소상공인의 생애주기별 특성 연구 : 신용보증을 받은 차주를 중심으로

The purpose of this paper is to classify the life cycles of small business owners using machine learning techniques and to analyze the characteristics of classified life cycles. For this purpose, we used the questionnaire, “A survey on the financial status of small businesses and the effect of credit guarantee support,” which is conducted annually by the KOREG. The analysis results are as follows. Since the misclassification rate of the SVM model is the lowest among various machine learning techniques, it is reasonable to analyze the life cycle characteristics of small businesses using the life cycle classification results by SVM. As a result of the characterization analysis, business period, and low credit ratings increase with life cycle. In addition, the company’s ownership, sales, net profit, and number of employees increase as the company starts from maturity to maturity, but declines during the recession stage. In conclusion, the business status of small business owners has improved slightly from the start of business to the stage of maturity, but there is still insufficient funds for business stability and business expansion. On the other hand, when the recession enters, financial performance deteriorates due to reduced sales, which makes it difficult for businesses to manage their businesses.