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How Does Digital Knowledge Management Drive Employees’ Innovative Behavior?

Author

Listed:
  • Shuli Gao

    (Business College, Beijing Union University, Beijing 100025, China)

  • Jianbin Chen

    (Management College, Beijing Union University, Beijing 100101, China)

  • Pengfei Jiang

    (Management College, Beijing Union University, Beijing 100101, China)

Abstract

With AI and other technologies widely applied, knowledge management paradigms are being systemically reconstructed. How to effectively leverage digital technologies to manage knowledge and activate employees’ innovative behaviors has become key for enterprises’ sustainable development. This article explores the influence pathways of digital knowledge management on employees’ innovative behavior, conducting cross-level transmission mechanism research based on digital knowledge management, organizational learning, and employee innovation behavior. Drawing on 325 questionnaires and hierarchical regression, this study finds that: digital knowledge management positively effects employees’ innovative behavior; exploitative learning mediates more strongly than exploratory learning between digital knowledge management and employees’ innovative behavior; challenging technostress weakens the link between organizational learning and innovation. This paper also uses fsQCA analysis to identify three pathways to high employee innovation behavior: exploration-driven innovation based on full knowledge chain collaboration, dual-driven innovation oriented towards knowledge transformation, and dual-driven innovation oriented towards knowledge sharing. The conclusions of this study are intended to promote the application and development of digital knowledge management in enterprises and provide practical insights for enterprises to foster employee innovation and achieve sustainable development.

Suggested Citation

  • Shuli Gao & Jianbin Chen & Pengfei Jiang, 2025. "How Does Digital Knowledge Management Drive Employees’ Innovative Behavior?," Sustainability, MDPI, vol. 17(17), pages 1-26, August.
    • Handle: RePEc:gam:jsusta:v:17:y:2025:i:17:p:7823-:d:1738245
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