A multi-step distance friction minimization (DFM) approach has been developed to assist a decision making unit to improve its efficiency. This approach contracts inputs and expands outputs simultaneously through the minimization of distance friction relative to the strongly efficient frontier based on a weighted Euclidean norm. In this paper, we point out that the DFM approach has a problem by means of two numerical examples and then show how to solve the problem. Using a real data set, we not only confirm the occurrence of this problem inherent in the original formulation, but also demonstrate how our modification works.
Data Envelopment Analysis (DEA) is a nonparametric method for measuring the relative efficiency and performance of Decision Making Units (DMUs). Traditionally, there are two issues regarding the DEA simultaneously i.e., the identification of a reference point on the efficient boundary of the production possibility set (PPS) and the use of some measures of distance from the unit under assessment to the efficient frontier. Due to its importance, in this paper, two alternative target setting models were developed to allow for lowefficient DMUs find the easiest way to improve its efficiency and reach to the efficient boundary. One seeks the closest weak efficient projection and the other suggests the most appropriate direction towards the strong efficient frontier surface. Both of these models provides the closest projection in one stage. Finally, a proposed problem is empirically checked by using a recent data related to 30 European airports.
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