ArticleFrontiers in psychology2022
Effects of human-machine interaction on employee's learning: A contingent perspective.
Article in Frontiers in psychology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
1 citing paper in PubMed.
- Impact of Job Demands on Employee Learning: The Moderating Role of Human-Machine Cooperation Relationship.Computational intelligence and neuroscience · 2022Article
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The popularization of intelligent machines such as service robot and industrial robot will make human-machine interaction, an essential work mode. This requires employees to adapt to the new work content through learning. However, the research involved human-machine interaction that how influences the employee's learning is still rarely. This paper was to reveal the relationship between human-machine interaction and employee's learning from the perspective of job characteristics and competence perception of employees. We sent questionnaire to 500 employees from 100 artificial intelligence companies in China and received 319 valid and complete responses. Then, we adopted a hierarchical regression for the test. Empirical results show that human-machine interaction has a U-shaped curvilinear relationship with employee learning, and employee's vitality mediates the curvilinear relationship. In addition, job characteristics (skill variety and job autonomy) moderate the U-shaped curvilinear relationship between human-machine interaction and employee's vitality, especially the results of moderating effects varying with employee's competence perception. Exploring the mechanism of the effect of human-machine interaction on employee's learning enriches the socially embedded model. Moreover, it provides managerial implications how to enhance individual adaptability with the introduction of AI into firms. However, our research focuses more on the impact of human-machine interaction on employees at the initial stage of AI development, and the level of machine intelligence in various industries will reach a high degree of autonomy in the future. The future research can explore the impact of human-machine interaction on individual's behavior at different stages, and the results may vary depending on the technologies mastered by different individuals. The study has theoretical and practical significance to human-machine interaction literature by underscoring the important of individual's behavior among individuals with different skills.
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Registered trials
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