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    한국 스타트업의 이질적 성장 유형과 영향 요인에 관한 실증분석 = An Empirical Analysis of Heterogeneous Growth Types of Korean Startups and Their Determinants

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    https://www.riss.kr/link?id=A110098654

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    This study classifies the growth trajectories of Korean startups and empirically analyzes the factors that influence their growth types. Using panel data from “Innoforest” and “Korea Rating and Data”, we estimate the growth speed and acceleration of sales and accumulated investment during years 2 to 6 after founding through a growth curve model. Based on these estimated dynamic indicators, we apply cluster analysis to categorize startup growth trajectories into four distinct types.
    The results show that the majority of startups fall into either the “General Growth Type” (77.4%), characterized by modest early growth that gradually accelerates, or the “Post-Growth Plateau Type” (13.8%), which experiences initial expansion followed by decelerating growth. A smaller group of startups exhibits rapid early growth, which is further classified into an “Accelerating High-Growth Type” (5.5%), where growth continues to accelerate over time and a “Decelerating High-Growth Type” (3.3%), where early rapid growth slows in later years.
    A multi-nomial logit analysis of the determinants of these growth types reveals that industry sector, geographic location, early-stage investment, early R&D activities, and initial financial soundness are all significantly associated with the likelihood of belonging to each growth category.
    These findings highlight the heterogeneous nature of startup growth trajectories and suggest that early conditions and strategic decisions play a critical role in shaping the sustainability and direction of startup growth.
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    This study classifies the growth trajectories of Korean startups and empirically analyzes the factors that influence their growth types. Using panel data from “Innoforest” and “Korea Rating and Data”, we estimate the growth speed and accelerat...

    This study classifies the growth trajectories of Korean startups and empirically analyzes the factors that influence their growth types. Using panel data from “Innoforest” and “Korea Rating and Data”, we estimate the growth speed and acceleration of sales and accumulated investment during years 2 to 6 after founding through a growth curve model. Based on these estimated dynamic indicators, we apply cluster analysis to categorize startup growth trajectories into four distinct types.
    The results show that the majority of startups fall into either the “General Growth Type” (77.4%), characterized by modest early growth that gradually accelerates, or the “Post-Growth Plateau Type” (13.8%), which experiences initial expansion followed by decelerating growth. A smaller group of startups exhibits rapid early growth, which is further classified into an “Accelerating High-Growth Type” (5.5%), where growth continues to accelerate over time and a “Decelerating High-Growth Type” (3.3%), where early rapid growth slows in later years.
    A multi-nomial logit analysis of the determinants of these growth types reveals that industry sector, geographic location, early-stage investment, early R&D activities, and initial financial soundness are all significantly associated with the likelihood of belonging to each growth category.
    These findings highlight the heterogeneous nature of startup growth trajectories and suggest that early conditions and strategic decisions play a critical role in shaping the sustainability and direction of startup growth.

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