Alguns paradoxos em modelos DEA-BCC: eficiências negativas e inexistência de retorno de escala.

O modelo DEA-BCC é usado em situações onde as unidades avaliadas são de tamanhos bem diferentes e é necessário levar em conta efeitos de escala. No entanto as propriedades deste modelo são, muitas vezes, mal compreendidas. Além das conheciddas distorções devido à existência de DMUs eficientes à partida mostra-se neste artigo a existência de duas outras propriedades problemáticas: a existência de eficiências negativas e os nunca crescentes retornos de escala. As primeiras surgem em situações tipo avaliação cruzada, devido à existência de um termo independente. Já a inexistência de retornos crescentes de escala advém da convexidade da fronteira

Practical common weights scalarizing function approach for efficiency analysis

A characteristic of Data Envelopment Analysis (DEA) is to allow individual decision making units (DMUs) to select the factor weights which are the most advantageous for them in calculating their efficiency scores. This flexibility in selecting the weights, on the other hand, deters the comparison among DMUs on a common base. For dealing with this difficulty and assessing all the DMUs on the same scale, this paper proposes using a multiple objective linear programming (MOLP) approach based on scalarizing function for generating common set of weights under the DEA framework. This is an advantageous of the proposed approach against general approaches in the literature which are based on multiple objective nonlinear programming

A Study of Highways Performance with a Molp-Dea Model and an Interactive Tri-Criteria Linear Programming Package (Trimap)

This paper deals with the evaluation of a few Brazilian privatised highways. We use Data Envelopment Analysis (DEA) for that. As the number of highways is too small, we need to use an additional method to avoid ties in the evaluation index. The MCDEA model of Li and Reeves (a tri-objective model) is adequate to solve this problem. The authors suggest the extension of the CCR model, considering two extra objective functions, i.e. a min-max function, corresponding to a measure of equity and a min-sum function, favouring some sort of overall evaluation of the DMUs, from the point of view of the DMU under analysis. The graphic decomposition of the weighting space (used in TRIMAP as an operational tool), the possibility of introducing constraints on the objective function values during the search automatically translated into the weighting space make it specially adequate to explore the MCDEA model.