Effect of Innovation Community on Innovation Performance in the Multi-layered Innovation Ecosystem

Abstract

The existing literature on innovation ecosystems either focuses on whole-network at the macro-level or emphasizes a firm’s ego-network at the micro-level, while few studies have investigated network community analysis at the meso-level. Additionally, innovation ecosystem studies overlook the differences between knowledge ecosystems and business ecosystems and mostly focus on a single-layer analysis of the ecosystem. Therefore, the current paper aims to explore the mechanism of knowledge-business community connectivity in a two-layered innovation ecosystem on firm innovation performance. Based on multi-source heterogeneous data such as patents and VAT invoices, using social network analysis, Newman topological clustering and multiple regression, we analyze community connectivity and firm innovation performance. We find that the connectivity of within-knowledge communities and cross-business communities significantly positively affect firm innovation performance; the connectivity of cross-knowledge communities and within-business communities has a significant negative impact on firm innovation performance; in addition, the interaction of knowledge-business community connectivity has a significant negative effect on firm innovation performance. This study deepens and enriches the study of the mechanism of innovation communities on innovation performance at the meso level, and expands innovation ecosystem research from the perspective of knowledge-business two-layer networks; it provides insights for China to construct and improve innovation ecosystems and promote innovation-driven development.