Introduction to data envelopment analysis

Data envelopment analysis (DEA) is a methodology for measuring the relative efficiencies of a set of decision-making units (DMUs) that uses multiple inputs to produce multiple outputs. Real input and output data are fundamentally indispensable in conventional DEA. Our focus in this chapter is on basic DEA models for measuring the efficiency of a DMU relative to similar DMUs to estimate a “best practice” frontier. So, this chapter will present a literature review on DEA, including the fundamental concept of DEA, frequently used DEA models, and the DMU efficiency definitions.