Multicriteria decision-making models for the evaluation and appraisal of teachers' performance

Mazumdar, Avijit; Datta, Saurav; Mahapatra, Siba Sankar

doi:10.1504/ijpqm.2010.034406

Cited by 13 publications

(5 citation statements)

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“…But there is no clear methodology for assigning this priority weight for the factors. Therefore, expert opinion is indeed required to estimate these factors weight values (Mazumdar et al , 2010). Consequently, determining the teaching performance can be evaluated a multiple criteria decision making (MCDM) problem which involves evaluation of different alternatives based on multiple conflicting criteria.…”

Section: Introductionmentioning

confidence: 99%

“…So, different MCDM methods can be useful for solving to this problem. Although there are many studies on educational evaluation conducted by Shaw and Gaynor (1982), Meyer and Hofmeyr (1995), Tang et al (2004), Badri and Abdulla (2004), Chen and Tzeng (2009), Datta et al (2009), Mazumdar et al (2010) and Wu et al (2011), the number of study measured teaching performance by using MCDM techniques is too few.…”

Section: Introductionmentioning

confidence: 99%

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Business School ranking with grey relational analysis: the case of Turkey

Hamzaçebi²,

Baki³

2013

Grey Systems: Theory & Appl

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PurposeThe purpose of this paper is to explore the teaching performance of Turkish Business Schools (BSs). It also aims to determine the degree of importance of factors affecting the teaching performance of Turkish BSs. The final objective is to test the functionality and applicability of the model.Design/methodology/approachThis study presents a ranking approach based on grey relational analysis (GRA). While evaluating the BSs, data were collected for 19 Turkish BSs in terms of five main criteria such as OSS score; Number of faculty members; Number of students per faculty member; the mean of KPSS score; and the standard deviation of KPSS score. In the analysis, three weighted methods were integrated into the GRA in order to weight the criteria.FindingsAccording to this result, the main factor influencing the teaching performance of Turkish BSs is the OSS score. This study can also confirm that the results obtained from the ranking orders using the proposed methods are reliable and these results can help decision makers to identify the best alternative.Research limitations/implicationsIn order to provide benchmarking data more effectively, in future, it would be helpful to collect data from both foundation and state universities with a research focus. Moreover, as an interesting suggestion for future research, fuzzy environment may be further integrated into the framework of GRA.Originality/valueIn contrast to prior research, this study makes comparisons based on the scores of national exams instead of different bibliometric indicators. Furthermore, there are no studies which have used GRA and these weighted methods as combined in education sector.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Business School ranking with grey relational analysis: the case of Turkey

Hamzaçebi²,

Baki³

2013

Grey Systems: Theory & Appl

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“…As some significant examples of applying COPRAS and COPRAS-G method can be mentioned: Banaitiene et al (2008), Zavadskas et al (2008a;2008b;, Mazumdar et al (2010), Podvezko et al (2010) and Madhuri et al (2010).…”

Section: (Copras) Complex Proportional Assessmentmentioning

confidence: 99%

Comparative analysis of some prominent MCDM methods: A case of ranking Serbian banks

Stanujkić¹,

Djordjevic²,

Djordjevic³

2013

Serb J Management

132

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In the literature, many multiple criteria decision making methods have been proposed. There are also a number of papers, which are devoted to comparison of their characteristics and performances. However, a definitive answer to questions: which method is most suitable and which method is most effective is still actual. Therefore, in this paper, the use of some prominent multiple criteria decision making methods is considered on the example of ranking Serbian banks. The objective of this paper is not to determine which method is most appropriate for ranking banks. The objective of this paper is to emphasize that the use of various multiple criteria decision making methods sometimes can produce different ranking orders of alternatives, highlighted some reasons which lead to different results, and indicate that different results obtained by different MCDM methods are not just a random event, but rather reality.Keywords: MCDM, SAW, MOORA, GRA, CP, VIKOR, TOPSIS * Corresponding author: dragisa.stanujkic@fmz.edu.rs S e r b i a n J o u r n a l o f M a n a g e m e n t Serbian Journal of Management 8 (2) (2013) 213 -241www.sjm06.com DOI:10.5937/sjm8-3774 1968), Compromise programming (Zeleny, 1973;Yu, 1973), Analytic Hierarchy Process (AHP) method (Saaty, 1980), Technique for Ordering Preference by Similarity to Ideal Solution (TOPSIS) method (Hwang & Yoon, 1981), Preference Ranking Organisation Method for Enrichment Evaluations (PROMETHEE) method (Brans & Vincke, 1985), Grey Relational Analysis (GRA) proposed by Deng (1989) as part of Grey system theory, ELimination and Choice Expressing REality (ELECTRE) method (Roy, 1991), COmplex PRoportional ASsessment (COPRAS) method (Zavadskas et al., 1994) (Brauers & Zavadskas, 2010a).In the past, these methods have been used to solve many problems, which are documented in many professional and scientific journals. Numerous prominent papers presented research in MCDM, which is why we omit the reference to them in this paper.The above-mentioned MCDM methods transform multiple criteria decision-making process, i.e., Multiple Criteria optimization, in a single criterion decision-making optimization, which is much easier to solve. A number of authors have been identifying different phases (stages) in MCDM process, from which, in order to more clearly point out the objectives of this study, the following phases are emphasized:-criteria weights determination, -normalization, -aggregation, and -selection. A typical MCDM problem can be precisely presented in the following form:( 1) where D is decision matrix, x ij is performance of i-th alternative with respect to j-th criterion, W is weight vector, w j is weight of j-th criterion, i = 1,2, … m; m is the number of compared alternatives, j = 1,2, ..., n; n is the number of the criteria.Information stored in a decision matrix is usually incommensurable, i.e. performance ratings in relation to different criteria are usually expressed using different units of measure. Therefore, data should be transformed into comparable values, usi...

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“…Zavadskas and Kaklauskas (1996) developed a method of multiple criteria complex proportional assessment of projects for determining the priority and the utility degree of alternatives. Lithuanian as well as foreign scientists have been applying the original or expanded method for solving different engineering and management multi-attribute problems in the period of 1996-2011 (Zavadskas et al, 2009a;Mazumdar et al, 2010;Podvezko et al, 2010;Chatterjee et al, 2011). Some other authors have been applying modified COPRAS method.…”

Section: Introductionmentioning

confidence: 99%

Measuring Congruence of Ranking Results Applying Particular MCDM Methods

Antuchevičienė¹,

Zakarevičius²,

Zavadskas³

2011

Informatica

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The aim of the current research is to measure objective congruence (incongruence) of the results obtained in a process of multiple criteria analysis when applying different MCDM methods. The methodology for evaluation of ranking results is developed on the ground of a case study of the redevelopment of derelict buildings as well as on composed experimental tasks. Fuzzified COPRAS, TOPSIS and VIKOR methods are applied for ranking the alternatives. Calculation results are evaluated by applying mathematical statistics methods. A methodology for measuring the congruence (incongruence) of the relative significances of alternatives is proposed.

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Multicriteria decision-making models for the evaluation and appraisal of teachers' performance

Cited by 13 publications

References 13 publications

Business School ranking with grey relational analysis: the case of Turkey

Business School ranking with grey relational analysis: the case of Turkey

Comparative analysis of some prominent MCDM methods: A case of ranking Serbian banks

Measuring Congruence of Ranking Results Applying Particular MCDM Methods

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