The purpose of the research presented in this paper is to provide a new approach related to the definition of variables in disaggregating branch expenses and income for evaluating the overall technical efficiency of bank branches by means of data envelopment analysis (DEA).
By applying an input minimization DEA model to a sample of bank branches of a large commercial bank in Greece, this study identifies pure technical and scale inefficiencies, efficiency and size relationship and returns to scale patterns. Moreover, it explores target setting strategies for inefficient branches.
Results indicate that branch size has an important influence on efficiency and that superior insights can be obtained by pure technical efficiency (PTE) and scale efficiency (SE), as constituent components of global technical efficiency (TE) than the information obtained from the analysis based on selected key performance indicators (KPIs) used by the bank under study.
A direction of future research would be to extend the analysis to incorporate environmental factors, such as branch location, local competitive environment, investment portfolio risk, among others, into the DEA assessment.
The study shows that DEA which provides an overall summary measure with respect to global TE and its constituent components PTE and SE can be used to complement the in‐house performance management system of the bank under study for the evaluation of its branch network.
From a policy perspective, this study highlights the use of DEA combined with statistical analysis to support the reduction of burden by means of either expense reduction or revenue enhancement.
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