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A New Hybrid MCDM Model for Personnel Selection Based on a Novel Grey PIPRECIA and Grey OCRA Methods

Author

Listed:
  • Alptekin Ulutaş

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

  • Gabrijela Popovic

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

  • Dragisa Stanujkic

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

  • Darjan Karabasevic

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

  • Edmundas Kazimieras Zavadskas

    (Institute of Sustainable Construction, Vilnius Gediminas Technical University, LT 10223 Vilnius, Lithuania)

  • Zenonas Turskis

    (Institute of Sustainable Construction, Vilnius Gediminas Technical University, LT 10223 Vilnius, Lithuania)

Abstract

People represent one of the most significant resources of an organization, and therefore, personnel selection is one of the problems that organizations have increasingly been facing. The criteria that influence the final decision are usually opposing, so the application of multiple-criteria decision-making methods (MCDM) represents a suitable way for the facilitation of the given process. Additionally, the decision environment is characterized by the vagueness and uncertainty and, because of that, it is very hard to express the criteria over the exact crisp numbers. To acknowledge the unpredictability and obscurity of the available information important for the selection of the optimal candidate, a hybrid grey MCDM model for personnel selection is proposed in this paper. As an extension of the PIPRECIA method, the novel Grey Pivot Pairwise Relative Criteria Importance Assessment—the PIPRECIA-G method—is proposed and used for the determination of criteria importance. The PIPRECIA-G method preserved the good features of the PIPRECIA, but its superiority is reflected in its ability to deal with input data that are vague and grey. For the final ranking of the considered alternative candidates, the OCRA-G method is used. Basing the decision process and candidate selection on the two grey extended MCDM methods contributes to the increase of the reliability and confidence in the performed selection.

Suggested Citation

  • Alptekin Ulutaş & Gabrijela Popovic & Dragisa Stanujkic & Darjan Karabasevic & Edmundas Kazimieras Zavadskas & Zenonas Turskis, 2020. "A New Hybrid MCDM Model for Personnel Selection Based on a Novel Grey PIPRECIA and Grey OCRA Methods," Mathematics, MDPI, vol. 8(10), pages 1-14, October.
    • Handle: RePEc:gam:jmathe:v:8:y:2020:i:10:p:1698-:d:423340
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    References listed on IDEAS

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    1. Aleksandras Krylovas & Edmundas Kazimieras Zavadskas & Natalja Kosareva & Stanislav Dadelo, 2014. "New KEMIRA Method for Determining Criteria Priority and Weights in Solving MCDM Problem," International Journal of Information Technology & Decision Making (IJITDM), World Scientific Publishing Co. Pte. Ltd., vol. 13(06), pages 1119-1133.
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    Cited by:

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    4. Tsai, Pei-Hsuan & Kao, Ya-Ling & Kuo, Szu-Yu, 2023. "Exploring the critical factors influencing the outlying island talent recruitment and selection evaluation model: Empirical evidence from Penghu, Taiwan," Evaluation and Program Planning, Elsevier, vol. 99(C).
    5. Donghun Lee, 2022. "Knowledge Gradient: Capturing Value of Information in Iterative Decisions under Uncertainty," Mathematics, MDPI, vol. 10(23), pages 1-20, November.
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    8. Mohammad Javad Bidel & Hossein Safari & Hannan Amoozad Mahdiraji & Edmundas Kazimieras Zavadskas & Jurgita Antucheviciene, 2022. "A Framework for Project Delivery Systems via Hybrid Fuzzy Risk Analysis: Application and Extension in ICT," Mathematics, MDPI, vol. 10(17), pages 1-22, September.

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