Community analysis in Slovenian labour network 2010-2020

Andonovikj, Viktor (author), Boškoski, Pavle (author), Evkoski, Bojan (author), Redek, Tjaša (author), Boshkoska, Biljana Mileva (author)

There is little evidence on the right approach on how to delineate the sub-networks in a labour market. The subject of research in this paper is computational influence identification of the labour force transitions between different professional occupations in the Slovenian labour network from 2010 to 2020. We use community detection algorithm to identify occupation groups and apply influence analysis on the Slovenian labour network from 2010 to 2020. This directly supports the decision-makers and employment services in identifying job opportunities for job-seekers based. The main conribution is using influence analysis to detect occupations and communities that had the most significant impact on the Slovenian labour market. The research is the first work to successfully apply community and influence analysis in the Slovenian labour network to the best of our knowledge. The paper carries several important implications, primarily highlighting the usage of existing data to increase employment levels.

• Language: English
• Keywords: Slovenia, labour market, decision making, directed network, community detection, Ensemble Louvain
• Work type: Article
• Typology: 1.01 - Original Scientific Article
• Organization: EF - School of Economics and Business
• Publication status: Published
• Publication version: Version of Record
• Year: 2022
• Number of pages: Str. 308–318
• Numbering: Vol. 31, no. S1
• PID: 20.500.12556/RUL-137146
• UDC: 331.5
• ISSN on article: 1246-0125
• DOI: 10.1080/12460125.2022.2070944
• COBISS.SI-ID: 107861251
• Publication date in RUL: 02.06.2022

Record is a part of a journal

• Title: Journal of decision systems
• Shortened title: J. decis. syst.
• Publisher: Taylor & Francis
• ISSN: 1246-0125
• COBISS.SI-ID: 515053593

Licences

• License: CC BY-NC-ND 4.0, Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International
• Link: http://creativecommons.org/licenses/by-nc-nd/4.0/
• Description: The most restrictive Creative Commons license. This only allows people to download and share the work for no commercial gain and for no other purposes.

Secondary language

• Language: Slovenian
• Keywords: Slovenija, trg dela, odločanje