Online banking performance evaluation using data envelopment analysis and axiomatic fuzzy set clustering

Tao, Lili; Liu, Xiaodong; Chen, Yan

doi:10.1007/s11135-012-9767-3

Cited by 14 publications

(15 citation statements)

References 21 publications

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“…This measurement can be either output-oriented or input-oriented. With its application in the banking sector (Aly et al, 1990;Miller and Noulas, 1996;Chen 2002;Casu and Molyneux, 2003;Drake and Hall, 2003;Hauner, 2005;Tao et al, 2013;and Dipayan, 2014), DEA has expanded in dealing with the issues of heterogeneity in DMUs by integrating the DEA model and cluster analysis to alleviate the gaps in DEA modeling (Yang and Kuo, 2003;Paradi et al, 2012;and Maletic et al, 2013).…”

Section: Literature Reviewmentioning

confidence: 99%

“…Amirteimoori and Kordrostami (2014) clustered the operational units then evaluated each unit in its cluster. Tao et al, (2013) presented a hybrid model to conducting performance measurements using DEA and axiomatic fuzzy set clustering. Jahangoshai et al, (2018) integrated dynamic fuzzy C-means and Arti cial Neural Network with a DEA model to solve a multiple criteria optimization problem.…”

Section: Literature Reviewmentioning

confidence: 99%

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Cluster-Adjusted DEA Efficiency in the presence of Heterogeneity: An Application to Banking Sector

2020

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This paper improves on the issues of extreme data points and heterogeneity found in the linear programming data envelopment analysis (DEA) by presenting a cluster-adjusted DEA model (DEA with cluster approach). This analysis, based on efficiency, determines the number of clusters via Gap statistic and Elbow methods. We use the December quarterly panel data consisting of 122 U.S agricultural banks across 37 states from 2000 to 2017 to estimate the cluster-adjusted DEA model. Empirical results show differences in the estimated DEA efficiency measures with and without a clustering approach. Furthermore, using non-parametric tests, the results of Ansari-Bradley, Kruskal Wallis, and Wilcoxon Rank Sum tests suggest that the cluster-adjusted DEA model provides statistically better efficiency measures in comparison to the DEA model without a clustering approach.

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Section: Literature Reviewmentioning

confidence: 99%

Section: Literature Reviewmentioning

confidence: 99%

Cluster-Adjusted DEA Efficiency in the presence of Heterogeneity: An Application to Banking Sector

2020

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“…It can also be expressed as the use of the same quantity or less inputs to produce a given amount of output compared to other firms in a given strata. This technique has been explored in many fields including environmental, financial, security, power, and administration (Kwon and Lee, 2015;Tao et al, 2013;Tsolas and Charles, 2015;Wanke and Barros, 2014;Aristovnik et al, 2014;Fang and Li, 2015;Du et al, 2014;Lozano, 2015;Azadeh et al, 2015;Omrani, et al, 2015). The technique is used to evaluate performance across a set of homogeneous production units with multiple resources and products.…”

Section: The Data Envelopment Analysis (Dea)mentioning

confidence: 99%

Assessing Efficiency in the Pharmaceutical Sector of Nigeria

Obukohwo

Olele

Buzugbe

2019

CBN-JAS

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The study analyses, empirically, the efficiency of the Pharmaceutical sector in Nigeria. Employing a balanced panel of 20 pharmaceutical firms between 2012 and 2016, the paper uses a non-parametric technique (Data Envelopment Analysis) to analyze the firms' efficiency under the constant returns to scale (CRS) and variable returns to scale (VRS) assumptions. The results obtained shows inefficiency in the pharmaceutical sector as it operates under a decreasing return to scale. This calls for an appropriate policy mix to stimulate the efficiency of the pharmaceutical sector in Nigeria by enhancing research and development (R&D) as ell as regulations within the sector.

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“…In the past years, the AFS theory has been used with great success in various fields. This section discusses various applications based on AFS theory in the area of business intelligence (Bi et al, ; Ebonzo & Liu, ; Ebonzo et al, ; Y. Li et al, , , ; Tao et al, ; Y. Wang et al, , ; Xu et al, ), computer vision (Q. Li et al, ; Z. Li, Duan, et al, ; Z. Li, Zhang, Duan, Wang, et al, ; Ren et al, ; Sarkhel et al, ), financial data analysis (Guo et al, ; Tao et al, ; W. Wang & Liu, ), and clinical data analysis (Silva et al, ). The AFS theory provides us a useful tool to study the knowledge representation and inference that is significant in knowledge engineering, decision‐making, and intelligent systems.…”

Section: Applicationsmentioning

confidence: 99%

Knowledge discovery and semantic learning in the framework of axiomatic fuzzy set theory

Liu

Jia

Wang

et al. 2018

WIREs Data Min & Knowl

Self Cite

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Axiomatic fuzzy set (AFS) theory facilitates a way on how to transform data into fuzzy sets (membership functions) and implement their fuzzy logic operations, which provides a flexible and powerful tool for representing human knowledge and emulate human recognition process. In recent years, AFS theory has received increasing interest. In this survey, we report the current developments of theoretical research and practical advances in the AFS theory. We first review some notion and foundations of the theory with an illustrative example, then, we focus on the various extensions of AFS theory for knowledge discovery, including clustering, classification, rough sets, formal concept analysis, and other learning tasks. Due to its unique characteristics of semantic representation, AFS theory has been applied in multiple domains, such as business intelligence, computer vision, financial analysis, and clinical data analysis. This survey provides a comprehensive view of these advances in AFS theory and its potential perspectives. This article is categorized under: Technologies > Computational Intelligence

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Online banking performance evaluation using data envelopment analysis and axiomatic fuzzy set clustering

Cited by 14 publications

References 21 publications

Cluster-Adjusted DEA Efficiency in the presence of Heterogeneity: An Application to Banking Sector

Cluster-Adjusted DEA Efficiency in the presence of Heterogeneity: An Application to Banking Sector

Assessing Efficiency in the Pharmaceutical Sector of Nigeria

Knowledge discovery and semantic learning in the framework of axiomatic fuzzy set theory

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