Abstract
The aim of this chapter is to position the newly developed distance friction minimization (DFM) model in the context of Data Envelopment Analysis (DEA). This model generates an appropriate (nonradial) efficiency-improvement projection model, for both an input reduction and an output increase. In this approach, a generalized distance function, based on a Euclidean distance metric in weighted spaces, is proposed to assist a decision making unit (DMU) to improve its performance by an appropriate movement toward the efficiency frontier surface. A suitable form of such a multidimensional projection function for efficiency improvement is given by a multiple objective quadratic programming (MOQP) model. This chapter describes the various steps involved in a systematic manner. The abovementioned DFM model is illustrated empirically by using a data set on several airports, where the aim is to offer an in-depth understanding of the advantages and features of the DFM model. In addition, the comparative analysis of these airports is able to comprise both input slacks and output slacks (or a combination of input reduction and output rise).
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