Well-designed packaging is intended to present a product in the best possible way, which would have a significant impact on sales improvement. Creating and finding the ideal design solution for packaging is an extremely complex process. Many characteristics of a packaging design can affect the level of customer satisfaction, where the different characteristics of the packaging tend to have a different significance. To make the problem more complex, the significance of characteristics of a packaging design is not the same for all customers. Therefore, creating and finding the ideal design solution for packaging often involves an evaluation of a number of variants, typically evaluated on the basis of multiple criteria, often with different significance. To provide an efficient approach for the selection of appropriate packaging, a framework for selecting the appropriate packaging design which meets customer preferences, based on the SWARA method and group decision making, is proposed. The usability and efficiency of the proposed framework is considered in the case of the selecting the appropriate packaging design for the wine of the autochthonous grape variety called Black Tamjanika. On the basis the considered examples, it can be concluded that SWARA method can be successfully used to solve many similar problems, and that in some cases may have some advantages over similar methods, such as AHP method or Conjoint Analysis. As an advantage of the proposed procedure can be mentioned a much smaller number of comparisons in pairs, compared with the AHP method, and much more comprehensible procedure for selecting the most acceptable alternative, compared with Conjoint Analysis. The proposed framework can also be easily adjusted to solve a significant number of MCDM problems.

In order to solve a number of real decision-making problems, over time, a number of multiple criteria decisionmaking methods have been proposed. The EDAS method is one of the newly proposed methods; its computational procedure can be identified as innovative and also based on verified approaches. An extension of the EDAS method adapted for the use of grey numbers is considered in this paper.

This paper proposes an extension of the ARAS method which, due to the use of intervalvalued fuzzy numbers, can be more appropriate for solving real-world problems. In order to overcome the complexity of real-world decision-making problems, the proposed extension also includes the use of linguistic variables and a group decision making approach. In order to highlight the proposed methodology an example of a faculty websites evaluation is considered.

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The application of information technology in all areas represents a significant facilitation of all business processes and activities. A competitive business system is hardly imaginable without adequate information technology. Therefore, this paper evaluates the conditions for the implementation of barcode technology in a warehouse system of a company for the manufacture of brown paper. SWOT (Strengths, Weaknesses, Opportunities, Threats) matrix was formed with a total of 27 elements based on which the benefits of the implementation of barcode technology in the warehouse system need to be analysed. For this purpose, a new fuzzy PIPRECIA (PIvot Pairwise RElative Criteria Importance Assessment) method has been developed to evaluate all elements in SWOT matrix. In addition, a part of the new developed approach includes new fuzzy scales for criterion assessment that are adapted to the methodology required by the fuzzy PIPRECIA method. To determine the consistency of the method, Spearman and Pearson correlation coefficients are applied. The results obtained in this study show that weaknesses are most noticeable in the current system. By implementing barcode technology, it is possible to create opportunities defined in SWOT matrix, which, in a very efficient way, allow elimination of the current weaknesses of the system.

Many real-world problems are complex and/or related to the manifestation of some form of uncertainty and/or prediction. Therefore the use of extended MCDM methods is more appropriate than the use of the other classic decision making methods. These methods are improved by the use of a form of fuzzy or interval grey numbers. In the field of operational research, during the previous period, numerous MCDM methods were formed, but one newly proposed, the MOORA method, is very specific and yet has no extension. Therefore, in this paper we combine concept of interval grey numbers and MOORA method in order to propose extended MOORA method which will be more appropriate to solve many complex real-world problems.

In the hiring process at companies, decision makers have underused the methods of the multi-criteria decision-making processes of selection of personnel. Therefore, this paper aims to establish a framework for the selection of candidates during the process of the recruitment and selection of personnel based on the SWARA and ARAS methods under uncertainties. The usability and efficiency of the proposed framework is considered in the conducted case study of the selection of candidate for the position of the sales manager.

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...