Integrating Financial, Institutional, and Social Capital into A Cross-Ecosystem Logistic Regression Analysis Using Large-Scale Firm-Level Data

Purpose: This study investigates the key determinants of startup survival across diverse entrepreneurial ecosystems, integrating financial, institutional, and social capital. It aims to clarify how ecosystem-level supports, such as access to finance, mentorship, policy backing, and networking, alongside firm-specific characteristics, influence startup longevity in emerging economies. Design/Methodology/Approach: The paper uses a dataset (2015–2023) covering 5,000 startups across Southeast Asia, SSA, and Latin America from a multilevel logistic regression models with random effects at the ecosystem level were employed to account for nesting of firms within ecosystems. Firm-level controls included age, size, and sector. Findings: Results indicate that access to finance, mentorship, policy support, and networking all positively and significantly enhance survival odds, while GDP per capita shows no direct effect. Firm age and size also contribute positively. The findings highlight the layered, interdependent roles of ecosystem resources in mitigating startup fragility. Implications/Originality/Value: The study underscores that survival depends less on macroeconomic wealth than on targeted ecosystem supports. Policymakers should prioritize integrated strategies that combine financial tools, mentorship programs, regulatory facilitation, and networking opportunities to foster resilient startup communities.