Input allocation with the Ellipsoidal Frontier Model

Abstract

This work aims at complementing the development of the EFM (Ellipsoidal Frontier Model) proposed by Milioni et al. (2011a). EFM is a parametric input allocation model of constant sum that uses DEA (Data Envelopment Analysis) concepts and ensures a solution such that all DMUs (Decision Making Units) are strongly CCR (Constant Returns to Scale) efficient. The degrees of freedom obtained with the possibility of assigning different values to the ellipsoidal eccentricities bring flexibility to the model and raises the interest in evaluating the best distribution among the many that can be generated. We propose two analyses named as local and global. In the first one, we aim at finding a solution that assigns the smallest possible input value to a specified DMU. In the second, we look for a solution that assures the lowest data variability.

Redistributing Multiple Inputs With a Parabolic Dea Model

“…Thus, as they have stated, the model presents results more adherent to the coherence property. Milioni et al (2011a) andBianca Alves et al (2014) have studied the input allocation using parameterized efficiency in elliptical geometry. Milioni et al (2011b) andSilva et al (2017) have introduced the hyperbolic DEA frontier.…”