Published Online:July 2025
Product Name:The IUP Journal of Knowledge Management
Product Type:Article
Product Code:IJKM010725
DOI:10.71329/IUPJKM/2025.23.3.5-27
Author Name:Jun Cui
Availability:YES
Subject/Domain:Management
Download Format:PDF
Pages:5-27
Drawing upon resource-based theory (RBT) and knowledge-based view (KBV), this study investigates the impact of knowledge-based organizational support (KOS), AI-driven knowledge sharing (KS), organizational learning (OL), and knowledge management dynamic capabilities (KMDC) on organizational performance (OP) in Chinese technology firms. In particular, this study explores the relationships among these factors, alongside control variables such as education level, staff skills, and technological innovation, to provide a comprehensive understanding of their influence on performance management. The study analyzed the primary data collected from employees of various Chinese technology firms, using confirmatory factor analysis (CFA) to validate the measurement constructs and structural equation modeling (SEM) to evaluate the hypothesized relationships. The findings reveal several significant insights: KOS, KS with AI, KMDC, and OL have a direct positive effect on OP, emphasizing their critical roles in enhancing organizational outcomes; and control variables, i.e., education level, staff skills, and technological innovation, significantly moderate the relationships between KOS, KS with AI, KMDC, OL, and OP, further amplifying their impact. These results highlight the importance of fostering collaborative knowledge innovation mechanisms and leveraging dynamic capabilities for effective performance management.
Over the past decade, many software and high-technology companies across various sectors have seen rapid development of knowledge management, artificial intelligence (AI) technologies, knowledge technologies, knowledge sharing, and organizational learning. These factors have become important elements for development for many technology companies in China (Chowdhury et al., 2022).