THE IMPORTANCE OF USING SMART DATA TO ANALYZE SKILLS IN THE LABOR MARKET
Keywords:
labor market, skills, skills matching, smart data, online job vacancies.Abstract
The needs of the workforce are constantly changing as a result of global concerns about digitization, production automation, the introduction of new technologies and industry 4.0. Therefore, the labor market needs a continuous reassessment of labor skills in the context of digitalization and the industrial revolution. The paper will study the change in perspective of the structure of the employed population by occupational groups and in high-tech economy of Romania compared to UE27 and the most requested skills currently in online job postings in various fields, based on traditional and intelligent data from Cedefop. It is also intended to understand how the use of BigData can facilitate labor market decision-making. The analysis of the skills required in the jobs posted online from various fields in Romania, in 2020, suggests importance of digital and contextual skills having in view that in the top is ,,accessing and analyzing digital data”, followed by ,,working with others” and ,,using digital tools for collaboration, content creation and problem solving”.References
APQC, 2019. Trending Tools and Technologies in HR, apud Baker, P., Blockchain HR technology: 5 use cases impacting human resources, https://www.techtarget.com/searchhrsoftware/tip/Blockchain-HR-technology-5-use-cases-impacting-human-resources.
Berkers, H.; Mol, S.T.; Kobayashi, V.; Kismihók, G.; Hartog, den D. 2019. “Big (data) insights into what employees do: A comparison between task inventory and text mining job analysis methods”, in H. A. Berkers, What do you do and who do you think you are? Activities speak louder than words, PhD thesis, University of Amsterdam, pp. 12–57. Available at: https://pure.uva.nl/ws/files/31377407/Chapter_2.pdf.
Cedefop (2019), Online job vacancies and skills analysis: a Cedefop pan-European approach, 2019. https://www.cedefop.europa.eu/en/publications-and-resources/publications/4172.
Comisia Europeană, 2021. Indicele economiei și societății digitale (DESI) 2021 România.
ETF (2019), Big Data for Labour Market Intelligence Systems – a brief introductory guide. Available at: https://www.etf.europa.eu/sites/default/files/2019-06/Big%20data%20for%20LMI.pdf.
Horton, J.J., & Tambe, P. (2015). Labor economists get their microscope: big data and labor market analysis. Big Data, 3(3), 130–137, https://doi. org/10.1089/big.2015.0017.
ILO, 2020. The feasibility of using big data in anticipating and matching skills needs – International Labour Office – Geneva.
Mezzanzanica, M.; Mercorio, F. 2019. Big data for labour market intelligence: An introductory guide (Turin: European Training Foundation). Available at: https://www.etf.europa.eu/sites/default/files/2019-06/ Big%20data%20for%20LMI.pdf.
Puchiu, R., Stoian, M., Foca, M.(coord), 2018. România digitală: Concepte și instrumente operaționale, Editura Club România București, pg 1015.
Sanchez, J. I., & Levine, E. L. 2012. The rise and fall of job analysis and the future of wok analysis. Annual Review of Psychology, 63, 397–425. https://doi.org/10.1146/annurev-psych-120710-100401.
Schwab, Klaus, 2017, The Fourth Industrial Revolution. Penguin Books.
Vankevich, A., & Kalinouskaya, I. (2021). Better understanding of the labour market using Big Data. Ekonomia i Prawo. Economics and Law, 20(3), 677–692. https://doi.org/10.12775/EiP.2021.040.
Vasilescu, M., D., et al., 2020. Digital Divide, Skills and Perceptions on Digitalisation in the European Union—Towards a Smart Labour Market. PLOS ONE, edited by Javier Ordóñez-Monfort, vol. 15, no. 4, p. e0232032. DOI.org (Crossref), https://doi.org/10.1371/journal.pone.0232032.
