Human-artificial intelligence interaction, knowledge sharing and R&D team innovation performance

Purpose Previous research has mostly examined how human–artificial intelligence interaction (HAI) affects individual workers’ cognitive abilities, paying little attention to how well R&D teams collaborate with AI to achieve innovative performance. Based on theories such as social roles and knowledge management, this paper aims to explore differential impacts of partner and steward HAI on the innovation performance in the R&D team. In addition, to the mediating role of knowledge sharing (KS), and further validated the moderating roles played by knowledge protection regulation (KPR) and digital organizational culture (DOC). Design/methodology/approach This study used SPSS and AMOS to empirically examine a data sample of R&D teams from 60 Chinese firms with high R&D activities and strong innovation capabilities. Findings This study found that partner HAI is positively related to R&D team innovation performance and KS, whereas steward HAI is negatively related to these two outcomes. In addition, KS has a partial mediating role in the effect of HAI on innovation performance. The moderating role of KPR and DOC was found. Originality/value First, it broadens the meaning and application of HAI by reorienting the study toward the various roles that it plays in R&D teams’ innovation performance. Second, this research validates that KS is a significant driving path, highlights the significance of KS in HAI and innovation performance and adds to the body of knowledge management literature. Finally, it extends social role theory to the role relationship between people and AI, improving its application in the field of HAI.

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Publication Details

Journal
Journal of Knowledge Management
Published
2026-01-09
DOI
https://doi.org/10.1108/jkm-02-2025-0226
Citations
2
Primary Topic
Knowledge Management and Sharing
Type
article
Field-Weighted Citation Impact
124.44
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article

Human-artificial intelligence interaction, knowledge sharing and R&D team innovation performance

Jing Xue, Y Zhang, M.-J. Chen
2 citations
Journal of Knowledge Management
Knowledge Management and Sharing
124.44
article

Human-artificial intelligence interaction, knowledge sharing and R&D team innovation performance

Jing Xue, Y Zhang, M.-J. Chen
article en
2 citations

Abstract

Purpose Previous research has mostly examined how human–artificial intelligence interaction (HAI) affects individual workers’ cognitive abilities, paying little attention to how well R&D teams collaborate with AI to achieve innovative performance. Based on theories such as social roles and knowledge management, this paper aims to explore differential impacts of partner and steward HAI on the innovation performance in the R&D team. In addition, to the mediating role of knowledge sharing (KS), and further validated the moderating roles played by knowledge protection regulation (KPR) and digital organizational culture (DOC). Design/methodology/approach This study used SPSS and AMOS to empirically examine a data sample of R&D teams from 60 Chinese firms with high R&D activities and strong innovation capabilities. Findings This study found that partner HAI is positively related to R&D team innovation performance and KS, whereas steward HAI is negatively related to these two outcomes. In addition, KS has a partial mediating role in the effect of HAI on innovation performance. The moderating role of KPR and DOC was found. Originality/value First, it broadens the meaning and application of HAI by reorienting the study toward the various roles that it plays in R&D teams’ innovation performance. Second, this research validates that KS is a significant driving path, highlights the significance of KS in HAI and innovation performance and adds to the body of knowledge management literature. Finally, it extends social role theory to the role relationship between people and AI, improving its application in the field of HAI.

Journal of Knowledge Management
Xi'an Shiyou University (CN)
Industry, innovation and infrastructure
Openalex Percentile: Top 0%
Knowledge Management and Sharing
124.44
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Human-artificial intelligence interaction, knowledge sharing and R&D team innovation performance — Jing Xue, Y Zhang, et al. · Journal of Knowledge Management (2026) | TGRS Research Map | TGRS