生成语法
期望理论
心理学
心理干预
相关性(法律)
生成模型
工作(物理)
社会心理学
性别差距
读写能力
测量数据收集
社会影响力
认知心理学
学历
应用心理学
作者
Dominik Zahs,Lynn Schmodde,Marius Wehner
出处
期刊:University of Hawaii at Manoa - ScholarSpace
日期:2025-12-23
摘要
Despite the growing relevance of generative AI in the workplace, a significant gender gap in its adoption persists. This study investigates why women are less likely than men to use generative AI tools at work and identifies predictors that explain this difference. Combining a cross-sectional survey (n = 200) with a one-week diary study (n = 76, 266 daily observations), we examine both the intention to use and actual daily use of generative AI. Across both studies, women reported lower usage intentions and spent significantly less time using generative AI. Drawing on the UTAUT, we find that performance expectancy is the strongest predictor—particularly among women—followed by social influence. In contrast, effort expectancy and facilitating conditions appear less relevant. Additional factors such as AI literacy and job demands further explain AI use. Our results highlight the need for gender-sensitive interventions to reduce the gender gap in generative AI use.
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