Multi-level entrepreneurial ecosystem framework: Founder, incubator, and country characteristics for start-up performance

Multi-level entrepreneurial ecosystem framework: Founder, incubator, and country characteristics for start-up performance

Article Date: 2025-01-01
Article URL: https://www.tandfonline.com/doi/full/10.1080/00472778.2025.2581669?af=R
Article Image: https://www.tandfonline.com/cms/asset/e19b9d6e-2170-4473-a0f1-838a24f66080/ujbm_a_2581669_f0001_oc.jpg

Summary

This global multi-level study investigates how founder-team characteristics (education, prior start-up experience, prior incubator experience), incubator features (financial support, structured education/training, specialisation) and country economic context (real GDP per capita) jointly predict two start-up outcomes: equity fundraising and revenue growth. The authors use GALI/Emory data covering 23,364 applications to 408 incubation/acceleration programmes across 176 countries (9,576 follow-ups; 2,451 incubated) and apply multi-level random-intercept models with a Heckman correction for selection bias.

Key findings: higher founder-team education and prior incubator experience significantly boost equity raised (but not revenue); prior start-up experience boosts both fundraising and revenue; incubator financial support and specialised sector-focused programmes raise equity, while structured education/training alone has no direct effect; country economic development (GDP per capita) amplifies the positive effect of founder education and start-up experience on equity but does not moderate revenue effects.

Key Points

• Dataset: 23,364 applications (2013–2019), 408 programmes, ~176 countries; 9,576 one-year follow-ups (2,451 incubated).
• Method: multi-level random-intercept models with Heckman selection correction and robustness OLS checks.
• Founder-team education and prior incubator experience increase equity fundraising; prior start-up experience increases both equity and revenue.
• Incubator financial support and specialised (sector-focused) programmes significantly raise equity; structured education/training shows no direct effect on fundraising or revenue.
• Country economic development (real GDP per capita) strengthens the effect of founder education and start-up experience on equity but does not moderate revenue gains.
• Implication: fundraising and revenue are driven by different antecedents — investor signals (education, incubator experience, specialised/financial support) vs commercial traction (prior start-up experience).

Context and relevance

This paper fills a gap by testing a micro–meso–macro model of entrepreneurial ecosystems on a global scale, moving beyond Western-only samples and purely conceptual debates. It gives actionable evidence for incubator managers, founders and policymakers about which programme design levers actually correlate with investor funding versus sales growth. The results matter for ecosystem design: targeted financial and sectoral support help with investor signalling, whereas practical founder experience matters more for commercial performance.

Why should I read this?

Short and blunt: if you run an incubator, back start-ups, or are picking one, this tells you what actually moves the needle. Want to raise equity fast? Back founders with education or prior incubator experience, offer financial support and sector-focused programmes. Want real revenue growth? pick founders with prior start-up experience. Boring generic training? Not enough on its own.

Author style

Punchy: a global, data-heavy paper that separates fundraising drivers from revenue drivers — very useful reading for programme designers and policymakers who need decisions, not anecdotes.

Source

Source: https://www.tandfonline.com/doi/full/10.1080/00472778.2025.2581669?af=R