文献类型：期刊文献

中文题名：人工智能技术运用何以提高员工任务绩效?

英文题名：Can the Application of Artificial Intelligence Technology Promote Employees’ Task Performance?

作者：盛晓娟[1];郭辉[1];何勤[2]

第一作者：盛晓娟

机构：[1]北京联合大学管理学院,北京100101;[2]首都经济贸易大学劳动经济学院,北京100070

第一机构：北京联合大学管理学院

年份：2022

卷号：20

期号：4

起止页码：85-94

中文期刊名：北京联合大学学报：人文社会科学版

外文期刊名：Journal of Beijing Union University(Humanities and Social Sciences)

收录：国家哲学社会科学学术期刊数据库;北大核心:【北大核心2020】；CSSCI:【CSSCI2021_2022】；

基金：国家社会科学基金重点项目“人工智能对劳动力市场的冲击及劳动者知识技能转换应对研究”(项目编号:19AGL025)。

语种：中文

中文关键词：人工智能技术;知识技能要求;员工任务绩效

外文关键词：artificial intelligence technology;knowledge and skill requirements;employees’task performance

摘要：数字经济时代下,人工智能技术的应用对组织变革与员工个体的行为产生了深刻的影响。本研究基于资源保存理论以及自我决定理论,构建人工智能技术运用对员工任务绩效的研究框架,并探究知识技能要求的中介效应。通过对全国各地应用了人工智能技术的传统企业的员工展开问卷调查,并利用多层线性回归以及Bootstrap方法对最终回收的1500份有效问卷进行数据分析。研究结果显示,人工智能技术的运用对员工的任务绩效有显著的正向影响作用,并且知识技能要求在二者间起到显著的中介作用。
In the digital economy era, the application of artificial intelligence technology has had a profound impact on organizational change and individual employee behavior. However, there is a lack of research on the mechanisms of how the introduction of AI technologies affects the employee task performance. Based on the conservation of resource theory and self-determination theory, this paper explores the mediating effect of knowledge and skills requirements between the application of artificial intelligence technology and employees’ task performance. Through a survey of 1500 employees in traditional enterprises that have applied artificial intelligence technology all over the country, we conduct an empirical study. The main analysis results are as following: there is a significant positive correlation between the application of artificial intelligence technology and employees’ task performance, and the knowledge and skill requirements play a significant mediating role between them. The research has exploratory innovation meaning on the micro-field study of the effect of the utilization of artificial intelligence technology on employees’ performance. And the research findings of this paper are of great practical significance for the in-depth understanding of the potential intermediary mechanism of the utilization of artificial intelligence technology affecting employees’ job performance, and further for enterprise management practice and employees’ career management.