技术群体成员变动、知识流耦合与产业创新网络抗毁性:技术异质性的调节作用

Relationship between membership variation and knowledge coupling of technology clusters and industrial innovation network invulnerability: role of technological heterogeneity

开放式创新盛行的背景下,如何提升产业创新网络应对"创造性毁灭"的能力是学界和业界关注的重点。针对产业创新网络结果研究中动态中观层面的缺失,本研究聚焦整体网视角下技术群体的成员变动影响产业创新网络抗毁性的多层级作用关系,分析技术群体耦合的中介作用和群间技术异质性的调节作用。本研究以新能源产业主要技术领域的138个专利引用网络为研究对象,执行网络拓扑分析和层次回归分析进行实证检验。结果表明:技术群体耦合在技术群体成员变动与产业创新网络抗毁性的关系中起非线性中介作用,群间技术异质性正向调节中介作用的前半段路径。本研究拓展了技术群体的动态属性研究及其与产业创新网络抗毁性的跨层级关系研究,深化了技术群体成员变动如何影响产业创新网络抗毁性的作用机制。研究结论揭示了技术群体微观成员变动影响更高层次网络结果的作用机制,对产业政策部门如何构建抗毁性较高的创新网络具有重要的实践价值。

Industrial innovation networks are vulnerable to uncertainty or risks posed by factors such as the dynamic industrial environment, disruptive technologies, and extruded product production cycles during the innovation process. The major issue for academia and industry is to overcome these challenges quickly and optimally to improve the invulnerability of innovation networks. Previous research has investigated static network invulnerability caused by network governance, macro-structural attributes, core corporate governance, and cascading failure. However, two gaps on this topic need to be filled in this research. First, the dynamic evolution of the innovation network and its micro-dynamic foundation are ignored. Second, sufficient explanation from the mesoscopic cohesive subgroup is lacking.It is important to fill these gaps as the industrial innovation network is a dynamically evolving organization. The micro-dynamic behavior of network actors is the most fundamental factor affecting network outcomes. Conducting micro-foundations explains how lower-level actors and their interactions affect the outcomes at a higher level. Moreover, the cohesive subgroup is the intermediate form of the transformation from the micro to the macro level, playing a significant role in the dynamic establishment of micro-network members and macro innovation networks. Based on these considerations, this study seeks to address the following three questions. First, how does the membership variation of technology clusters influence innovation network invulnerability? Second, what role does the knowledge flow coupling between technology clusters play in the relationship? Third, is membership variation effective for reinforcing the knowledge flow coupling of technology clusters in the case of technological heterogeneity contingency? This study enhances existing research in the following three aspects. First, it contributes to the structural changes and the knowledge diffusion in the formation, merger, division, or disintegration of technology clusters caused by member variation, expanding the research on the dynamic properties of network communities. Second, it extends the understanding of technology clusters to the entire innovation network and analyzes the nonlinear mechanism of the coupling activity of technology clusters, the antecedent variable, on the invulnerability of innovation networks. Third, based on the global network perspective, this study constructs a cross-hierarchy analysis paradigm of “micro-dynamic behavior of members-medium technology clusters′ interaction-macro network outcome” and explains how the member variation improves innovation network invulnerability. Finally, this study extends technological heterogeneity as a situational variable to this research framework, deepening the understanding of the path in the first half of the mediating effects. We predict that technology cluster coupling plays a nonlinear mediating role in the relationship between membership variation and the invulnerability of industrial innovation networks. Moreover, inter-cluster technological heterogeneity positively moderates the positive effect of the rate of change of membership variation on technology cluster coupling. To test the hypotheses, we used the 11 main technological fields of the new energy industry as the research sample and constructed 138 patent citation networks as our analytical unit. Further, we identified technology clusters based on the block model and performed network topology and hierarchical regression analyses. The results show that membership variation positively affects the coupling of technology clusters and presents an inverted U-shaped influence on the invulnerability of the industrial innovation network. The inter-cluster technological heterogeneity positively moderates the first half path of the mediating effect. This research provides the following insights for industrial innovation network managers and regulators. First, it guides the construction of technology clusters and manages their interaction activities from micro-network members′ innovation behavior by understanding the dynamic behavior of the organization clustering. Second, it advocates that enterprise should focus on the disadvantages of “circle thinking” and organize technology clusters to enable appropriate innovation interactions to promote innovation networks. Third, from the global perspective of innovation network governance, it is necessary to establish a flexible configuration mechanism for cluster members and maintain the destructiveness of the innovation network of the new energy industry through appropriate coupling between technology clusters. Fourth, when the technological differences between technology clusters are large, they should be encouraged to frequently enter and exit the clusters′ boundaries to promote the formation of multidimensional and circulating channels of technology diffusion, improving the stable operation of the innovation network.