PERSONNEL SELECTION FOR PROMOTION USING AN INTEGRATED FUZZY ANALYTIC HIERARCHY PROCESS-GREY RELATIONAL ANALYSIS METHODOLOGY: A REAL CASE STUDY

Abstract

The basic idea of personnel selection is to choose the best candidate for a job. Personnel selection is crucial in human resources management and also a very important issue for both academicians and industrialists. Personnel selection can be handled as a Multi Criteria Decision Making (MCDM) problem.

The aim of this paper is to determine the best personnel using the integrated Fuzzy Analytic Hierarchy Process (FAHP) and Grey Relational Analysis (GRA) methodology. FAHP is used to determine the importance weights of personnel (17 alternatives) according to personnel selection criteria (22 subcriteria are categorized under 5 main criteria).  Then, obtained fuzzy importance weights defuzzified by centroid method. After that, defuzzified importance weights of personnel according to personnel selection criteria are integrated with a GRA model to prioritize the personnel alternatives. For a case study in Turkey, the ranking of the alternatives is calculated using the integrated FAHP-GRA model, and the best-performing personnel is selected for promotion. According to this methodology, managers/human resources department can easily predict how they can evaluate and promote employees.

The proposed methodology provides less data and can analyze many factors that can overcome the disadvantages of statistics methods in the literature. The main contribution of this study is to reduce data for a preference matrix using the integrated methodology. As a result, the number of transactions decrease. To the authors’ knowledge, this will be the first study which integrates Fuzzy Analytic Hierarchy Process (FAHP) and Grey Relational Analysis (GRA) methodologies for human resources in the area of industrial engineering.

Keywords

• Personnel Selection,Personnel Selection Criteria,Multi Criteria Decision Making (MCDM),Fuzzy Analytic Hierarchy Process (FAHP),Grey Relational Analysis (GRA)

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