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A new inverse DEA cost efficiency model for estimating potential merger gains: a case of Canadian banks

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Abstract

Estimating potential gains from mergers is an important strategic decision-making problem. This paper introduces a new inverse data envelopment analysis (DEA) based on a cost efficiency model for estimating potential gains from mergers. There are restructuring scenarios for firms that want to minimize cost. The existing inverse DEA technical efficiency models are not appropriate for estimating merger gains in these situations. It is also shown that the proposed inverse DEA cost efficiency model can reveal more merger gains than the inverse DEA technical efficiency model. The applicability of the proposed method is shown through an application in Canada’s banking sector to determine the required level of inputs and outputs for a merged bank to achieve target levels of cost and technical efficiencies. The results highlight the potential financial gains to improving both technical and cost efficiencies as efficiency-seeking banks increasingly become large and complex institutions through growth, mergers and acquisitions in a financial environment that is being shaped by reforms and technological innovation.

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Authors and Affiliations

  1. Faculty of Business, University of New Brunswick at Saint John, Saint John, NB, E2L 4L5, Canada

    Gholam R. Amin & Mustapha Ibn Boamah

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  1. Gholam R. Amin
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  2. Mustapha Ibn Boamah
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Correspondence to Gholam R. Amin.

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Appendix

Appendix

See Table 4.

Table 4 Data for 28 Canadian banks (year 2017)
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Amin, G.R., Ibn Boamah, M. A new inverse DEA cost efficiency model for estimating potential merger gains: a case of Canadian banks. Ann Oper Res 295, 21–36 (2020). https://doi.org/10.1007/s10479-020-03667-9

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