DIGITAL METHODS AND TECHNOLOGIES OF FORMING AN INNOVATIVE LABOUR MARKET INFORMATION SUPPORT SYSTEM IN UKRAINE
DOI:
https://doi.org/10.35774/jee2023.03.471Keywords:
Big Data, employment, digitalization, labour market analytics, labour market information system, the labour sphere.Abstract
Digitalization processes bring about radical transformations in the content and nature of work, leading to shifts in the demand for certain skills and abilities and the emergence of new occupations. Traditional survey-based sources of information about the labour market prove insufficient to track these changes for employment policy purposes. In this article, the authors reveal alternative data sources on the labour market, made possible due to the development of new digital technologies, and delineate their respective advantages and drawbacks. Additionally, the authors systematize international experiences in leveraging digital technologies and Big Data for statistical and information-analytical research on the labour market. Having analysed the leading research-analytical projects in the USA, Great Britain, and EU countries, the authors found them to be focused on constructing functional intellectual and analytical systems for the labour market. These projects aim to develop methodologies and promote widespread adoption of digital tools for working with Big Data, significantly expanding the capabilities of labour market information and analytical systems. The authors examined specific projects that used Big Data from online job vacancies to assess the demand and supply of jobs, as well as to analyse and forecast the requirements for skills and competences that would be feasible for adoption in Ukraine. Big Data from specialized online portals, servers and services were found to serve as powerful resources to supplement and enrich the existing conventional system of labour market statistics and analytics. Finally, the authors substantiate the need and expediency of creating a fundamentally new Labour Market Information and Analytical System (LMIAS) in Ukraine and coordinating it with labour market platforms in EU countries. They also identify a range of problematic issues that require in-depth research and resolution in Ukraine, such as ensuring the representativeness of online job vacancy data, improving the classifiers of occupations, abilities and skills, and introducing methods for integrating statistical, administrative, and Big Data on the labour market.
JEL: J21, J44, С80, О15, О38.
References
Arthur D. Little & Huawei. (2020). Think differently. Think archetype. Your digital economy model: A novel approach to digital transformation and policy reform. https://www.huawei.com/-/media/corp2020/pdf/public-policy/adl_huawei_digital_transformation_main_report.pdf?la=en.
Antonyuk, L. L., Ilnytskyi, D. O., & Sevastiuk, A. O. (Eds.) (2021). Digital economy: The impact of information and communication technologies on human capital and formation of competences of the future [in Ukrainian]. KNEU. https://ir.kneu.edu.ua/handle/2010/36436?show=full&locale-attribute=en.
Azmuk, N. A. (2019). Transforming employment in the transition to the digital economy: Global challenges and adaptation strategies [in Ukrainian]. Znannia.
CEDEFOP. (2014). Real-time labour market information on skill requirements: Feasibility study and working prototype [Call for Tenders]. (Ref. No. AO/RPA/VKVET-NSOFRO/Real-time LMI/010/14). https://goo.gl/qNjmrn.
CEDEFOP. (2023). Skills-OVATE [Online Skills Intelligence Tool]. https://www.cedefop.europa.eu/ en/data-visualisations/skills-online-vacancies.
Colombo, E., Mercorio, F., & Mezzanzanica, M. (2018, February 22). Applying machine learning tools on web vacancies for labour market and skill analysis [Paper Presentation]. Technology Policy Institute Conference on the Economics and Policy Implications of Artificial Intelligence, Washington DC, USA. https://techpolicyinstitute.org/wp-content/uploads/2018/02/Colombo_paper.pdf.
Colombo, E., Mercorio, F., & Mezzanzanica, M. (2019). AI meets labour market: Exploring the link between automation and skills. Information Economics and Policy, 47(June), 27-37. https://doi.org/10.1016/j.infoecopol.2019.05.003
CompTIA. (2018, June 6). US cybersecurity worker shortage expanding, new CyberSeek™ data reveals [Press Release]. https://www.comptia.org/ newsroom/press-releases/2018/06/06/us-cybersecurity-worker-shortage-expandingnew-cyberseek-data-reveals.
