IDEAS home Printed from https://ideas.repec.org/a/plo/pone00/0329405.html

Quantifying the influence of vocational education and training with text embedding and similarity-based networks

Author

Listed:
  • Hyeongjae Lee
  • Inho Hong

Abstract

Assessing the potential influence of Vocational Education and Training (VET) courses on creating job opportunities and nurturing work skills has been considered challenging due to the ambiguity in defining their complex relationships and connections with the local economy. Here, we quantify the potential influence of VET courses and explain it with future economy and specialization by constructing a network of more than 17,000 courses, jobs, and skills in Singapore’s SkillsFuture data based on their text similarities captured by a text embedding technique, Sentence Transformer. We find that VET courses associated with Singapore’s 4th Industrial Revolution economy demonstrate higher influence than those related to other future economies. The course influence varies greatly across different sectors, attributed to the level of specificity of the skills covered. Lastly, we show a notable concentration of VET supply in certain occupation sectors requiring general skills, underscoring a disproportionate distribution of education supply for the labor market.

Suggested Citation

  • Hyeongjae Lee & Inho Hong, 2025. "Quantifying the influence of vocational education and training with text embedding and similarity-based networks," PLOS ONE, Public Library of Science, vol. 20(8), pages 1-19, August.
    • Handle: RePEc:plo:pone00:0329405
    DOI: 10.1371/journal.pone.0329405
    as

    Download full text from publisher

    File URL: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0329405
    Download Restriction: no
    File URL: https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0329405&type=printable
    Download Restriction: no
    File URL: https://libkey.io/10.1371/journal.pone.0329405?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
    ---><---

    References listed on IDEAS

    as
    1. Kai Li & Feng Mai & Rui Shen & Xinyan Yan, 2021. "Measuring Corporate Culture Using Machine Learning," NBER Chapters, in: Big Data: Long-Term Implications for Financial Markets and Firms, pages 3265-3315, National Bureau of Economic Research, Inc.
    2. Kai Li & Feng Mai & Rui Shen & Xinyan Yan, 2021. "Measuring Corporate Culture Using Machine Learning [Machine learning methods that economists should know about]," The Review of Financial Studies, Society for Financial Studies, vol. 34(7), pages 3265-3315.
    3. Barbara Biasi & Song Ma, 2022. "The Education-Innovation Gap," CESifo Working Paper Series 9653, CESifo.
    4. Barbara Biasi & Song Ma, 2022. "Frontier Knowledge in Higher Education," NBER Working Papers 29853, National Bureau of Economic Research, Inc.
    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. Chen, Wenpeng & Wang, Jiaqi & Wang, Shan, 2025. "Economic uncertainty, digital transformation, and firm supply chain disruption risk," Economics Letters, Elsevier, vol. 255(C).
    2. Wang, Sumingyue & Wang, Xinlu & Xu, Liang, 2023. "Debt maturity structure and the quality of risk disclosures," Journal of Corporate Finance, Elsevier, vol. 83(C).
    3. Tran, Thanh & Nguyen, Harvey & Pham, Mia Hang, 2025. "Do financial markets value corporate culture?," International Review of Financial Analysis, Elsevier, vol. 98(C).
    4. Lutfa Tilat Ferdous & Tarek Rana & Richard Yeboah, 2025. "Decoding the impact of firm‐level ESG performance on financial disclosure quality," Business Strategy and the Environment, Wiley Blackwell, vol. 34(1), pages 162-186, January.
    5. Coraggio, Luca & Pagano, Marco & Scognamiglio, Annalisa & Tåg, Joacim, 2025. "JAQ of all trades: Job mismatch, firm productivity and managerial quality," Journal of Financial Economics, Elsevier, vol. 164(C).
    6. Semeyutin, Artur & Kaawach, Said & Kara, Alper, 2023. "CEO risk-culture, bank stability and the case of the Silicon Valley Bank," Economics Letters, Elsevier, vol. 233(C).
    7. Shiblu, Kawser Ahmed & Toscano, Francesca, 2026. "Culture as a catalyst: The impact of corporate culture on strategic alliances and equity market response," Journal of Financial Stability, Elsevier, vol. 82(C).
    8. Li, Jian & Yi, Mei & Sun, Qing, 2025. "Artificial intelligence and supply chain risk: Mediating effects of supply chain efficiency and resilience," International Review of Financial Analysis, Elsevier, vol. 108(PA).
    9. Jinjuan Yang & Jiayuan Xin & Yan Zeng & Pei Jose Liu, 2025. "Signaling and perceiving on equity crowdfunding decisions — a machine learning approach," Small Business Economics, Springer, vol. 65(1), pages 315-356, June.
    10. Luisa Faust & Maura Kolbe & Sasan Mansouri & Paul P. Momtaz, 2022. "The Crowdfunding of Altruism," JRFM, MDPI, vol. 15(3), pages 1-29, March.
    11. Preuss, Susanne & Max, Malte M., 2024. "Do firms put their money where their mouth is? Sociopolitical claims and corporate political activity," Accounting, Organizations and Society, Elsevier, vol. 113(C).
    12. Shi, Lu, 2025. "Better innovation subsequent to political content disclosure: Evidence from China," Economic Analysis and Policy, Elsevier, vol. 88(C), pages 1165-1184.
    13. Cao, June & Huang, Zijie & Shahid, Ahmad Usman, 2025. "Fostering environmental integrity via investor-focused communications: Private in-house meeting disclosures and greenwashing behaviors," Journal of Economic Behavior & Organization, Elsevier, vol. 232(C).
    14. Yu, Shule & Zhang, Jun & Yan, Xueling, 2024. "Robots, gender economic opportunities and household adjustment: Evidence from China," Structural Change and Economic Dynamics, Elsevier, vol. 71(C), pages 57-67.
    15. Maria Saveria Mavillonio, 2024. "Natural Language Processing Techniques for Long Financial Document," Discussion Papers 2024/317, Dipartimento di Economia e Management (DEM), University of Pisa, Pisa, Italy.
    16. He, Yu & Liu, Zhenya & Lu, Shanglin & Wei, Ran, 2024. "Measuring firm-level manager risk perception," Finance Research Letters, Elsevier, vol. 69(PB).
    17. Fay, Scott & Feng, Cong & Patel, Pankaj C., 2022. "Staying small, staying strong? Retail store underexpansion and retailer profitability," Journal of Business Research, Elsevier, vol. 144(C), pages 663-678.
    18. Cumming, Douglas & Köchling, Gerrit & Neukirchen, Daniel & Posch, Peter, 2022. "Does Corporate Culture Influence IPO Pricing?," VfS Annual Conference 2022 (Basel): Big Data in Economics 264105, Verein für Socialpolitik / German Economic Association.
    19. John (Jianqiu) Bai & Wang Jin & Matthew Serfling, 2022. "Management Practices and Mergers and Acquisitions," Management Science, INFORMS, vol. 68(3), pages 2141-2165, March.
    20. Datta, Sudip & Doan, Trang & Toscano, Francesca, 2023. "Top executive gender, corporate culture, and the value of corporate cash holdings," Journal of Financial Stability, Elsevier, vol. 67(C).

    More about this item

    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:plo:pone00:0329405. 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: plosone (email available below). General contact details of provider: https://journals.plos.org/plosone/ .

    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.