The Explore of Knowledge Management Dynamic Capabilities, AI-Driven Knowledge Sharing, Knowledge-Based Organizational Support, and Organizational Learning on Job Performance: Evidence from Chinese Technological Companies

Drawing upon Resource-Based Theory (RBT) and the 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 firms. In particular, this research 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. While recent studies on organizational performance have predominantly concentrated on digital business strategies and high-level decision-making, limited attention has been given to the role of digital maturity, workplace activities, and communication-related dynamics. This study addresses these gaps by consolidating critical factors that contribute to overarching job performance within organizations. Moreover, to empirically test the proposed hypotheses, data were collected from 129 valid questionnaires completed by employees across various Chinese firms. The research employed 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: (1) KOS, KS with AI, KMDC, and OL each have a direct positive effect on OP, emphasizing their critical roles in enhancing organizational outcomes. (2) Control variables, including education level, staff skills, and technological innovation, significantly moderate the relationships between KOS, KS with AI, KMDC, OL, and OP, further amplifying their impact.