Original Research

Quantitative efficiency assessment based on the dynamic slack-based network data envelopment analysis for commercial banks in Ghana

Zhixiang Zhou, Nelson Amowine, Dechun Huang
South African Journal of Economic and Management Sciences | Vol 21, No 1 | a1717 | DOI: https://doi.org/10.4102/sajems.v21i1.1717 | © 2018 Zhixiang Zhou, Nelson Amowine, Dechun Huang | This work is licensed under CC Attribution 4.0
Submitted: 30 November 2016 | Published: 09 April 2018

About the author(s)

Zhixiang Zhou, School of Economics, Hefei University of Technology, China
Nelson Amowine, School of Business, Hohai University, Ghana
Dechun Huang, Department of Economics and International Trade School of Business, Hohai University, China


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Abstract

Background: Gains in bank efficiency improvement have widely been regarded as one of the most effective and efficient means of ensuring sustainability of a financial system.

 

Aim: This article proposes a relative dynamic two-stage network data envelopment analysis model for measurement of bank efficiency based on the slack-based measure.

 

Setting: Twenty-seven banks in Ghana during the period of 2009–2014.

 

Methods: By considering simultaneous processes within the framework of two-stage data envelopment analysis, the slack-based measure approach identifies the sources of inefficiency in the banks.

 

Results: In the empirical analysis, non-performing loans are an undesirable output in one production process, which should also be treated as a carry-over factor; that is to say, some non-performing loans from the preceding year can be collected in the current year. The carry-over factors should be used to indicate the presence of performance gaps that exist in the banks. The proposed model was used to measure the efficiency of the 27 banks in Ghana during the period of 2009–2014. We also present useful suggestions for improvement in bank efficiency based on the empirical results.

 

Conclusion: The 27 main commercial banks in Ghana are far from efficient. For all banks, the efficiency score in the second stage is much higher than that of the first stage. That means more attention should be paid to the first stage of production in order to increase the banks’ efficiency.


Keywords

two-stage network DEA model; dynamic slack-based measure; banks; non-performing loans; Ghanaian banks

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