Unpacking the Path from Knowledge Heterogeneity to Team Creativity: A Knowledge-Based View and Dynamic Capability Theory Perspective
This study examines how knowledge heterogeneity affects team creativity in the context of China’s digital intelligence transformation and analyzes the mediating effects of digital intelligence enablement and technology management capability. Grounded in the knowledge-based view and dynamic capability theory, a sequential mediation model of the effect of knowledge heterogeneity on team creativity is developed and tested using both hierarchical regression and structural equation modeling. We conducted a two-wave anonymous questionnaire survey in a knowledge-intensive enterprise in Shanghai and obtained 203 valid responses. The results indicate that we draw three main conclusions. First, knowledge heterogeneity has a significant positive effect on team creativity. Second, technology management capability and digital intelligence enablement act as mediators in this relationship. Technology management capability improves the efficiency of transforming heterogeneous knowledge, while digital intelligence enablement facilitates the integration and application of such knowledge. Finally, technology management capability and digital intelligence enablement together form a sequential mediation pathway, where heterogeneous knowledge first enhances technology management capability and then promotes digital intelligence enablement, ultimately fostering team creativity. This study deepens the understanding of how knowledge heterogeneity promotes team creativity and provides implications for advancing digital intelligence transformation and industry competitiveness.
Authors
- Heng Zhao (ORCID: https://orcid.org/0000-0002-7344-4329)
- Hongyi Cai
- Yong Huang (ORCID: https://orcid.org/0000-0001-5953-6908)
Institutions
- University of Shanghai for Science and Technology (CN)
- Beijing Jiaotong University (CN)
- China University of Geosciences (CN)
Publication Details
- Journal
- Administrative Sciences
- Published
- 2025-10-22
- DOI
- https://doi.org/10.3390/admsci15110408
- Primary Topic
- Innovation and Knowledge Management
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- University of Shanghai for Science and Technology