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Internal Benchmarking for Efficiency Evaluations Using Data Envelopment Analysis: A Review of Applications and Directions for Future Research

In: Advanced Mathematical Methods for Economic Efficiency Analysis

Author

Listed:
  • Fabio Sartori Piran

    (Research Group on Modeling for Learning - GMAP | UNISINOS)

  • Ana S. Camanho

    (Universidade do Porto)

  • Maria Conceição Silva

    (CEGE - Centro de Estudos em Gestão e Economia)

  • Daniel Pacheco Lacerda

    (Research Group on Modeling for Learning - GMAP | UNISINOS)

Abstract

Efficiency evaluations based on DEA are often associated with external benchmarking, usually requiring an expressive sample of comparable firms and access to sensitive information. However, some organizations present unique characteristics that make it challenging to find appropriate comparators. The literature often neglects the possibility of using DEA within an organization when comparable units are not available. In this context, internal benchmarking is a promising alternative that enables conducting relative efficiency assessments by introducing the time dimension in the assessment of a single firm. This chapter provides a literature review of internal longitudinal benchmarking assessments conducted with DEA. The applications in different sectors are explored, and the conditions under which the use of DEA for internal benchmarking is appropriate are analyzed. The main contributions and limitations of this approach are discussed.

Suggested Citation

  • Fabio Sartori Piran & Ana S. Camanho & Maria Conceição Silva & Daniel Pacheco Lacerda, 2023. "Internal Benchmarking for Efficiency Evaluations Using Data Envelopment Analysis: A Review of Applications and Directions for Future Research," Lecture Notes in Economics and Mathematical Systems, in: Pedro Macedo & Victor Moutinho & Mara Madaleno (ed.), Advanced Mathematical Methods for Economic Efficiency Analysis, pages 143-162, Springer.
    • Handle: RePEc:spr:lnechp:978-3-031-29583-6_9
    DOI: 10.1007/978-3-031-29583-6_9
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