A new inverse DEA method for merging banks

Gattoufi, Said; Amin, Gholam R.; Emrouznejad, Ali

doi:10.1093/imaman/dps027

Cited by 97 publications

(81 citation statements)

References 32 publications

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“…Seiford and Zhu (1999) applied an output-oriented DEA approach to examining the performance of two hypothetical banks that were resulted from two banks' M&As. Gattoufi et al (2014) developed a new inverse DEA approach to obtain the inputs and outputs for a merged bank if an efficiency target is set. Lozano (2013) proposed a cost minimization model and obtained the potential cost saving to help decision makers to find the best partner for a horizontal cooperation.…”

Section: Introductionmentioning

confidence: 99%

Estimation of potential gains from bank mergers: A novel two-stage cost efficiency DEA model

Shi

Emrouznejad

et al. 2017

Journal of the Operational Research Society

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This paper develops a novel two-stage cost efficiency model to estimate and decompose the potential gains from Mergers and Acquisitions (M&As). In this model, a hypothetical DMU is defined as a combination of two or more candidate DMUs. The hypothetical DMU would surpass the traditional Production Possibility Set (PPS). In order to solve the problem, a Merger Production Possibility Set (PPS M ) is constructed. The model minimizes the total cost of the hypothetical DMU while maintaining its outputs at the current level, and estimates the overall merger efficiency by comparing its minimal total cost with its actual cost. Moreover, the overall merger efficiency could be decomposed into technical efficiency, harmony efficiency, and scale efficiency. We show that the model can be extended to a two-stage structure and these efficiencies can be decomposed to both sub-systems. To show the usefulness of the proposed approach, we applied it to a real dataset of top 20 most competitive Chinese City Commercial Banks (CCBs). We concluded that (1) there exist considerably potential gains for the proposed merged banks. (2) It is also shown that the main impact on potential merger gains are from technical and harmony efficiency. (3) As an interesting result we found that the scale effect works against the merger, indicating that it is not favorable for a full-scale merger.

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Section: Introductionmentioning

confidence: 99%

Estimation of potential gains from bank mergers: A novel two-stage cost efficiency DEA model

Shi

Emrouznejad

et al. 2017

Journal of the Operational Research Society

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“…The mathematical modeling suggested for merger by the InvDEA approach (Gattoufi et al 2014) is presented hereafter. It allows determining the levels of inputs and outputs for a single merged firm, following a merger between at least two firms.…”

Section: Invdea For Mergermentioning

confidence: 99%

“…Any restructuring decision is usually accompanied with a predefined performance target to be reached (Wu et al, 2014, Gaughan, 2010Gattoufi et al 2014). The assessment of the potential gains, compared with the predefined target, has been discussed in the Data Envelopment Analysis (DEA) literature, benefiting from the ability of DEA modeling to assess relative efficiency.…”

Section: Introductionmentioning

confidence: 99%

“…More recently, Zhang and Cui (2016) presented an extension of the inverse DEA model and Lim (2016) introduced an inverse DEA model with the frontier change for setting a new product target. Gattoufi et al (2014) proposed a methodology to identify the required reduction in inputs, or increase in outputs depending on whether the analysis is input or output oriented, in order to realize a predefined efficiency target for a merger between at least two merging DMUs producing a single merged DMU. However, generality imposes two forms of restructuring namely consolidation and split.…”

Section: Introductionmentioning

confidence: 99%

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Modelling generalized firms’ restructuring using inverse DEA

2017

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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.

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“…The Data Envelopment Analysis (DEA) is respecifi ed by [15] in the form of an inverse DEA to assess the efforts that the acquirer or a merger has to make in order to reach a certain level of effi ciency of the process.…”

Section: The Banking Sectormentioning

confidence: 99%