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A Comparative Analysis of Multi-Criteria Decision Methods for Personnel Selection: A Practical Approach

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  • Pablo A. Pinto-DelaCadena

    (Business School, Universidad Internacional del Ecuador, UIDE, Quito 170411, Ecuador
    Departament Matamàtiques per a l’Economia i l’Empresa, Universitat de València, 46022 Valencia, Spain)

  • Vicente Liern

    (Departament Matamàtiques per a l’Economia i l’Empresa, Universitat de València, 46022 Valencia, Spain)

  • Andrea Vinueza-Cabezas

    (Grupo de Investigación Bienestar, Salud y Sociedad, Escuela de Psicología y Educación, Universidad de Las Américas, Quito 170125, Ecuador)

Abstract

This research focused on decision-making supported by multi-criteria decision methods, specifically TOPSIS, OWA, and their respective variants within personnel selection. The study presented models aimed at facilitating the selection of the best candidate for a job through competency-based assessments and comparing the application of four methods across various scenarios. We employed methods such as TOPSIS, OWA, and two variations (Canós–Liern method and an OWA model based on mathematically replicating expert opinion). Each model provided distinct rankings and demonstrated adaptability to specific situations within a company. Furthermore, it was emphasized that each method could and should be tailored according to the company’s reality to derive maximum benefit from its implementation. A crucial aspect of securing the best candidates involves understanding the context and identifying the appropriate methodology.

Suggested Citation

  • Pablo A. Pinto-DelaCadena & Vicente Liern & Andrea Vinueza-Cabezas, 2024. "A Comparative Analysis of Multi-Criteria Decision Methods for Personnel Selection: A Practical Approach," Mathematics, MDPI, vol. 12(2), pages 1-18, January.
    • Handle: RePEc:gam:jmathe:v:12:y:2024:i:2:p:324-:d:1322198
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    References listed on IDEAS

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    1. Liang, Gin-Shuh & Wang, Mao-Jiun J., 1994. "Personnel selection using fuzzy MCDM algorithm," European Journal of Operational Research, Elsevier, vol. 78(1), pages 22-33, October.
    2. Canós, L. & Liern, V., 2008. "Soft computing-based aggregation methods for human resource management," European Journal of Operational Research, Elsevier, vol. 189(3), pages 669-681, September.
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