Identifying Entrepreneurial Patterns Among Women: A Cluster Analysis Approach
Kratka vsebina
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.
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Kategorije
- Ekonomija
- Logistika
- Matematika
- Podjetništvo
- Poslovne vede
- Računalništvo in informatika
- Sociologija
- Strojništvo
- Turizem
- Upravne in organizacijaske vede
- Varnostne vede
- Varstvo okolja
- Vzgoja in izobraževanje
- Zdravstvene vede
- 2026
- Zbornik konference
- Odprti dostop
- Univerza v Mariboru, Fakulteta za organizacijske vede
- Slovenski jezik
- Angleški jezik
- Večjezično






