Journal of Productivity Analysis

, Volume 48, Issue 1, pp 51–61 | Cite as

Modelling generalized firms’ restructuring using inverse DEA

  • Gholam R. Amin
  • Ali Emrouznejad
  • Said Gattoufi


The key consideration for firms’ restructuring is improving their operational efficiencies. Market conditions often offer opportunities or generate threats that can be handled by restructuring scenarios through consolidation, to create synergy, or through split, to create reverse synergy. A generalized restructuring refers to a move in a business market where a homogeneous set of firms, a set of pre-restructuring decision making units (DMUs), proceed with a restructuring to produce a new set of post-restructuring entities in the same market to realize efficiency targets. This paper aims to develop a novel inverse Data Envelopment Analysis based methodology, called GInvDEA (Generalized Inverse DEA), for modeling the generalized restructuring. Moreover, the paper suggests a linear programming model that allows determining the lowest performance levels, measured by efficiency that can be achieved through a given generalized restructuring. An application in banking operations illustrates the theory developed in the paper.


Generalized restructuring Consolidation Split Efficiency Data Envelopment Analysis (DEA) Inverse DEA 

JEL Classifications

C44 C61 


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Copyright information

© Springer Science+Business Media New York 2017

Authors and Affiliations

  • Gholam R. Amin
    • 1
  • Ali Emrouznejad
    • 2
  • Said Gattoufi
    • 3
  1. 1.Faculty of BusinessUniversity of New Brunswick at Saint JohnSaint JohnCanada
  2. 2.Operations & Information Management Group, Aston Business SchoolAston UniversityBirminghamUK
  3. 3.Laboratoire SOIE, Institut Supérieur de GestionUniversité de TunisTunisTunisia

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