Indian banks' productivity ranking via Data Envelopment Analysis and Fuzzy Multi-Attribute Decision-Making hybrid

Pramodh, Chelimala; Ravi, Vadlamani; Nagabhushanam, T.

doi:10.1504/ijids.2008.020035

Cited by 19 publications

(7 citation statements)

References 52 publications

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“…Every respondent describes his judgment about the innovation degree in his bank by the following linguistic terms; Not at all satisfied, unsatisfied, moderately satisfied, satisfied, and very satisfied. These linguistic expressions were converted into fuzzy numbers as (3,4,5), (6,7,8), (9,10,11), (12,13,14) and (15,16,17), respectively. In order to establish the imprecise value of the innovation level for each bank, we used the following aggregation function.…”

Section: Used Datamentioning

confidence: 99%

Assessing the Efficiency of commercial Tunisian Banks using Fuzzy Data Envelopment Analysis

Tlig¹,

Hamed²

2017

Data Envelopment Analysis and Decision Science

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The banking sector is of great importance to Tunisian's economy. Major commercial banks continue to spend high proportion of their budgets on new technologies and innovation in order to satisfy their customers and enhance their competitiveness. Consequently, performance analysis has become part of their management practices.This paper aims to evaluate the efficiency of commercial Tunisian banks in terms of several crisp and imprecise data. Two approaches of fuzzy data envelopment analysis (FDEA), the possibility approach and the approach based on relations between fuzzy numbers (BRONF), are used to obtain the efficiency score of each bank. The results show that, in a competitive environment, no-financial inputs and outputs should be taken into account in order to obtain credible and realistic efficiency scores.

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Section: Used Datamentioning

confidence: 99%

Assessing the Efficiency of commercial Tunisian Banks using Fuzzy Data Envelopment Analysis

Tlig¹,

Hamed²

2017

Data Envelopment Analysis and Decision Science

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“…Since 1985 DEA has been extensively functional in the banking sector. DEA has been applied widely in measuring efficiency of Indian banks by Pramodh et al (2008). Berger and Humphery (1997) reviewed 130 efficiency studies of financial institutions including commercial banks and explained that efficiency estimates of financial institutions in 21 countries vary across studies due to use of different methods in different studies.…”

Section: Literature Studymentioning

confidence: 99%

Information Technology Role on Private Commercial Banks Efficiency with Cost and Profit DEA Technology

Baten¹

2021

AMBR

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<p align="justify">IT plays a pivotal role to improve the competitiveness of the bank by providing its existing customers with satisfactory services, while at the same time bringing about a significant reduction in cost. This study measures the effect of IT factors on cost and profit efficiency of Private Commercial Banks (PCBs) in Bangladesh employing cost and profit Data Envelopment Analysis (DEA) and Ordinary Least Square (OLS) method. The average cost efficiency (41.4%) was recorded higher than the average profit efficiency (18.8%) for PCBs. Prime bank was the most cost and profit efficient among PCBs. The Credit card transaction (0.000006) and Credit card expenses (0.0002) were observed positively significant for cost efficiency of PCBs and the IT personnel expenses (0.0015) and Credit card transaction (0.00008) were positively significant for profit efficiency of PCBs. IT factors were found more significant for PCBs in profit efficiency. The results attained from this study could aid government, managers and depositors to remove the hindrance of progress in Bangladesh. This type of empirical analysis could be applied in another sector of the economic market.</p>

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“…Some recent examples include the financial services industry (Malhotra et al, 2009); banking sector (Afsharian et al, 2012;Pramodh et al, 2008;Yang and Morita, 2012); organisational performance (Poitier and Cho, 2011); seaport operations (Ablanedo-Rosas et al, 2010); airport operations (Ablanedo-Rosas and Gemoets, 2010); air major carriers (Martin and Roman, 2010); companies experiencing mergers and acquisitions (Wu et al, 2011); supply chain performance (Dharmapala, 2008); countries' performance in the Olympic Games (Wu and Liang, 2010); and mobile phone selection (Mahdavi et al, 2008), just to cite a few. Studies have been carried out in the various sectors of the economy and society.…”

Section: Data Envelopment Analysismentioning

confidence: 99%

Evaluating telecommunications efficiency in China with data envelopment analysis

Lundy

Ablanedo-Rosas

Gao³

et al. 2014

IJIDS

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Telephone communications, mobile services, and internet traffic continue to grow in China. As more people in China become telecommunications customers, China must find effective and efficient ways to provide these services in order to compete in the global market. This research examines the efficiency of telecommunications services for 31 Chinese provinces by using data envelopment analysis (DEA) models. The results show that 81% and 71% of the Chinese provinces were operating efficiently according to the variable and constant returns to scale DEA model respectively. Additionally, super efficiency scores were computed in order to differentiate and rank the efficient Chinese provinces.

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Indian banks' productivity ranking via Data Envelopment Analysis and Fuzzy Multi-Attribute Decision-Making hybrid

Cited by 19 publications

References 52 publications

Assessing the Efficiency of commercial Tunisian Banks using Fuzzy Data Envelopment Analysis

Assessing the Efficiency of commercial Tunisian Banks using Fuzzy Data Envelopment Analysis

Information Technology Role on Private Commercial Banks Efficiency with Cost and Profit DEA Technology

Evaluating telecommunications efficiency in China with data envelopment analysis

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