| 摘要: |
| 尽管人工智能技术在改善员工绩效方面优势明显,但其工效提升机制却鲜有系统探索。 研究
旨在探讨人工智能技术对制造业员工工作效率的影响机制。 结合技术决定论和工作特征模型,从知识、
任务和社会 3 个角度选取知识专业化、工作需求、工作自主性和社会支持等工作特征作为中介变量,内在
动机作为调节变量,构建技术影响模型。 采用三步混合方法进行路径分析和神经网络模型检验,在控制
了替代危机和人口统计变量后,研究发现:人工智能应用分别可通过工作需求、工作自主性或知识专业化
提升员工工作效率,且工作需求的影响效应超过其他两个变量;社会支持不能在人工智能应用和员工工
作效率的关系之间起中介作用,但内在动机在其间起了负向调节作用。 该结论有助于理解人工智能技术
在制造业的落地机制,为持续提升人机协同效率提供路径参考。 |
| 关键词: 人工智能 工作特征模型 人工神经网络模型 工作效率 内在动机 |
| DOI： |
| 分类号: |
| 基金项目: |
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| The Influence Mechanism of Artificial Intelligence Application on the WorkEfficiency of Manufacturing Employees |
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LIU Shengmin, MA Manting
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| Abstract: |
| Although artificial intelligence (AI) technology has obvious advantages in improving employee
performance, the mechanism of its efficiency improvement has rarely been systematically explored. This study
aims to investigate the mechanism by which AI technology affects the work efficiency of manufacturing employees. Combining technological determinism and the job characteristics model, it selects job characteristics such
as knowledge specialization, job demands, job autonomy, and social support from the perspectives of knowledge, tasks, and society as mediating variables, and intrinsic motivation as a moderating variable, to construct
a technology impact model. A three-step mixed method is used for path analysis and neural network model verification. After controlling for substitution crisis and demographic variables, the study finds that the application
of AI can enhance employee work efficiency through job demands, job autonomy, or knowledge specialization
respectively; the influence effect of job demands exceeds that of the other two variables; social support cannot
play a mediating role in the relationship between AI application and employee work efficiency, but intrinsic motivation has a negative moderating effect on such relationship. This conclusion helps to understand the implementation mechanism of AI technology in the manufacturing industry and provides a path reference for continuously improving the efficiency of human-machine collaboration. |
| Key words: artificial intelligence job characteristics model artificial neural network model work efficiency intrinsic motivation |
