Ranking Decision Making Units Based on DEA- like Nonreciprocal Pairwise Comparisons

Ever since the birth of data envelopment analysis (DEA) the question of ranking the decision making units (DMUs) has been one of the focal points of research in the area. Among several other approaches, promising attempts have been made to marry DEA with the analytic hierarchy process (AHP) method. Keeping the idea of using DEA-based pairwise comparisons between the DMUs, as proposed in some DEA-AHP variants published in the literature, a new method is presented for combining DEA with techniques for eliciting weights from pairwise comparison matrices. The basic idea is to apply a variant of the CCR problem instead of the classic one. The ensuing scores are then utilized to build a nonreciprocal pairwise comparison matrix which serves as the basis for eliciting the ranking values of the DMUs. The main advantage of this new method is the wider range of the resulting ranking values which subsequently leads to better distinction between the DMUs. Besides the eigenvector method, optimization based methods are also considered for eliciting the ranking values from the nonreciprocal pairwise comparison matrix. Numerical examples are supplied for comparing the proposed techniques.