Frontier Analysis with DEA

Kenneth Moore
Additional contact information
Kenneth Moore: The Nous Group

Chapter 6 in Measuring Productivity in Education and Not-for-Profits, 2021, pp 85-98 from Springer

Abstract: Abstract This chapter introduces the concept of productivity frontier analysis and appropriate applications of the method. It explains how data envelopment analysis (DEA) is one of the most popular techniques for conducting a frontier analysis. It then provides a walk-through for how the DEA algorithm works. The tutorial in this chapter explores a case study of five hypothetical not-for-profit organizations. It demonstrates how to use DEA on data from these organizations and how to interpret results. The chapter stresses how the direct results of DEA cannot be taken at face value, especially when the data elements being examined are non-priced. It explains how risks emerge if data are not interrogated further.

Keywords: Data envelopment analysis; Linear programming; Frontier analysis (search for similar items in EconPapers)
Date: 2021
References: Add references at CitEc
Citations:

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:mgmchp:978-3-030-72965-3_6

Ordering information: This item can be ordered from
http://www.springer.com/9783030729653

DOI: 10.1007/978-3-030-72965-3_6

Access Statistics for this chapter

More chapters in Management for Professionals from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().