Analysis of High-Growth Factors and Support Strategy Development for SMEs in Gyeongnam Using Decision Tree Analysis

Abstract

This study analyzed the factors that influence the high growth beneficiary companies in the Gyeongnam Technopark support project. To this end, experimental data were analyzed by constructing a prediction model consisting of highly important variables in beneficiary company decisions, identified among a variety of company information, using the decision tree model. The primary role of the decision tree model is to simplify the understanding of complex data. It hierarchically analyzes the impact of various variables on the outcomes, making it easy to identify key decision factors. In addition, it enhances prediction accuracy by eliminating less important variables and prioritizing significant ones during the classification process, thereby deriving effective decision-making rules. This study, identified ‘years in business’ and ‘revenue’ as key variables from the sales perspective compared to ‘total liabilities’ and ‘years in business’ from the employment perspective. In addition, various rules were derived to determine the beneficiary companies of the Gyeongnam Technopark’s support project using the analysis results expressed as decision trees. Three policy measures were presented based on the important rules that repeatedly appear in different predictive models to increase the effect of Gyeongnam Technopark’s industrial development. First, customized support programs should be expanded to assist companies in areas such as technology, management, market entry, and talent acquisition. Second, financial support and consulting should be strengthened to reduce debt burdens and improve financial soundness. Third, focused support should be provided to early-stage and newly established companies, especially young firms, to maximize their growth potential. Using the analysis methods presented in this study and the determinants of the beneficiary companies of the Gyeongnam Technopark support project will help create a sustainable future growth environment for both high growth and employment growth in the region.