혁신 사업화 여정 기반의 중소기업 규제 대응 전략 연구

As the convergence of technology and industry accelerates, conflicts between regulations and technological innovation are increasing. The government is approaching regulatory issues from various angles to respond to the rapidly changing industrial environment, but revising laws and systems to keep pace with technological development has limits. Accordingly, companies are preparing their own strategies to respond to various regulations. However, few studies still confirm the relationship between corporate response strategies against regulation and regulatory factors appearing in the process of corporate innovation. This study examines regulatory factors that affect companies' response efforts and constructs a machine learning-based model for predicting corporate response to the regulations. In Phase 1, we identified regulatory barriers through factor analysis and revealed the difficulties faced by each company. These are summarized as a map of the innovation commercialization journey. In Phase 2, we conducted logistic regression analysis to determine how regulatory barriers affect companies' regulatory response efforts. Finally, in Phase 3, we built a predictive model based on regulatory factors using random forest, SVM, and neural network algorithm, and confirmed the performance superiority of the predictive model.