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Measuring the performance of the Indian banking industry: data envelopment window analysis approach. BENCHMARKING-AN INTERNATIONAL JOURNAL 2021. [DOI: 10.1108/bij-03-2021-0115] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
Abstract
Purpose
This study aims to empirically evaluate the performance of commercial banks operating in India.
Design/methodology/approach
The efficiency of the commercial banks is evaluated using the data envelopment analysis (DEA) approach. We measure the technical, pure technical and scale efficiency of the sampled conventional banks using the input-oriented model. We employed an extended DEA window analysis approach based on a panel sample of 47 banks in the Indian scenario. The period of study is from 2009 to 2018.
Findings
The results obtained from CRS and VRS measures envisage that Indian banks have failed to manage their inputs efficiently and convert them into outputs. It implies that Indian banks do not operate at an optimum level. Moreover, the results show that public banks exhibit superior efficiency scores followed by private and foreign banks. Apart from the aggregate sector level, we also investigate the performance of Indian banks at the individual level for in-depth analysis. The individual bank-level analysis reports that the public sector banks (PSBs) are the most efficient followed by foreign banks, whereas, the least efficient are the private banks.
Research limitations/implications
The findings of our study have implications for government, financial institutions and policymakers to access the verve and flexibility of the Indian banking system. The government should consider restructuring inefficient banks to enhance overall performance. This can be considered by improvement in managerial efficiency, efficient allocation of scarce resources and appropriate scale of operation. However, the findings of the study should be interpreted in light of the period of study for the banks being operational (as we filter out banks that ceased to exist) in India and empirical methods employed. The results may vary if alternative measures are used.
Originality/value
The present paper investigates the efficiency of the Indian banking sector employing the Data Envelopment Window Analysis (DEWA) technique. To the best of our knowledge, the present study is perhaps the first one to employ the DEWA measure on the Indian banking industry to gauge their performance over time.
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Karbassi Yazdi A, Abdi F. Designing robust model for banks benchmarking based on Rembrandt method and DEA. BENCHMARKING-AN INTERNATIONAL JOURNAL 2017. [DOI: 10.1108/bij-01-2015-0001] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
Abstract
Purpose
The purpose of this paper is to find excellent banks on the basis of identified variables. First of all, banks are evaluated based on operation costs, deposits, staff, investments, net profit, and loans variables. Subsequently, these variables are categorized into inputs and outputs. The performances of the banks based on these variables are analyzed by data envelopment analysis (DEA) method to find efficiency and inefficiency of decision making units (DMUs).
Design/methodology/approach
This research is aimed to determine the best banks based on predetermined indicators. The indicators are categorized into inputs and outputs. DEA method is used to find efficiency and inefficiency of DMU. However, the aim is to find the efficient banks and to implement the model by using AP Super Efficiency method in order to find the most efficient unit for benchmarking. However, some inputs and outputs have more priority for banks than the others, as a result it will require some changes.
Findings
The results indicate that among 13 banks, including ten public and three private, solely five public banks are efficient. Moreover, DEA is used as a benchmarking tool for inefficient banks to be efficient. Among these banks ten of them are public banks and three are private. Among efficient ones, all are public banks. Moreover, five of public banks and three of private are inefficient.
Originality/value
In some cases, inputs and outputs have more priority for DMs than the others, as a result it will require some changes. Also, if one of the inputs or outputs is larger in number than the others, the DMU becomes efficient, despite its low priority. Thus, for solving this problem, the indicators of this research are ranked by Rembrandt method considering the existing ones to find the best banks (best DMU) based on their performance and the relevant indicators.
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Progressive Time-Weighted Dynamic Energy Efficiency, Energy Decoupling Rate, and Decarbonization: An Empirical Study on G7 and BRICS. SUSTAINABILITY 2016. [DOI: 10.3390/su8090928] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
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