Cymbal, O. I., Libanova, E. M., Makarova, O. V., Sarioglo, V. H., Ostafiychuk, Ya. V., Tkachenko, L. H., Bogush, L. H., Svets, P. A., Yarosh, O. M., Krymova, M. O., Chernichenko, V. V., Otkydach, M. V., & Shmorhun, O. Ya. (2021). Human development in Ukraine. Priorities of the national policy of minimizing the asymmetry of the Ukrainian labour market [in Ukrainian]. PH «Akademperiodyka». https://idss.org.ua/arhiv/Block_Libanova_Ludskij_rozvytok_web.pdf
European Training Foundation. (2017). Labour market information systems: Collecting information and data on labour market trends. https://www.etf.europa.eu/sites/default/files/m/466C7A2340B3DAE0C12580E60049FC1D_LMIS.pdf.
European Training Foundation. (2022). Big data for labour market intelligence. https://www.etf.europa.eu/en/news-and-events/events/big-data-labour-marketintelligence-online-capacity-development-programme.
European Commission. (2016). A new skills agenda for Europe (COM(2016) 381 final). https://eur-lex.europa.eu/legal-content/EN/TXT/?uri=CELEX%3A52016DC0381.
European Commission. (2018). Threats and opportunities from automation and robotisation. https://knowledge4policy.ec.europa.eu/foresight/topic/ changing-nature-work/new-technologies-automation-work-developments_en.
European Commission. (2023). ESSnet Big Data. https://goo.gl/EF6GtU. Frey, C., & Osborne, А. (2017). The future of employment: How susceptible are jobs to computerisation? Technological Forecasting and Social Change,114, 254‒280. https://doi.org/10.1016/j.techfore.2016.08.019
Kolot, A. M., & Herasymenko, O. O. (2020). The sphere of labour in the conditions of the global socio-economic reality 2020: Challenges for Ukraine [in Ukrainian]. Representation of the Friedrich Ebert Foundation in Ukraine.https://library.fes.de/pdf-files/bueros/ukraine/16344.pdf.
Kolot, A. M., & Herasymenko, O. O. (2021). Work XXI: Philosophy of change, challenges, vectors of development [in Ukrainian]. National Economic University named after Vadym Hetman. https://ir.kneu.edu.ua/items/ee8cf399-8bcb-46ee-84cb-ac6759b412df.
Kolot, A. M., & Herasymenko, O. O. (2022). Novel formats of labour activity organization: nature, challenges, and development trajectories [in Ukrainian]. Ekonomika Ukrainy, 5, 59-76. https://doi.org/10.15407/economyukr.2022.05.059
Kyslova, O. M. (2019). Big data in the context of studying problems of modern society [in Ukrainian]. Visnyk of V. N. Karazin Kharkiv National University. Series «Sociological Studies of Contemporary Society: Methodology, Theory, Methods», 42, 59-68. https://doi.org/10.26565/2227-6521-2019-42-06
Lightcast. (2023). Lightcast European Insights [Interactive Tool]. https://europeinsights.lightcast.io/.
Manyika, J., Lund, S., Chui, M., Bughin, J., Woetzel, J., Batra, P., Ko, R., & Sanghvi, S. (2017, November 28). Jobs lost, jobs gained: What the future of work will mean for jobs, skills, and wages. McKinsey Global Institute. https://www.mckinsey.com/featured-insights/future-of-work/jobs-lost-jobsgained-what-the-future-of-work-will-mean-for-jobs-skills-and-wages.
Mezzanzanica, M., & Mercorio, F. (2018). Big Data enables labour market intelligence. In S. Sakr & A. Zomaya (Eds.), Encyclopedia of Big Data Technologies (pp. 1-11). Springer, Cham. https://doi.org/10.1007/978-3-319-63962-8_276-1
Mezzanzanica, M., & Mercorio, F. (2019). Big Data in the context of the labour market intelligence: An introductory guide [in Russian]. European Training Foundation. https://www.etf.europa.eu/sites/default/files/2019-12/big_data_for_lmi_ru.pdf.
