IDEAS home Printed from https://ideas.repec.org/a/prg/jnlcbr/v2024y2024i5id365p1-22.html
   My bibliography  Save this article

Towards Algorithm-Assisted Career Management - a Challenge for New Immigration Countries. Predicting Migrants' Work Trajectory Using Ensemble Learning

Author

Listed:
  • Jolanta Maj
  • Bogdan Ruszczak
  • Sabina Kubiciel-Lodzińska

Abstract

Migration processes have emerged as crucial social, political and economic concerns, affecting societies, industries and organisations. The challenge lies in effectively utilizing immigrants' resources. This research aims to determine how AI tools can support matching migrants' skills with labour markets in host countries. We propose the application of an ensemble learning methodology. To validate this approach, we collect data to assess the career trajectories of 248 tertiary-educated Ukrainian immigrants in Poland, a new immigration destination. Various machine learning models are evaluated using the decision tree algorithm on these feature sets. To ensure credible results, a 10-fold cross-validation procedure is employed for each training process of every submodel. This research introduces an original ensemble machine learning classifier that combines pre-selected models with the highest performance, thereby reducing the number of parameters to be investigated. Its application in determining the career paths of highly skilled migrants, specifically Ukrainians, is novel. The study offers significant implications for Central Europe, notably Poland, where migration patterns and the integration of highly skilled migrants, mainly from Ukraine, are increasingly important. Implications for Central European audience: The ensemble machine learning classifier developed in this study could aid in optimising the career paths of these migrants, combating brain waste and facilitating their successful integration into the labour market. Integrating tools like these into decision-making processes may enhance career management and contribute to Central Europe's social and economic growth.

Suggested Citation

  • Jolanta Maj & Bogdan Ruszczak & Sabina Kubiciel-Lodzińska, 2024. "Towards Algorithm-Assisted Career Management - a Challenge for New Immigration Countries. Predicting Migrants' Work Trajectory Using Ensemble Learning," Central European Business Review, Prague University of Economics and Business, vol. 2024(5), pages 1-22.
  • Handle: RePEc:prg:jnlcbr:v:2024:y:2024:i:5:id:365:p:1-22
    DOI: 10.18267/j.cebr.365
    as

    Download full text from publisher

    File URL: http://cebr.vse.cz/doi/10.18267/j.cebr.365.html
    Download Restriction: free of charge

    File URL: http://cebr.vse.cz/doi/10.18267/j.cebr.365.pdf
    Download Restriction: free of charge

