关键词: 区域创新生态系统, 协同机制, 创新绩效, 组态效应, 模糊集定性比较分析

Abstract: Constructing regional innovation ecosystem has become a key strategy to achieve regional collaborative innovation development and improve national innovation ability. The extant studies mainly focus on the overall research of the construction, evaluation and evolution of the regional innovation ecosystem, and analyze the net effect of regional innovation elements on innovation performance by adopting traditional linear regression method. However, regional innovation ecosystem is a complex and dynamic whole, in which frequent cooperation and interaction is happened among various elements. The traditional net effect research can't analyze the non-linear relationship between the system and innovation performance, and also unable to clarify the interactive relationship between different elements. Therefore, it is necessary to explore the complex causal relationship between regional innovation ecosystem and innovation performance from a holistic perspective.
Based on innovation-ecosystem perspective, this study constructs the analytical framework of regional innovation ecosystem from three aspects: innovation actor, innovation resource and innovation environment. To make up for the mismatch between the traditional methods and theories, this research applies the fuzzy set qualitative comparative analysis(fsQCA) method to carry out research, this method can not only explore the synergistic effect among multiple factors, but also identify the interactive relationship between conditions. Thus, taking 31 provinces in China as samples, this study explores the synergy mechanism of regional innovation ecosystem on innovation performance and the interactive relationship between innovation elements by employing fsQCA method.
The results of this research show that: (1) The sufficient of human resource is a necessary condition for regions to achieve high innovation performance, and the lack of R&D expenditure is a necessary condition for generating non-high innovation performance. (2) There are four recipes that can stimulate high innovation performance, namely, knowledge innovation actor & human resource recipe, technology innovation actor & R&D expenditure recipe, knowledge innovation actor balanced recipe and technology innovation actor balanced recipe, which can be summarized into two synergistic innovation strategies: "actor & resource" dual driven type and "actor & resource & environment" balanced driven type. There are three recipes for generating non-high innovation performance, and there is an asymmetrical relationship with the recipes of high innovation performance. (3) Under certain conditions, there are substitutive relationships both between innovation actors and between each innovation actor and the combination of environmental elements in regional innovation ecosystem. (4) The innovation strategies of regional innovation ecosystem in China show significant spatial distribution characteristics, the eastern region mainly adopts "actor & resource & environment" balanced driven type, while the central and western regions mainly adopt "actor & resource" dual driven type.
What's more, the study shows that: (1) This study introduces fsQCA method into the research of regional innovation ecosystem, which is helpful to enhance the understanding of innovation ecosystem theory in regional innovation research, and also contribute to deeply explore the synergy mechanism and the pathway diversity of the influence of regional innovation ecosystem on innovation performance. (2) This study discusses that under certain conditions, there are multiple substitutive relationships between innovation elements in the process of explaining regional innovation, which contributes to deepen the research on the symbiotic relationship between elements in regional innovation ecosystem. (3) This study demonstrates the important role of human resource and R&D expenditure in driving regional innovation performance, which helps to enrich the important connotation of resource-based view in the research of regional innovation ecosystem.
This study provides some policy implications for improving regional innovation ability in Chinese context. First of all, innovation resources are the basic guarantee factors to drive innovation performance, policymakers should give priority to ensuring adequate supply of human resources and R&D expenditure. Secondly, considering the substitutive relationship between innovation elements, policymakers should choose appropriate innovation strategies that adapts to local development endowment. When the innovation environment is good, policymakers should choose "actor & resource & environment" balanced driven type, otherwise, "actor & resource" dual driven strategy should be adopted.
For future research, first, it is meaningful to pay attention to the dynamic relationship between regional innovation ecosystem and innovation performance, which can be realized by introducing the dynamic QCA method with multi-period and multi-linear growth. Second, it will be helpful to provide a more fine-grained understanding on the causal complexity of regional innovation by integrating government support and innovation platform into the analysis framework, or refining the research objects to specific areas such as cities or high-tech zones.

Key words: regional innovation ecosystem, synergy mechanism, innovation performance, configurational effect, fuzzy set qualitative comparative analysis