Mykhailova, O. (2023, May 23). How artificial intelligence will affect the labour market in Ukraine and what the risks are [in Ukrainian]. Fakty. https://fakty.com.ua/ua/ukraine/suspilstvo/20230523-yak-shtuchnyj-intelektvplyne-na-rynok-praczi-v-ukrayini-ta-v-chomu-ryzyky/.
Novikova, O. F., Zaloznova, O. I., Amosha, O. I., Khandii, O. O., Azmuk, N. A., Ostafiychuk, Ya. V., Shamileva, L. L., Pankova, O. V., Novak, I. M., Shastun, A. D., Kasperovych, O. Yu., Ishchenko, O. V., Krasulina, Ya. Ye., Amelicheva, L. P., & Kompaniyets, V. V. (2022). Transformation of sociallabour sphere under the conditions of digitalization of the economy [in Ukrainian]. Institute of Industrial Economics of the National Academy of Sciences of Ukraine. https://iie.org.ua/wp-content/up-loads/application/pdf/da_mono_2022-pdf-na-sajt_compressed.pdf.
Olsson, P., Galaz, V., & Boonstra, W. J. (2014). Sustainability transformations: a resilience perspective. Ecology and Society, 19(4), 1-13. http://dx.doi.org/10.5751/ES-06799-190401
Sarioglo, V. (2016). «Big data» as an information source and a toolkit for official statistics: Capacities, problems, prospects [in Ukrainian]. Statystyka Ukrainy, 4, 12-19. http://194.44.12.92:8080/jspui/bitstream/123456789/2244/1/5.pdf.
Sarioglo, V., & Cymbal, O. (2020). Labour market landscaping Ukraine. European Training Foundation. https://www.etf.europa.eu/sites/default/files/2020-11/ukraine_web_labour_market_landscaping_final_web.pdf.
Stronkowski, P. (2018). Collecting and using labour market information for strengthening the regional system of vocational and technical education: A practical guide [in Ukrainian]. U-LEAD.
Technologies for processing Big Data. (n.d.). https://e-tk.lntu.edu.ua/ pluginfile.php/20333/mod_resource/content/0/%D0%A2%D0%B5%D0%BC%D0%B0%2016.%20%D0%A2%D0%B5%D1%85%D0%BD%D0%BE%D0%BB%D0%BE%D0%B3%D1%96%D1%96%CC%88%20%D0%BE%D0%B1%D1%80%D0%BE%D0%B1%D0%BA%D0%B8%20%D0%B2%D0%B5%D0%BB%D0%B8%D0%BA%D0%B8%D1
UK Commission for Employment and Skills. (2015, December 10). The importance of labour market intelligence. https://www.gov.uk/government/ publications/the-importance-of-labour-market-intelligence.
Vaccarino, А. (2020). Big data for labour market information (LMI) in Ukraine. Methodological overview and analytics insights on Ukrainian web labour market. European Training Foundation. https://www.etf.europa.eu/sites/ default/files/2021-05/ukraine_big_data_lmi_analysis_2020_web.pdf.
Vishnevsky, V. P., Dasiv, A. F., Okhten, O. O., & Turlakova, S. S. (2022). The industrial future of Ukraine: Prediction by mathematical modeling methods [in Ukrainian]. Institute of Industrial Economics of the National Academy of Sciences of Ukraine. https://iie.org.ua/wp-content/uploads/application/pdf/mono_2022-1_compressed.pdf.
Received: June 12, 2023.
Reviewed: July 7, 2023.
Accepted: August 12, 2023.
Downloads
Published
How to Cite
Issue
Section
License
Authors who publish with this journal agree to the following terms:
- Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution License that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.
- Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal.
- Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (See The Effect of Open Access).