    File URL: https://libkey.io/10.18267/j.cebr.365?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Duan, Yanqing & Edwards, John S. & Dwivedi, Yogesh K, 2019. "Artificial intelligence for decision making in the era of Big Data – evolution, challenges and research agenda," International Journal of Information Management, Elsevier, vol. 48(C), pages 63-71.
    2. Liu, Xiaohui & Gao, Lan & Lu, Jiangyong & Wei, Yingqi, 2015. "The role of highly skilled migrants in the process of inter-firm knowledge transfer across borders," Journal of World Business, Elsevier, vol. 50(1), pages 56-68.
    3. Joerg Dietz & Chetan Joshi & Victoria M. Esses & Leah K. Hamilton & Fabrice Gabarrot, 2015. "The skill paradox: explaining and reducing employment discrimination against skilled immigrants," Post-Print hal-01667154, HAL.
    4. Binggeli, Steve & Dietz, Joerg & Krings, Franciska, 2013. "Immigrants: A Forgotten Minority," Industrial and Organizational Psychology, Cambridge University Press, vol. 6(1), pages 107-113, March.
    5. Maciej Duszczyk & Agata Górny & Paweł Kaczmarczyk & Andrzej Kubisiak, 2023. "War refugees from Ukraine in Poland – one year after the Russian aggression. Socioeconomic consequences and challenges," Regional Science Policy & Practice, Wiley Blackwell, vol. 15(1), pages 181-199, February.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Shipilov, Andrew V. & Li, Stan Xiao & Li, Wan, 2020. "Can you do Kung Fu and also act? New entrants’ status attainment in the creative industries," Journal of World Business, Elsevier, vol. 55(3).
    2. Irina Y. Yu & Morgan X. Yang & Haksin Chan & Bradley R. Barnes, 2022. "Promoting sustainable human resource management by reducing recruitment discrimination: A cross‐cultural perspective," Sustainable Development, John Wiley & Sons, Ltd., vol. 30(4), pages 503-512, August.
    3. Fitzsimmons, Stacey R. & Baggs, Jen & Brannen, Mary Yoko, 2020. "Intersectional arithmetic: How gender, race and mother tongue combine to impact immigrants’ work outcomes," Journal of World Business, Elsevier, vol. 55(1).
    4. Thomas Köllen & Andri Koch & Andreas Hack, 2020. "Nationalism at Work: Introducing the “Nationality-Based Organizational Climate Inventory” and Assessing Its Impact on the Turnover Intention of Foreign Employees," Management International Review, Springer, vol. 60(1), pages 97-122, February.
    5. Cano-Marin, Enrique & Mora-Cantallops, Marçal & Sánchez-Alonso, Salvador, 2023. "Twitter as a predictive system: A systematic literature review," Journal of Business Research, Elsevier, vol. 157(C).
    6. Wei, Hao & Yuan, Ran & Zhao, Laixun, 2020. "International talent inflow and R&D investment: Firm-level evidence from China," Economic Modelling, Elsevier, vol. 89(C), pages 32-42.
    7. Latinovic, Zoran & Chatterjee, Sharmila C., 2022. "Achieving the promise of AI and ML in delivering economic and relational customer value in B2B," Journal of Business Research, Elsevier, vol. 144(C), pages 966-974.
    8. Taiga Saito & Shivam Gupta, 2022. "Big data applications with theoretical models and social media in financial management," CARF F-Series CARF-F-550, Center for Advanced Research in Finance, Faculty of Economics, The University of Tokyo.
    9. Rizgar R. Zebari & Gheyath M. Zebari & Adel Al-zebari & Marwan Aziz Mohammed, 2025. "LSTM-XGBoost: An Ensemble Model for Blood Demand Distribution Forecasting – A Case Study in Zakho City, Kurdistan Region, Iraq," SN Operations Research Forum, Springer, vol. 6(1), pages 1-22, March.
    10. Kelly Z. Peng & Fang Lee Cooke & Xuhua Wei, 2023. "Managing minority employees in organizations in Asia Pacific: Towards a more inclusive workplace?," Asia Pacific Journal of Management, Springer, vol. 40(3), pages 877-902, September.
    11. Ranabahu, Nadeera & de Vries, Huibert P. & Basharati, Zhiyan, 2025. "Refugees’ employment: Adapting a structural inequality framework for multinational corporations," International Business Review, Elsevier, vol. 34(1).
    12. Ozkan-Canbolat, Ela & Beraha, Aydin, 2016. "Evolutionary knowledge games in social networks," Journal of Business Research, Elsevier, vol. 69(5), pages 1807-1811.
    13. Liu, Xiaohui & Xia, Tianjiao & Jiangyong, Lu & Lin, Daomi, 2019. "Under what institutional conditions does overseas business knowledge contribute to firm performance?," International Business Review, Elsevier, vol. 28(3), pages 588-602.
    14. Latukha, M. & Nintuona Soyiri, J., 2018. "Determinants of Talent Mobility in Africa: Talent Attraction and Retention Practices in Ghana," Working Papers 15113, Graduate School of Management, St. Petersburg State University.
    15. Lin, Daomi & Zheng, Wei & Lu, Jiangyong & Liu, Xiaohui & Wright, Mike, 2019. "Forgotten or not? Home country embeddedness and returnee entrepreneurship," Journal of World Business, Elsevier, vol. 54(1), pages 1-13.
    16. Tetiana Zatonatska & Olena Liashenko & Yana Fareniuk & Łukasz Skowron & Tomasz Wołowiec & Oleksandr Dluhopolskyi, 2023. "The Impact of Migration on Forecasting Budget Expenditures on Education: The Sustainability Context," Sustainability, MDPI, vol. 15(21), pages 1-21, October.
    17. Dydrov, Artur (Дыдров, Артур), 2023. "Artificial Intelligence: Mythologies Of Western Scientific Content [Искусственный Интеллект: Мифологемы Западного Научного Контента]," Sotsium i vlast / Society and power, Russian Presidential Academy of National Economy and Public Administration, pages 16-25.
    18. Yuan, Chunlin & Zhang, Chenlei & Wang, Shuman, 2022. "Social anxiety as a moderator in consumer willingness to accept AI assistants based on utilitarian and hedonic values," Journal of Retailing and Consumer Services, Elsevier, vol. 65(C).
    19. Fawwaz Tawfiq Awamleh & Ala Nihad Bustami, 2022. "Examine the Mediating Role of the Information Technology Capabilities on the Relationship Between Artificial Intelligence and Competitive Advantage During the COVID-19 Pandemic," SAGE Open, , vol. 12(3), pages 21582440221, August.
    20. Tobias Bender, 2024. "Towards a process selection method for embedded analytics," Information Systems and e-Business Management, Springer, vol. 22(3), pages 501-525, September.

    More about this item

    Keywords

    career management; migration; immigrants; machine learning; ensemble learning; decision trees; labour market;
    All these keywords.

    JEL classification:

    • F22 - International Economics - - International Factor Movements and International Business - - - International Migration
    • J61 - Labor and Demographic Economics - - Mobility, Unemployment, Vacancies, and Immigrant Workers - - - Geographic Labor Mobility; Immigrant Workers
    • O15 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development - - - Economic Development: Human Resources; Human Development; Income Distribution; Migration

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:prg:jnlcbr:v:2024:y:2024:i:5:id:365:p:1-22. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Stanislav Vojir (email available below). General contact details of provider: https://edirc.repec.org/data/uevsecz.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.