IDEAS home Printed from https://ideas.repec.org/a/eee/finana/v105y2025ics1057521925005265.html
   My bibliography  Save this article

Investigating the investment readiness of European SMEs: A machine learning approach

Author

Listed:
  • Alexakis, Christos
  • Gogas, Periklis
  • Petrella, Giovanni
  • Polemis, Michael
  • Salvadè, Federica

Abstract

This study exploits machine learning techniques to investigate the investment readiness of European small and medium-sized enterprises (SMEs). Understanding the drivers behind SMEs' willingness to use equity capital and foster innovation is crucial for promoting economic growth. Our analysis is grounded on the Survey on the Access to Finance of Enterprises (SAFE) released by the European Commission and the European Central Bank, which covers a vast sample of European SMEs. The empirical findings reveal that factors associated with the entrepreneurial ecosystem—such as regulatory frameworks, the availability of skilled staff, and perceived market outlook within a country—are critical drivers of investment readiness. Importantly, we find that access to debt financing and firm risk do not significantly influence SMEs' willingness to raise equity capital. Lastly, this research offers valuable insights for policymakers and equity providers, suggesting that tailored investment readiness programs that consider cultural and country-specific characteristics can unlock the full potential dynamics of European SMEs.

Suggested Citation

  • Alexakis, Christos & Gogas, Periklis & Petrella, Giovanni & Polemis, Michael & Salvadè, Federica, 2025. "Investigating the investment readiness of European SMEs: A machine learning approach," International Review of Financial Analysis, Elsevier, vol. 105(C).
  • Handle: RePEc:eee:finana:v:105:y:2025:i:c:s1057521925005265
    DOI: 10.1016/j.irfa.2025.104439
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S1057521925005265
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.irfa.2025.104439?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

    for a different version of it.

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;

    JEL classification:

    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation
    • G19 - Financial Economics - - General Financial Markets - - - Other
    • G30 - Financial Economics - - Corporate Finance and Governance - - - General

    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:eee:finana:v:105:y:2025:i:c:s1057521925005265. 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.

    We have no bibliographic references for this item. You can help adding them by using 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/inca/620166 .

    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.