Impact of scientific and technological innovation policies on innovation efficiency of high-technology industrial parks – A dual analysis with linear regression and QCA

Abstract

Scientific and technological innovation policies play a critical role in the innovative development of high-technology industrial parks. However, it remains unclear how scientific and technological innovation policies impact the innovation efficiency of high-technology industrial parks and what the impact pathways are. An in-depth investigation of this topic can give an insight into the inherent relation between the scientific and technological innovation policies and technological innovation. By conducting a theoretical analysis, this study empirically analyzed the impact of scientific and technological innovation policies on the innovation efficiency of high-technology industrial parks. The main research methods applied in this study were linear regression and qualitative comparative analysis (QCA). The results showed that the policy targets drove innovation efficiency in a relatively minor way. Among all policy tools, the demand-based policy tools had the most significant influence on innovation efficiency. The supply-based and environment-based policy tools had notable positive impacts during the lag periods of policies. The policy mix pathways for scientific and technological innovation policies that impact innovation efficiency come in four forms, namely, the targets-directed, demand-driven, supply-dominated environment optimization, and environment-dominated comprehensive pathways. Therefore, this study put forward proposals on classifying and refining the scientific and technological innovation policies and optimizing the policy mix-driven models.