Zhang Kexin, Wu Cisheng, Ge Manman, Liu Teng
School of Management, Hefei University of Technology, Hefei, Anhui, China.
Front Artif Intell. 2025 Jul 9;8:1645172. doi: 10.3389/frai.2025.1645172. eCollection 2025.
With the development of AI technology, the employment mode of companies is undergoing unprecedented changes.
The paper defines the composition of blended human resources of a company as three types of formal employees, flexible workers and intelligent machine workers, constructs a blended human resource contribution rate calculation method based on BP-MIV, and analyzes the data of automobile manufacturing companies in 2022.
The results show that the contribution rate of blended human resources to company performance is 73.81%. Among them, the contribution rate of formal employees is 19.55%, while flexible workers and intelligent machine workers, despite their significantly smaller proportion in number compared to formal employees, have contribution rates of 20.26% and 34.00%, respectively. In further discussions, the calculation results of the blended human resource contribution rate based on the production function method were compared with those based on the BP-MIV method.
The findings indicate that the BP-MIV-based calculation method exhibits certain advantages in capturing nonlinear relationships, such as the synergistic effects of various types of blended human resources on company performance. This study attempts to propose a preliminary theoretical framework and methodological approach for blended human resource management research in the AI era.
随着人工智能技术的发展,公司的就业模式正在经历前所未有的变化。
本文将公司混合人力资源的构成定义为正式员工、灵活工人和智能机器工人三种类型,构建了基于BP-MIV的混合人力资源贡献率计算方法,并对2022年汽车制造公司的数据进行了分析。
结果表明,混合人力资源对公司绩效的贡献率为73.81%。其中,正式员工的贡献率为19.55%,而灵活工人和智能机器工人,尽管其数量在比例上明显小于正式员工,但其贡献率分别为20.26%和34.00%。在进一步的讨论中,将基于生产函数法的混合人力资源贡献率计算结果与基于BP-MIV法的计算结果进行了比较。
研究结果表明,基于BP-MIV的计算方法在捕捉非线性关系方面具有一定优势,例如各类混合人力资源对公司绩效的协同效应。本研究试图为人工智能时代的混合人力资源管理研究提出初步的理论框架和方法论方法。