Identifying Entrepreneurial Patterns Among Women: A Cluster Analysis Approach

Authors

Melinda Krankovits
Széchenyi István University, Faculty of Informatics and Electrical Engineering
https://orcid.org/0000-0002-6722-782X
Áron Szennay
Budapest University of Economics and Business, Faculty of Finance and Accounting
https://orcid.org/0000-0003-3567-9394
Judit Csákné Filep
University of Nyíregyháza, Institute of Business Administration
https://orcid.org/0000-0002-5902-5195
DOI: https://doi.org/10.18690/um.fov.3.2026.27

Synopsis

Introduction – Female entrepreneurship has become an increasingly prominent topic in business research. Although women exhibit lower entrepreneurial activity across most countries, the underlying drivers remain poorly understood. The study examines determinants of women’s entrepreneurial engagement. Methodology – Using Global Entrepreneurship Monitor (GEM) data from Hungary between 2021 and 2024 (n=4,080 women), an exploratory principal component analysis (PCA) was first conducted using 14 variables measuring entrepreneurial attitudes and perceptions, followed by Python-based K-means clustering. Results – Three distinct clusters emerged: (1) entrepreneurially engaged women with high perceived readiness and strong opportunity recognition; (2) proactive aspirants with high fear of failure despite positive attitudes; and (3) disengaged non-entrepreneurs with low proactivity and higher risk aversion. The clusters show clear separation in PCA space and significant differences across all attitudinal dimensions. Discussion – Results reveal heterogeneity in women’s entrepreneurial attitudes. Entrepreneurship-related perceptions may change over time due to external factors, suggesting that targeted interventions can foster female entrepreneurial activity.

Author Biographies

Melinda Krankovits, Széchenyi István University, Faculty of Informatics and Electrical Engineering

Melinda Krankovits (Ph.D.) is an Associate Professor at the Széchenyi István University Department of Informatics in Győr, Hungary. Her research and publication activities focus on social science, tertiary education, regional science, and economics.  Among the main research topics are the characteristics of higher education, e-learning models, and relations between universities and entrepreneurship, with a focus on regional analysis. She also contributes to papers on other fields (SMEs, entrepreneurs) as an expert in AI and machine learning. Her research and interests include machine learning, data processing, and data mining. She is a HE quality assurance expert. 

Győr, Hungary. E-mail: kmelinda@sze.hu

Áron Szennay, Budapest University of Economics and Business, Faculty of Finance and Accounting

Aron Szennay (Ph.D.) is an Associate Professor at the Budapest University of Economics and Business, Department of Finance, in Budapest, Hungary. His major research topic is entrepreneurship and SMEs, with a special focus on sustainability issues, digitalisation and female entrepreneurship.

Budapest, Hungary. E-mail: szennay.aron@uni-bge.hu

Judit Csákné Filep, University of Nyíregyháza, Institute of Business Administration

Judit Csákné Filep (Ph.D.) is a Professor at the University of Nyíregyháza. She holds a PhD in Management and Business Administration, with research interests focusing on family businesses and entrepreneurship. As the National Team Leader for Hungary in the Global Entrepreneurship Monitor (GEM), she contributes extensively to both national and international entrepreneurship research. Beyond her academic publications, she is dedicated to advancing the Hungarian family business sector and is a frequent conference speaker and a regular contributor to podcasts and professional media platforms.

Nyíregyháza, Hungary. E-mail: filep.judit@nye.hu

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Volume

45th International Conference on Organizational Science Development: Organization and the Longevity Society, Conference Proceedings

Pages

359-372

Published

March 17, 2026

Series

Razvoj organizacijskih znanosti

Categories

Copyright (c) 2026 University of Maribor, University of Maribor Press

License

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

How to Cite

Krankovits, M., Szennay, Áron, & Csákné Filep, J. (2026). Identifying Entrepreneurial Patterns Among Women: A Cluster Analysis Approach. In P. Šprajc, D. Maletič, N. Petrović, I. Iztok, A. Škraba, D. Tomić, & A. Žnidaršič Mohorič (Eds.), & (Ed.), 45th International Conference on Organizational Science Development: Organization and the Longevity Society, Conference Proceedings (Vols. 45., pp. 359-372). University of Maribor Press. https://doi.org/10.18690/um.fov.3.2026.27