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Considerations About Adding Aggregated Variables to the DEA Model

  • Filipe Giovani Bonin BisoffiEmail author
  • Renata Maria Ganselli Stevaux
  • Victor Henrique Duarte de Oliveira
  • Sérgio Ricardo Barbosa
Chapter
  • 407 Downloads
Part of the Telecommunications and Information Technology book series (TIT)

Abstract

Even in a scenario where Big Data has increasingly become a part of company structure, it is not uncommon to come across statistical or mathematical analysis processes lacking sufficient available observations to consider all the business variables of interest. As a consequence, it affects, in different levels, all analytic methods whether statistical or mathematical. Specifically in the case of the benchmarking model known as DEA (Data Envelopment Analysis), the convergence of involved algorithms is directly dependent on the relation between the quantity of observations and the quantity of variable considered. Any attempt to circumvent the conditions imposed by these methodologies will result in loss of information. The scope of this study is to propose an alternative method to deal with this problem when the DEA model is applied and minimize information loss.

Keywords

DEA Confidence interval Nonparametric regression analysis 

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Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  • Filipe Giovani Bonin Bisoffi
    • 1
    Email author
  • Renata Maria Ganselli Stevaux
    • 1
  • Victor Henrique Duarte de Oliveira
    • 2
  • Sérgio Ricardo Barbosa
    • 2
  1. 1.Decision Management Support & Applications DepartmentCPqD Research and Development Center in TelecommunicationsCampinasBrazil
  2. 2.CEMIG Distribuição S.A.Belo HorizonteBrazil

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