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Abstract
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Data Envelopment Analysis (DEA) is an eciency measurement tool for evaluation of similar Decision
Making Units (DMUs). In DEA, weights are assigned to inputs and outputs and the absolute eciency
score is obtained by the ratio of weighted sum of outputs to weighted sum of inputs. In traditional
DEA models, this measure is also equivalent with relative eciency score which evaluates DMUs in
compare with the most ecient DMU. Recently network DEA models are appeared in the literature,
which try to assess DMUs regarding their internal production divisions and intermediate products. In
this paper we compare absolute and relative eciency scores in network framework. Since in network
DEA models, an ecient DMU does not exist necessarily, the relative eciency model helps us to
have at least one ecient DMU in our assessments
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