Exploring network dynamics in scientific innovation: collaboration, knowledge combination, and innovative performance

The system of scientific innovation can be characterized as a complex, multi-layered network of actors, their products and knowledge elements. Despite the progress that has been made, a more comprehensive understanding of the interactions and dynamics of this multi-layered network remains a significant challenge. This paper constructs a multilayer longitudinal network to abstract institutions, products and ideas of the scientific system, then identifies patterns and elucidates the mechanism through which actor collaboration and their knowledge transmission influence the innovation performance and network dynamics. Aside from fostering a collaborative network of institutions via co-authorship, fine-grained knowledge elements are extracted using KeyBERT from academic papers to build knowledge network layer. Empirical studies demonstrate that actor collaboration and their unique and diverse ideas have a positive impact on the performance of the research products. This paper also presents empirical evidence that the embeddedness of the actors, their ideas and features of their research products influence the network dynamics. This study gains a deeper understanding of the driving factors that impact the interactions and dynamics of the multi-layered scientific networks.