Competency‐based IT personnel selection using a hybrid SWARA and ARAS‐G methodology

In the knowledge economy, human capital is a key factor in any organization to achieve a sustainable competitive advantage. Thus, selection of competent personnel is the most important function of human resource managers. However, because of a wide range of criteria and organizational factors that a...

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Veröffentlicht in:Human factors and ergonomics in manufacturing & service industries 2018-01, Vol.28 (1), p.5-16
Hauptverfasser: Heidary Dahooie, Jalil, Beheshti Jazan Abadi, Elham, Vanaki, Amir Salar, Firoozfar, Hamid Reza
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container_issue 1
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container_title Human factors and ergonomics in manufacturing & service industries
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creator Heidary Dahooie, Jalil
Beheshti Jazan Abadi, Elham
Vanaki, Amir Salar
Firoozfar, Hamid Reza
description In the knowledge economy, human capital is a key factor in any organization to achieve a sustainable competitive advantage. Thus, selection of competent personnel is the most important function of human resource managers. However, because of a wide range of criteria and organizational factors that affect the process, personnel selection is often regarded as a complex problem that can be answered through multicriteria decision‐making (MCDM) procedures. Despite the great importance of determining a comprehensive set of criteria, it has not gained enough attention in the literature. This study presents a competency framework with five criteria for choosing the best information technology (IT) expert from five alternatives. The stepwise weight assessment ratio analysis (SWARA) and grey additive ratio assessment (ARAS‐G) methods are also used to derive the criteria weights and provide the final alternative, respectively. The results reveal that subject competency is the major criteria in IT personnel selection.
doi_str_mv 10.1002/hfm.20713
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subjects ARAS‐G
Business competition
competency model
Criteria
Decision making
Human capital
Information technology
MCDM
Organizational aspects
Personnel
Personnel selection
SWARA
title Competency‐based IT personnel selection using a hybrid SWARA and ARAS‐G methodology
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