This paper takes knowledge level, knowledge features, technology platform, knowledge sharing information security, interaction of knowledge sharing and incentive mechanism as dependent variables; takes knowledge sharing willingness and consciousness of digital open collaboration as intermediary variables and builds a theoretical framework of influencing factors of knowledge sharing behavior from the perspective of digital innovation ecosystem.
We use structural equation models (SEM) for hypothesis testing and path analysis to quantitatively assess the direct and indirect effects of each variable on knowledge sharing behavior. In addition, to further uncover the synergistic effects among multiple variables, we employed fuzzy-set qualitative comparative analysis (fsQCA) to gain a more comprehensive understanding of how these conditions influence knowledge-sharing behavior.
The results of this paper show that the key factors to promote active knowledge sharing are the optimization of technology platform, the improvement of knowledge level, the complexity of knowledge characteristics, the strengthening of digital open collaboration concept, the improvement of incentive mechanism and the guarantee of knowledge sharing information security.
This paper uses structural equation model for hypothesis testing and path analysis, combined with fsQCA analysis method, to explore the multi-antecedent linkage effect. This will help to understand the dynamic mechanism of knowledge sharing in the digital innovation ecosystem and provide theoretical support and practical guidance for formulating effective strategies.
