scholarly journals A hybrid method of grey relational analysis and data envelopment analysis for evaluating and selecting efficient suppliers plus a novel ranking method for grey numbers

2014 ◽  
Vol 7 (5) ◽  
Author(s):  
Mohsen Sayyah Markabi ◽  
Mohammad Sabbagh
Keyword(s):  
Data Envelopment Analysis ◽  
Hybrid Method ◽  
Grey Relational Analysis ◽  
Ranking Method ◽  
Data Envelopment ◽  
Relational Analysis ◽  
Grey Relational

Evaluating Business Performance Using Data Envelopment Analysis and Grey Relational Analysis

2021 ◽  
pp. 115-148
Author(s):  
Tihana Škrinjarić ◽  
Boško Šego
Keyword(s):  
Data Envelopment Analysis ◽  
Grey Relational Analysis ◽  
Business Performance ◽  
Business Failure ◽  
Special Focus ◽  
Data Envelopment ◽  
Relational Analysis ◽  
Using Data ◽  
Grey Relational ◽  
A Company

Financial ratios are used in a variety of ways today. Empirical research is getting bigger, with a special focus on predicting business failure, the strength of a company, investment decision making, etc. This chapter focuses on two methodologies suitable to deal with many data to evaluate business performance. They are data envelopment analysis and grey relational analysis. The empirical part of the chapter conducts an empirical analysis with the aforementioned two approaches. Firms are ranked based on their performances and detailed interpretations are obtained so that managers within businesses can get useful information on how to utilize such an approach to modelling. This study implicates that using the two mentioned approaches can be useful when making investment decisions based on many data available for the decision maker. This is due to the methodology being suitable to handle big data and correctly quantifying the overall financial performance of a company.

scholarly journals A grey relational analysis based approach to the evaluation of Brazilian postgraduate programs in master of business administration

2017 ◽  
Vol 12 (4) ◽  
pp. 391-400
Author(s):  
Pauli A. A. Garcia ◽  
Fernanda A. de C. Duim
Keyword(s):  
Data Envelopment Analysis ◽  
Grey Relational Analysis ◽  
Future Research ◽  
Data Envelopment ◽  
Ministry Of Education ◽  
Education Development ◽  
Relational Analysis ◽  
College Programs ◽  
The Many ◽  
Grey Relational

The education development in Brazil has been influenced by government policies, especially those directed at higher learning. To judge the effectiveness of these policies it is necessary to evaluate the quality of the teaching offered, particularly with respect to public education. In this context, there have been many initiatives for new postgraduate programs. To be accredited, these programs must be approved by the Coordination for the Improvement of Higher Education Personnel (CAPES), part of the Ministry of Education. Among the many criteria considered by CAPES, the academic production is the most important. Many works proposing approaches to classify college programs based on faculty bibliographical output have been published; among these, those based on data envelopment analysis stand out. The present work uses grey relational analysis based approach. Another difference is that the information is considered on a master’s program not yet accredited, that is, one that still needs to be evaluated by CAPES. A classification is established for this program in relation to the ones already accredited along with a way to identify the improvement points and an improvement factor for each attribute considered. The results indicate that the approach is efficient in relation to that based on traditional data envelopment analysis and suggest areas for future research in this area.

scholarly journals An integrated approach to grey relational analysis, analytic hierarchy process and data envelopment analysis

2016 ◽  
Vol 9 (1) ◽  
pp. 71-86 ◽  
Author(s):  
Mohammad Sadegh Pakkar
Keyword(s):  
Data Envelopment Analysis ◽  
Grey Relational Analysis ◽  
Data Envelopment ◽  
Analytic Hierarchy ◽  
Content Type ◽  
Attribute Weights ◽  
Relational Analysis ◽  
Dea Models ◽  
Grey Relational ◽  
Hierarchy Process

