Effects of human–machine interaction on employee’s learning: A contingent perspective - Sen, Wang; Hong, Zhao; Xiaomei, Zhu (Frontiers in Psychology, 2022)
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 how influences employee learning is still rarely. This paper is to reveal the relationship between human-machine interaction and employee 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-shape curvilinear relationship with employee learning and employee vitality mediates the curvilinear relationship. In addition, job characteristics (skill variety and job autonomy) moderate the U-shape curvilinear relationship between human-machine interaction and employee 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 learning enriches the socially embedded model. Moreover, it provides managerial implications how to enhances 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, 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 behavior at different stages, and the results may vary depending on the technologies masted by different individuals. The study has theoretical and practical significance to human-machine interaction literature by underscoring the important of individual behavior among individuals with different skills.