A DEA-PROMETHEE approach for complete ranking of units

Maryam Bagherikahvarin

International Journal of Operational Research, 2019, vol. 35, issue 2, 224-244

Abstract: Data envelopment analysis (DEA) and multiple criteria decision aid (MCDA) are two well-known approaches to rank so-called decision-making units (DMUs) or alternatives. In this contribution, a two-step model is presented to completely rank units according to multiple inputs and outputs. In the first step, DEA is applied between each pair of DMUs independently to generate a pairwise comparison matrix. In the second step, the obtained matrix is exploited by means of Preference Ranking Organization Method for Enrichment Evaluations (PROMETHEE) to completely rank units. We show the compatibility between the resulting ranking of DEA and DEA-PROMETHEE methods while there exist just one input and one output. We also discuss the monotonicity property of the method. We compare DEA-PROMETHEE with an integrated DEA-AHP approach on a numerical example.

Keywords: data envelopment analysis; DEA; multiple criteria decision aid; MCDA; PROMETHEE; efficiency; ranking; decision-making; DM. (search for similar items in EconPapers)
Date: 2019
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