Modelling generalized firms' restructuring using inverse DEA

Gholam R. Amin, Ali Emrouznejad*, Said Gattoufi

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review


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.
Original languageEnglish
Pages (from-to)51–61
Number of pages11
JournalJournal of Productivity Analysis
Early online date5 May 2017
Publication statusPublished - Aug 2017

Bibliographical note

The final publication is available at Springer via


  • generalized restructuring
  • split
  • consolidation
  • efficiency
  • inverse DEA
  • data envelopment analysis
  • DEA


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