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The impact of transactive memory systems on innovation performance in undergraduate teams
Peng Hu1, Die Hu2, Maoyan She1
1College of Management Science, Chengdu University of Technology, Chengdu, Sichuan, China.
Background:
Transactive Memory Systems (TMS) are widely recognized as an important mechanism for knowledge integration and collaborative performance in teams. However, limited research has examined how different TMS dimensions operate jointly in temporary undergraduate innovation teams, which are typically characterized by limited formal structure, short interaction histories, and strong dependence on peer-based collaboration. To address this gap, this study investigates how specialization, credibility, and coordination influence innovation performance in undergraduate innovation teams, and further examines whether credibility and coordination strengthen the effect of specialization on innovation performance.
Methods:
Grounded in the knowledge integration perspective, this study develops a conceptual model of TMS and innovation performance. Using survey data collected from undergraduate teams participating in innovation and entrepreneurship programs, structural equation modeling (SEM) was employed to examine the relationships among specialization, credibility, coordination, and innovation performance, as well as the moderating effects of credibility and coordination on the relationship between specialization and innovation performance.
Results:
The findings show that specialization, credibility, and coordination each have a significant positive effect on innovation performance. Moreover, the impact of specialization on innovation performance is strengthened when teams exhibit higher levels of credibility and coordination.
Originality/Value:
This study extends TMS research to undergraduate innovation teams and shows that TMS dimensions should be understood not only as distinct components, but also as interacting elements. It further contributes to innovation and entrepreneurship education research by explaining how interdisciplinary student teams can better translate distributed expertise into innovation outcomes through stronger peer credibility and collaborative coordination.
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