Selection Input Output by Restriction Using DEA Models Based on a Fuzzy Delphi Approach and Expert Information

Arsad, Roslah; Abdullah, Mohammad; Alias, Suriana; Isa, Zaidi

doi:10.1088/1742-6596/892/1/012010

Cited by 3 publications

(2 citation statements)

References 12 publications

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“…The DEA method is a non-parametric approach that has been widely employed in a variety of disciplines as an efficiency performance measurement tool for comparing a set of DMU entities such as firms (Arsad et al, 2017), bank industry (Jha et al, 2013) and investments (Lin & Yang, 2014). These DMUs utilize the asset of multiple homogenous inputs to produce a set of multiple homogenous outputs.…”

Section: Literature Reviewmentioning

confidence: 99%

Stock Selection using the Data Envelopment Analysis Models and DuPont Analysis

Arsad¹,

Isa²,

Abidin³

et al. 2022

IJARBSS

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Analysing performance using the financial ratio is challenging for many investors and researchers. The purpose of this study is to evaluate efficiency performance of decisionmaking units (DMUs) which is stocks company of using production frontier-based and accounting-based approaches. Thus, the data envelopment analysis (DEA) models and DuPont analysis were applied. Specifically, DuPont analysis was utilized to evaluate three different aspects: profitability, the efficiency of assets utilization and financial leverage. The return on equity (ROE) was calculated to rank the companies' performance. Meanwhile, the estimation method of DEA computed the efficiency scores and ranked the companies accordingly based on the ROE, return on assets, earnings per share, net profit margin, price to earnings ratio, debt to equity ratio and asset turnover. The major results showed that DMUs (company) gave different picture performance rankings with different approaches. The finding also revealed that the results from DEA method, gave more comprehensive analysis in term of efficiency measurement, whereas DuPont presented good analysis because it provided information for investors if the highest return is the main objective for them. Additionally, the analysis also provided an indication whether a company can earn a higher return if it generates a high net profit margin; if it uses its assets effectively to generate more sales and if it has a high financial leverage.

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Section: Literature Reviewmentioning

confidence: 99%

Stock Selection using the Data Envelopment Analysis Models and DuPont Analysis

Arsad¹,

Isa²,

Abidin³

et al. 2022

IJARBSS

Self Cite

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“…Before we proceed with the application of the proposed DEA analysis with regressionbased feedback, we hereafter position our contribution with respect to the literature on variable selection in DEA. So far, such literature could be divided into (1) Judgemental Screening or Expert Opinions such as Fuzzy Delphi Method (Arsad et al 2017); (2) (Li et al 2017), Directional Technology Distance Function (Guarda et al 2013), Regression Analysis (Lewin et al 1982;Fanchon 2003;Ruggiero 2005;Luo et al 2012;Golany and Roll 1989); Decision Tree Analysis (Lim 2008;Jain et al 2016), and Genetic Algorithms (Madhanagopal and Chandrasekaran 2014). Our contribution falls into the subcategory of Regression Analysis; however, unlike previous contributions, ours use regression analysis within a feedback mechanism and allows for no-inputs or no-outputs situations.…”

Section: Formulation Descriptionmentioning

confidence: 99%

Assessing efficiency profiles of UK commercial banks: a DEA analysis with regression-based feedback

Ouenniche

Carrales

2018

Ann Oper Res

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Data envelopment analysis (DEA) has witnessed increasing popularity in banking studies since 1985. In this paper, we propose a new DEA-based analysis framework with a regression-based feedback mechanism, where regression analysis provides DEA with feedback that informs about the relevance of the inputs and the outputs chosen by the analyst. Unlike previous studies, the DEA models used within the proposed framework could use both inputs and outputs, only inputs, or only outputs. So far, the UK banking sector remains relatively under researched despite its crucial importance to the UK economy. We use the proposed framework to address several research questions related to both the efficiency of the UK commercial banking sector and DEA analyses with and without regression-based feedback. Empirical results suggest that, on average, the commercial banks operating in the UK-whether domestic or foreign-are yet to achieve acceptable levels of overall technical efficiency, pure technical efficiency, and scale efficiency. On the other hand, DEA analyses with and without a linear regression-based feedback mechanism seem to provide consistent findings; however, in general DEA analyses without feedback tend to over-or under-estimate efficiency scores depending on the orientation of the analyses. Furthermore, in general, a linear regression-based feedback mechanism proves effective at improving discrimination in DEA analyses unless the initial choice of inputs and outputs is well informed.Keywords Data envelopment analysis · Efficiency · UK commercial banks · DEA models without explicit inputs · DEA models without explicit outputs

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Evaluating the efficiency of stock performance: A Cobb-Douglas function in stochastic frontier analysis approach

Arsad

Isa

2019

The 2018 UKM FST POSTGRADUATE COLLOQUIUM: Proceedings of the Universiti Kebangsaan Malaysia, Faculty of Science and Technology

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Selection Input Output by Restriction Using DEA Models Based on a Fuzzy Delphi Approach and Expert Information

Cited by 3 publications

References 12 publications

Stock Selection using the Data Envelopment Analysis Models and DuPont Analysis

Stock Selection using the Data Envelopment Analysis Models and DuPont Analysis

Assessing efficiency profiles of UK commercial banks: a DEA analysis with regression-based feedback

Evaluating the efficiency of stock performance: A Cobb-Douglas function in stochastic frontier analysis approach

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