Modifying the convexity condition in Data Envelopment Analysis (DEA)
DOI:
https://doi.org/10.5377/nexo.v33i02.10784Keywords:
Data Envelopment Analysis (DEA), Convexity condition, Constant return to scale (CRS), Variable return to scale (VRS), Efficiency estimationAbstract
Conventional Data Envelopment Analysis (DEA) models are based on a production possibility set (PPS) that satisfies various postulates. Extension or modification of these axioms leads to different DEA models. In this paper, our focus concentrates on the convexity axiom, leaving the other axioms unmodified. Modifying or extending the convexity condition can lead to a different PPS. This adaptation is followed by a two-step procedure to evaluate the efficiency of a unit based on the resulting PPS. The proposed frontier is located between two standard, well-known DEA frontiers. The model presented can differentiate between units more finely than the standard variable return to scale (VRS) model. In order to illustrate the strengths of the proposed model, a real data set describing Iranian banks was employed. The results show that this alternative model outperforms the standard VRS model and increases the discrimination power of (VRS) models.
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