envelopment analysis (DEA) is a widely used non-parametric technique for evaluating the relative efficiency of Decision-Making Units (DMUs) based on multiple inputs and outputs. To enhance the discriminatory power of classical DEA, the cross-efficiency method incorporates peer evaluation by applying each DMU's optimal weights to all others. This process generates a cross-efficiency matrix that captures both self-appraisal and peer-appraisal scores. In cross-efficiency analysis, determining the appropriate peers is crucial, as other DMUs can improve their efficiency by adopting the peer weight system. Focusing on this aspect highlights the importance of selecting suitable peers. However, identifying peers from the cross-efficiency matrix presents challenges; therefore, in this paper, we propose generating virtual peers.
In this study, we improve upon the models of Rödder and Reucher [18] by utilizing a goal programming method to generate a weighted set of virtual peers. We present a model with an appropriate weight structure that can enhance the efficiency of all DMUs.
Finally, the proposed model is illustrated with an example, and the results are compared to those of Rödder and Reucher [18].
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