知识管理
计算机科学
工作表现
学习迁移
认知
人力资源管理
资源(消歧)
生成语法
工作分析
人工智能
社会认知理论
知识转移
生成模型
数据科学
培训转移
人工智能应用
人力资源
绩效管理
社会智力
测量数据收集
信息技术
作者
Hui Zhang,Lidong Zhu,Ayuan Zhang,Kilichov Shohruh
出处
期刊:PLOS ONE
[Public Library of Science]
日期:2026-01-22
卷期号:21 (1): e0327786-e0327786
被引量:1
标识
DOI:10.1371/journal.pone.0327786
摘要
The rapid advancement of AI technology has accelerated the adoption of generative artificial intelligence (GenAI) tools in the workplace, eroding the boundaries between professional responsibilities and personal space, thus impacting employees' innovative performance. This study empirically examines the link between innovative job performance and GenAI tool usage, framed through the Uses and Gratifications Theory. Analyzing survey data from 366 employees nationwide revealed that: (1) both cognitive and social uses of GenAI tools significantly enhance innovative performance; (2) cognitive use primarily facilitates knowledge transfer behaviors, while social use bolsters resource acquisition. Enhanced knowledge transfer and resource acquisition, in turn, improve job satisfaction, which is pivotal in driving innovative performance. This study introduces a novel framework for utilizing GenAI tools to optimize and manage employee performance within organizational settings.
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