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A New Grey Approach for Using SWARA and PIPRECIA Methods in a Group Decision-Making Environment

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  • Dragiša Stanujkić

    (Technical Faculty in Bor, University of Belgrade, Vojske Jugoslavije 12, 19210 Bor, Serbia)

  • Darjan Karabašević

    (Faculty of Applied Management, Economics and Finance, University Business Academy in Novi Sad, Jevrejska 24, 11000 Belgrade, Serbia)

  • Gabrijela Popović

    (Faculty of Applied Management, Economics and Finance, University Business Academy in Novi Sad, Jevrejska 24, 11000 Belgrade, Serbia)

  • Predrag S. Stanimirović

    (Faculty of Sciences and Mathematics, University of Niš, Višegradska 33, 18000 Niš, Serbia)

  • Muzafer Saračević

    (Department of Computer Sciences, University of Novi Pazar, Dimitrija Tucovića bb, 36300 Novi Pazar, Serbia)

  • Florentin Smarandache

    (Mathematics and Science Division, Gallup Campus, University of New Mexico, 705 Gurley Ave., Gallup, NM 87301, USA)

  • Vasilios N. Katsikis

    (Department of Economics, Division of Mathematics and Informatics, National and Kapodistrian University of Athens, Panepistimiopolis, 15784 Ilissia, Greece)

  • Alptekin Ulutaş

    (Department of International Trade and Logistics, Faculty of Economics and Administrative Sciences, Sivas Cumhuriyet University, 58140 Sivas, Turkey)

Abstract

The environment in which the decision-making process takes place is often characterized by uncertainty and vagueness and, because of that, sometimes it is very hard to express the criteria weights with crisp numbers. Therefore, the application of the Grey System Theory, i.e., grey numbers, in this case, is very convenient when it comes to determination of the criteria weights with partially known information. Besides, the criteria weights have a significant role in the multiple criteria decision-making process. Many ordinary multiple criteria decision-making methods are adapted for using grey numbers, and this is the case in this article as well. A new grey extension of the certain multiple criteria decision-making methods for the determination of the criteria weights is proposed. Therefore, the article aims to propose a new extension of the Step-wise Weight Assessment Ratio Analysis (SWARA) and PIvot Pairwise Relative Criteria Importance Assessment (PIPRECIA) methods adapted for group decision-making. In the proposed approach, attitudes of decision-makers are transformed into grey group attitudes, which allows taking advantage of the benefit that grey numbers provide over crisp numbers. The main advantage of the proposed approach in relation to the use of crisp numbers is the ability to conduct different analyses, i.e., considering different scenarios, such as pessimistic, optimistic, and so on. By varying the value of the whitening coefficient, different weights of the criteria can be obtained, and it should be emphasized that this approach gives the same weights as in the case of crisp numbers when the whitening coefficient has a value of 0.5. In addition, in this approach, the grey number was formed based on the median value of collected responses because it better maintains the deviation from the normal distribution of the collected responses. The application of the proposed approach was considered through two numerical illustrations, based on which appropriate conclusions were drawn.

Suggested Citation

  • Dragiša Stanujkić & Darjan Karabašević & Gabrijela Popović & Predrag S. Stanimirović & Muzafer Saračević & Florentin Smarandache & Vasilios N. Katsikis & Alptekin Ulutaş, 2021. "A New Grey Approach for Using SWARA and PIPRECIA Methods in a Group Decision-Making Environment," Mathematics, MDPI, vol. 9(13), pages 1-16, July.
    • Handle: RePEc:gam:jmathe:v:9:y:2021:i:13:p:1554-:d:587065
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    References listed on IDEAS

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    1. Yoram Wind & Thomas L. Saaty, 1980. "Marketing Applications of the Analytic Hierarchy Process," Management Science, INFORMS, vol. 26(7), pages 641-658, July.
    2. Rezaei, Jafar, 2015. "Best-worst multi-criteria decision-making method," Omega, Elsevier, vol. 53(C), pages 49-57.
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    Cited by:

    1. Aşkın Özdağoğlu & Gülin Zeynep Öztaş & Murat Kemal Keleş & Volkan Genç, 2021. "An Integrated PIPRECIA and COPRAS Method under Fuzzy Environment: A Case of Truck Tractor Selection," Alphanumeric Journal, Bahadir Fatih Yildirim, vol. 9(2), pages 269-298, December.
    2. Dragisa STANUJKIC & Darjan KARABASEVIC & Gabrijela POPOVIC & Cipriana SAVA, 2021. "Simplified Pivot Pairwise Relative Criteria Importance Assessment (Piprecia-S) Method," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(4), pages 141-154, December.

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