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A Multi-Method Framework for Exploring Skill Structures in the IT Job Market.

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Title: A Multi-Method Framework for Exploring Skill Structures in the IT Job Market.
Authors: Ioanăș, Ioana1, Sandu, Andra1, Delcea, Camelia1 iviu.cotfas@ase.ro, Cotfa, Liviu-Adrian1, Domenteanu, Adrian1, Crișan, Alina-Georgiana1
Source: Journal of Grey System. 2026, Vol. 38 Issue 2, p105-122. 18p.
Subjects: Labor market, Core competencies, Clustering algorithms, Computer literacy, Multiagent systems, Information technology, Information technology personnel
Abstract: This paper is oriented towards investigating the changes in Romanian job market, more specifically focusing on examining the employees' skills in computers and information technology sector. Initially, 12 representative competences (Cognitive skills, Basic technical skills, Advanced technical skills, Software development, Cloud computing, Databases, Data analysis, Machine Learning & Deep Learning, Cybersecurity, Programming engineering, Soft skills, and Personal skills) were selected, and then a Google Formsbased online questionnaire was created and distributed for assessing the respondents' skills with respect to the mentioned categories, involving a Likert scale with 5 points. The case study covers the period between November and December 2024 and consists of 154 valid responses from individuals that are either working or looking for a job in the field of computers and information technology. A grey clustering approach was then used for splitting the respondents into multiple categories, considering their core capabilities. Moreover, the actors in the job market were further described based on the information collected from various sources, and a series of hypotheses were made. Finally, a context-specific ABM framework is proposed, including the agent's types, characteristics, and even possible interconnections, while the use of NetLogo software offers an interface which exposes the identified attributes of the agents under consideration. The insights uncovered in this paper represent essential data for the job market sector, highlighting the most common employees' skills, underdeveloped competences, along with the current employers' distribution and key categories of learning suppliers. This information can assist in further expanding the domain and better comprehending how the technology's evolution influences this area. [ABSTRACT FROM AUTHOR]
Copyright of Journal of Grey System is the property of Research Information Ltd. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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  Data: A Multi-Method Framework for Exploring Skill Structures in the IT Job Market.
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  Data: <searchLink fieldCode="JN" term="%22Journal+of+Grey+System%22">Journal of Grey System</searchLink>. 2026, Vol. 38 Issue 2, p105-122. 18p.
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  Data: This paper is oriented towards investigating the changes in Romanian job market, more specifically focusing on examining the employees' skills in computers and information technology sector. Initially, 12 representative competences (Cognitive skills, Basic technical skills, Advanced technical skills, Software development, Cloud computing, Databases, Data analysis, Machine Learning & Deep Learning, Cybersecurity, Programming engineering, Soft skills, and Personal skills) were selected, and then a Google Formsbased online questionnaire was created and distributed for assessing the respondents' skills with respect to the mentioned categories, involving a Likert scale with 5 points. The case study covers the period between November and December 2024 and consists of 154 valid responses from individuals that are either working or looking for a job in the field of computers and information technology. A grey clustering approach was then used for splitting the respondents into multiple categories, considering their core capabilities. Moreover, the actors in the job market were further described based on the information collected from various sources, and a series of hypotheses were made. Finally, a context-specific ABM framework is proposed, including the agent's types, characteristics, and even possible interconnections, while the use of NetLogo software offers an interface which exposes the identified attributes of the agents under consideration. The insights uncovered in this paper represent essential data for the job market sector, highlighting the most common employees' skills, underdeveloped competences, along with the current employers' distribution and key categories of learning suppliers. This information can assist in further expanding the domain and better comprehending how the technology's evolution influences this area. [ABSTRACT FROM AUTHOR]
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  Data: <i>Copyright of Journal of Grey System is the property of Research Information Ltd. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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        Text: English
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      – SubjectFull: Core competencies
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      – SubjectFull: Clustering algorithms
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      – SubjectFull: Computer literacy
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      – SubjectFull: Multiagent systems
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      – SubjectFull: Information technology
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      – SubjectFull: Information technology personnel
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      – TitleFull: A Multi-Method Framework for Exploring Skill Structures in the IT Job Market.
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            NameFull: Ioanăș, Ioana
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              Text: 2026
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