재창업 중소기업의 무엇이 성공과 실패, 그리고 생존을 좌우하는가?

초록

This study analyzes administrative data from 6,615 re-startup SMEs that received Re-startup Fund from the Korea SMEs and Startups Agency (KOSME) between 2010 and 2022. The research examines the probabilities of success, failure, and survival five years after the year of funding, and identifies the key influencing factors. A predictive model was developed using a decision tree machine learning algorithm to extract core rules associated with the success and failure of re-startup SMEs. Additionally, the Kaplan-Meier survival function and Cox proportional hazards model were employed to analyze changes in survival rates over time and the factors affecting these changes. The results identified financial stability indicators such as cash assets, business experience, technological capabilities, industry type, region, and the representative’s age as statistically significant variables. Based on these findings, the study highlights the importance of early intervention and post-support management for re-startup companies, and emphasizes the need for segmented policy designs that consider diverse firm characteristics.

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