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Competency‐based IT personnel selection using a hybrid SWARA and ARAS‐G methodology
Author(s) -
Heidary Dahooie Jalil,
Beheshti Jazan Abadi Elham,
Vanaki Amir Salar,
Firoozfar Hamid Reza
Publication year - 2018
Publication title -
human factors and ergonomics in manufacturing and service industries
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.408
H-Index - 39
eISSN - 1520-6564
pISSN - 1090-8471
DOI - 10.1002/hfm.20713
Subject(s) - multiple criteria decision analysis , selection (genetic algorithm) , function (biology) , computer science , set (abstract data type) , process (computing) , risk analysis (engineering) , knowledge management , operations research , business , engineering , artificial intelligence , evolutionary biology , biology , programming language , operating system
Abstract 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.