Purpose This paper aims to propose an integration of the analytic hierarchy process (AHP) and data envelopment analysis (DEA) methods in a multiattribute grey relational analysis (GRA) methodology in which the attribute weights are completely unknown and the attribute values take the form of fuzzy numbers. Design/methodology/approach This research has been organized to proceed along the following steps: computing the grey relational coefficients for alternatives with respect to each attribute using a fuzzy GRA methodology. Grey relational coefficients provide the required (output) data for additive DEA models; computing the priority weights of attributes using the AHP method to impose weight bounds on attribute weights in additive DEA models; computing grey relational grades using a pair of additive DEA models to assess the performance of each alternative from the optimistic and pessimistic perspectives; and combining the optimistic and pessimistic grey relational grades using a compromise grade to assess the overall performance of each alternative. Findings The proposed approach provides a more reasonable and encompassing measure of performance, based on which the overall ranking position of alternatives is obtained. An illustrated example of a nuclear waste dump site selection is used to highlight the usefulness of the proposed approach. Originality/value This research is a step forward to overcome the current shortcomings in the weighting schemes of attributes in a fuzzy multiattribute GRA methodology.

scholarly journals Utility Exchange Traded Fund Performance Evaluation. A Comparative Approach Using Grey Relational Analysis and Data Envelopment Analysis Modelling

2019 ◽  
Vol 7 (4) ◽  
pp. 67 ◽  
Author(s):  
Ioannis E. Tsolas
Keyword(s):  
Data Envelopment Analysis ◽  
Grey Relational Analysis ◽  
Real Data ◽  
Comparative Approach ◽  
Data Envelopment ◽  
Exchange Traded Funds ◽  
Relational Analysis ◽  
Dea Models ◽  
Dea Approach ◽  
Grey Relational

Selecting funds is a common problem for investors who use published available data on fund indicators while they are selecting the funds. Since this process deals with more than one indicator, the investing issue becomes multi-criteria decision-making (MCDM) problem for the investors. Therefore, the purpose of this paper is to propose an effective approach that integrates grey relational analysis (GRA) and data envelopment analysis (DEA) for selecting the best utility exchange traded funds (ETFs). The current study uses GRA for deriving the grade relational coefficients and then puts them in the output side of competing no-input DEA models to derive weighed grey relational grades. Moreover, the ETFs are also evaluated by selected DEA models. This research is implemented with real data on utility ETFs available for three consecutive years (2008–2010). The results show that the top ETFs identified by the GRA-DEA approach are also DEA efficient. The proposed GRA-DEA approach is superior to conventional DEA as regards the fund ranking and therefore, it seems to be effective as a picking fund tool.

scholarly journals Financial Performance Assessment of Construction Firms by Means of RAM-Based Composite Indicators

Mathematics ◽  
2020 ◽  
Vol 8 (8) ◽  
pp. 1347
Author(s):  
Ioannis E. Tsolas
Keyword(s):  
Data Envelopment Analysis ◽  
Financial Performance ◽  
Composite Indicators ◽  
Upper Class ◽  
Practical Implementation ◽  
Data Envelopment ◽  
Tobit Regression ◽  
Construction Firms ◽  
Relational Analysis ◽  
Grey Relational

This paper aims to provide a novel construct that is based on data envelopment analysis (DEA) range adjusted measure (RAM) of efficiency and demonstrate its practical implementation by evaluating the financial performance of a sample of three upper-class contracting license (Classes 5–7) Greek construction firms. In a two-step framework, firm efficiency (i.e., composite indicators (CIs)) is produced firstly by means of RAM using single financial ratios, which are selected by grey relational analysis (GRA), and then Tobit regression is employed to model the CIs. In light of the results, only 4% of the sampled firms are efficient, and the firm ranking is consistent with the ranking of Grey Relational Grande (GRG) values produced by GRA. Moreover, the firms with a contracting license of the highest level (Class 7) appear not to be superior in efficiency to their counterparts that belong to Classes 5–6.

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