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Effects of human–machine interaction on employee’s learning: A contingent perspective
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 t...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9490363/ https://www.ncbi.nlm.nih.gov/pubmed/36160504 http://dx.doi.org/10.3389/fpsyg.2022.876933 |
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author | Sen, Wang Hong, Zhao Xiaomei, Zhu |
author_facet | Sen, Wang Hong, Zhao Xiaomei, Zhu |
author_sort | Sen, Wang |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-9490363 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-94903632022-09-22 Effects of human–machine interaction on employee’s learning: A contingent perspective Sen, Wang Hong, Zhao Xiaomei, Zhu Front Psychol Psychology 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. Frontiers Media S.A. 2022-09-07 /pmc/articles/PMC9490363/ /pubmed/36160504 http://dx.doi.org/10.3389/fpsyg.2022.876933 Text en Copyright © 2022 Sen, Hong and Xiaomei. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Psychology Sen, Wang Hong, Zhao Xiaomei, Zhu Effects of human–machine interaction on employee’s learning: A contingent perspective |
title | Effects of human–machine interaction on employee’s learning: A contingent perspective |
title_full | Effects of human–machine interaction on employee’s learning: A contingent perspective |
title_fullStr | Effects of human–machine interaction on employee’s learning: A contingent perspective |
title_full_unstemmed | Effects of human–machine interaction on employee’s learning: A contingent perspective |
title_short | Effects of human–machine interaction on employee’s learning: A contingent perspective |
title_sort | effects of human–machine interaction on employee’s learning: a contingent perspective |
topic | Psychology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9490363/ https://www.ncbi.nlm.nih.gov/pubmed/36160504 http://dx.doi.org/10.3389/fpsyg.2022.876933 |
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