기업의 혁신활동 특성에 따른 코로나19 정부지원정책 효과:잠재프로파일 기반 다중집단 구조방정식 분석

This study examines the performance effects of COVID-19 government support policies focusing on how these effects vary with firms’ innovation activity characteristics. Using data from the Korea Innovation Survey (KIS), firms were classified into three innovation types—balanced, passive, and proactive—through Latent Profile Analysis (LPA). Then Multi-group Structural Equation Modeling (SEM) was employed to analyze heterogeneous policy effects. Results show that COVID-19 government support policies had significantly effects on firms’ innovation performance. Among policy types, tax incentives and financial support exhibited the strongest impacts on firms with higher innovation activity characteristics. Moreover, identical policies operated differently depending on innovation type. These findings imply the need for customized support policies that account for firm-specific innovation capacities in post-COVID economic recovery.