
doi: 10.18282/hrms5880
Purpose: In the era of digital transformation, employee–artificial intelligence (AI) collaboration has become an increasingly important work pattern. However, its impact on employees’ innovative behavior remains unclear. Drawing on the social cognitive framework, this study aims to examine how employee–AI collaboration influences employees’ innovative behavior and to uncover the underlying mechanism. Design/Methodology/Approach: A 2 × 2 scenario-based experiment was conducted among employees from China. The experiment manipulated two factors: the level of employee–AI collaboration (high vs. low) and the level of AI trust (high vs. low). Findings: The results indicate that employee–AI collaboration has a positive effect on employees’ innovative behavior. AI self-efficacy mediates the relationship between employee–AI collaboration and innovative behavior. In addition, AI trust moderates this relationship. Originality/Value: This study extends the research on human–AI collaboration to the domain of employee innovation and reveals the cognitive mechanism and boundary condition underlying the influence of employee–AI collaboration on innovative behavior.
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 0 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
