Knowledge Network Embeddedness and Innovation Resilience

Abstract

Innovation resilience refers to an innovator's capability to withstand disruptions and challenges and engage in innovation activities in a sustainable manner. Taking the innovation activities in the field of artificial intelligence as an example, this research analyzes the impact mechanisms of innovators’ innovation resilience. We propose four variables (i.e., combination breadth, combination opportunity, combination distance, and combination depth) to describe the combination characteristics of innovators’ knowledge elements, and find that the combination breadth of innovators’ knowledge elements has a positive impact on their innovation resilience, the combination distance of innovators’ knowledge elements has a negative impact on their innovation resilience, both the combination opportunities and combination depth of innovators’ knowledge elements have inverted U-shaped relationships with their innovation resilience.