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Flexible target setting in mergers using inverse data envelopment analysis

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  • Gholam R. Amin
  • Amar Oukil

Abstract

In a merger, one important issue is the estimation of the levels of inputs and outputs required from each merging decision-making unit (DMU) so that the merged entity can realise a desired efficiency target. This paper uses the potential of inverse data envelopment analysis (InvDEA) to build a flexible target setting of the inputs and outputs. This study expands the application of the InvDEA methodology in a merger by introducing a flexible target setting that allows the decision maker to favour specific input in the target setting. We use a dataset of 30 universities to illustrate the practical scope of the proposed flexible target setting method, which can obviously be employed in any other merging context.

Suggested Citation

  • Gholam R. Amin & Amar Oukil, 2019. "Flexible target setting in mergers using inverse data envelopment analysis," International Journal of Operational Research, Inderscience Enterprises Ltd, vol. 35(3), pages 301-317.
    • Handle: RePEc:ids:ijores:v:35:y:2019:i:3:p:301-317
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    Citations

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    Cited by:

    1. Gholam R. Amin & Mustapha Ibn Boamah, 2021. "A two‐stage inverse data envelopment analysis approach for estimating potential merger gains in the US banking sector," Managerial and Decision Economics, John Wiley & Sons, Ltd., vol. 42(6), pages 1454-1465, September.
    2. Amar Oukil & Slim Zekri, 2021. "Investigating farming efficiency through a two stage analytical approach: Application to the agricultural sector in Northern Oman," Papers 2104.10943, arXiv.org.
    3. Gholam R. Amin & Mustapha Ibn Boamah, 2020. "A new inverse DEA cost efficiency model for estimating potential merger gains: a case of Canadian banks," Annals of Operations Research, Springer, vol. 295(1), pages 21-36, December.

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