创造力
拆箱
心理学
联想(心理学)
社会心理学
对偶(语法数字)
主动性
灵活性(工程)
心理干预
认知
验证性因素分析
过程(计算)
双重过程理论(道德心理学)
应用心理学
知识管理
宏
社会影响力
认知心理学
认知灵活性
社会认知理论
适度
结构方程建模
多级模型
工作(物理)
工作行为
回归分析
组织行为学
产业与组织心理学
社会支持
发展心理学
测量数据收集
作者
Baorong Guo,Zaifeng Wu,Quan Wen,Yifeng Peng
出处
期刊:PLOS ONE
[Public Library of Science]
日期:2026-04-24
卷期号:21 (4): e0347335-e0347335
标识
DOI:10.1371/journal.pone.0347335
摘要
The deep integration of artificial intelligence (AI) into organizational settings has significantly transformed employees' work patterns, underscoring the need to investigate the mechanisms through which employee-AI collaboration influences creativity. Grounded in social cognitive theory, this study examines how employee-AI collaboration affects creativity via internal (self-efficacy) and external (performance pressure) mechanisms, and explores the moderating role of proactive behavior. Using convenience sampling, 733 valid responses were collected from six technology-driven enterprises. The theoretical model was tested through confirmatory factor analysis and regression analyses using AMOS and the Process macro for SPSS. Our results reveal that employee-AI collaboration is positively associated with creativity through two statistically supported indirect pathways: parallel indirect effects via self-efficacy (internal pathway) and performance pressure (external pathway), and a sequential indirect association in which higher self-efficacy is related to higher performance pressure, which in turn is positively related to creativity. Moreover, proactive behavior appears to moderate these relationships, such that the association between employee-AI collaboration and self-efficacy is more pronounced at higher levels of proactive behavior, whereas the association between employee-AI collaboration and performance pressure is less pronounced at higher levels of proactive behavior, yielding a pattern consistent with moderated indirect effects on creativity through both routes. These findings provide theoretical insights into the complex psychological processes underlying creativity in AI-enabled work environments and offer practical implications for optimizing AI applications and developing targeted interventions to foster employee creativity.
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