초기 스타트업의 후속 투자 라운드 전환 결정요인 분석: Seed에서 Series A로의 전환을 중심으로

초록

This study empirically investigates the determinants enabling seed-stage startups to secure Series A funding within 24 months. Using a Korean startup database providing investment histories to firm-level characteristics, logistic regression models are estimated under a baseline specification and an extended specification that additionally incorporates financial indicators and employment dynamics measured over the preceding 12 months. The results indicate that headquarters location and industry category measures are consistently and positively associated with the Series A transition across specifications. When financial and employment variables are included, organizational and performance signals provide incremental explanatory power and weaken several patent-based effects. Estimates from the extended model should be interpreted with caution due to limited coverage of financial and employment data. Overall, the findings underscore the roles of external context and dynamic firm signals in early-stage funding transitions.

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