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“乐享繁荣”之际“保持警惕”:人工智能的使用如何影响员工的创新行为和主动技能发展。

"Remaining Vigilant" While "Enjoying Prosperity": How Artificial Intelligence Usage Impacts Employees' Innovative Behavior and Proactive Skill Development.

作者信息

Qian Jin, Chen Jiaxi, Zhao Shuming

机构信息

School of Business, Nanjing University, Nanjing 210093, China.

出版信息

Behav Sci (Basel). 2025 Apr 3;15(4):465. doi: 10.3390/bs15040465.

DOI:10.3390/bs15040465
PMID:40282086
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC12024141/
Abstract

As Artificial Intelligence (AI) has become a crucial element in the competitive advantage of enterprises, it is important to understand how to stimulate employees' creativity and initiative to cope with AI-driven changes. Drawing from the traditional Chinese wisdom of "remaining vigilant while enjoying prosperity" and based on the Conservation of Resources Theory, this study explored the impact of AI usage on employees' innovative behavior and proactive skill development. The results of a three-stage survey of 350 questionnaires showed that (1) AI usage positively influences employees' innovative behavior and proactive skill development; (2) job absorption partially mediates the relationship between AI usage and employees' innovative behavior; (3) AI job replacement anxiety partially mediates the relationship between AI usage and proactive skill development; and (4) employees' learning goal orientation positively moderates the impact of AI usage on innovative behavior through job absorption and on proactive skill development through AI job replacement anxiety. This study provides insights into how individuals respond to AI-driven changes and offers a novel perspective for developing research on AI usage at the individual level.

摘要

随着人工智能(AI)已成为企业竞争优势的关键要素,了解如何激发员工的创造力和主动性以应对人工智能驱动的变化至关重要。本研究借鉴中国传统智慧“居安思危”,并基于资源保存理论,探讨了人工智能的使用对员工创新行为和主动技能发展的影响。对350份问卷进行的三阶段调查结果表明:(1)人工智能的使用对员工的创新行为和主动技能发展具有积极影响;(2)工作专注度部分中介了人工智能使用与员工创新行为之间的关系;(3)人工智能工作替代焦虑部分中介了人工智能使用与主动技能发展之间的关系;(4)员工的学习目标导向通过工作专注度对人工智能使用对创新行为的影响以及通过人工智能工作替代焦虑对主动技能发展的影响起到正向调节作用。本研究深入了解了个体如何应对人工智能驱动的变化,并为开展个体层面的人工智能使用研究提供了新视角。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5823/12024141/fa37d11c9d70/behavsci-15-00465-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5823/12024141/37ca8f8626e3/behavsci-15-00465-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5823/12024141/e72549937947/behavsci-15-00465-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5823/12024141/48b9d785eddb/behavsci-15-00465-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5823/12024141/fa37d11c9d70/behavsci-15-00465-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5823/12024141/37ca8f8626e3/behavsci-15-00465-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5823/12024141/e72549937947/behavsci-15-00465-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5823/12024141/48b9d785eddb/behavsci-15-00465-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5823/12024141/fa37d11c9d70/behavsci-15-00465-g004.jpg

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