Data Envelopment Analysis: The Mathematical Programming Approach to Efficiency Analysis

Emmanuel Thanassoulis*, Maria C S Portela, Ozren Despić

*Corresponding author for this work

Research output: Chapter in Book/Published conference outputChapter


This chapter deals with the measurement of efficiency through the nonparametric, mathematical programming-based technique better known as data envelopment analysis (DEA). A producer is defined as an economic agent that takes a set of inputs and transforms them either in form or in location into a set of outputs. In DEA, the economic agent is referred to as a decision-making unit (DMU) to accord with the notion that we are assessing entities that have control over the processes they deploy to convert their inputs into outputs. The DEA can be used to address a large variety of questions about the transformation of inputs into outputs by a DMU. These include questions such as the relative efficiency of a DMU (e.g., how far short are its output levels from maximum levels attainable for its input levels?); identification of "suitable" efficient peers for an inefficient DMU to emulate; and estimates of input-output levels that would render a DMU efficient (i.e., targets for the DMU). The advantages and limitations of the DEA models are discussed.

Original languageEnglish
Title of host publicationThe Measurement of Productive Efficiency and Productivity Change
PublisherOxford University Press
ISBN (Print)9780199870288, 9780195183528
Publication statusPublished - 1 Jan 2008


  • DEA
  • Decision-making unit
  • Efficiency measures
  • Inputs
  • Outputs
  • Value judgements


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