Research on the impact mechanism of innovation resilience: a cross-level network perspective

This research investigates the impact mechanisms of innovators’ innovation resilience from a cross-level perspective (i.e. innovator level and whole network level). Taking the patent data in the field of artificial intelligence from 2017 to 2022 as an example, we examine the effects of the structural embeddedness and knowledge diversity of innovators on innovation resilience, and test the moderating effects of the density and knowledge diversity of whole networks. We find that both the structural embeddedness and knowledge diversity of innovators can positively influence their innovation resilience. The density of whole networks negatively moderates the effects of innovators’ structural embeddedness and knowledge diversity on innovation resilience, while the knowledge diversity of whole networks acts as a positive moderator in these relationships.