Applications of data envelopment analysis in education

Emmanuel Thanassoulis*, Kristof de Witte, Jill Johnes, Geraint Johnes, Giannis Karagiannis, Conceição S. Portela

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingChapter (peer-reviewed)

Abstract

Non-parametric methods for efficiency evaluation were designed to analyse industries comprising multi-input multi-output producers and lacking data on market prices. Education is a typical example. In this chapter, we review applications of DEA in secondary and tertiary education, focusing on the opportunities that this offers for benchmarking at institutional level. At secondary level, we investigate also the disaggregation of efficiency measures into pupil-level and school-level effects. For higher education, while many analyses concern overall institutional efficiency, we examine also studies that take a more disaggregated approach, centred either around the performance of specific functional areas or that of individual employees.

Original languageEnglish
Title of host publicationData envelopment analysis
Subtitle of host publicationa handbook of empirical studies and applications
EditorsJoe Zhu
Place of PublicationNew York (US)
PublisherSpringer
Pages367-438
Number of pages72
ISBN (Electronic)978-1-4899-7684-0
ISBN (Print)978-1-4899-7682-6
DOIs
Publication statusPublished - 23 Mar 2016

Publication series

NameInternational Series in Operations Research and Management Science
PublisherSpringer
Volume238
ISSN (Print)0884-8289

Keywords

  • benchmarking
  • DEA
  • education
  • efficiency
  • higher education efficiency
  • pupil-level effects
  • school efficiency

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  • Cite this

    Thanassoulis, E., de Witte, K., Johnes, J., Johnes, G., Karagiannis, G., & Portela, C. S. (2016). Applications of data envelopment analysis in education. In J. Zhu (Ed.), Data envelopment analysis: a handbook of empirical studies and applications (pp. 367-438). (International Series in Operations Research and Management Science; Vol. 238). Springer. https://doi.org/10.1007/978-1-4899-7684-0_12