Abstract
This article identifies differences and similarities between DEA (Data Envelopment Analysis) and DA (Discriminant Analysis) in the view of GP (Goal Programming). Based upon such characterization, this article proposes a new type of DA technique, referred to as “DEA-Discriminant Analysis (DEA-DA)”, that incorporates a methodological strength of DEA into the DA formulation. This research applies the proposed DEA-DA method to both an illustrative data set and a real case study related to Japanese banks. The importance of DEA-DA is confirmed by comparing it with other DA methods.
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