Author(s)

Yuan Song ¹

Affiliation(s)

¹ School of Economics and Management, Shanghai University of Political Science and Law, Shanghai, 201701, China

Corresponding Author

Yuan Song

ABSTRACT

There are some factors that can affect the traditional approach of management of the employees including, for instance, the fact that there is no optimum coordination between machines and human beings, the process of algorithm-driven decision-making lacks transparency, and the adaptability of the employee in job-changing. The purpose of this article is to analyze the psychological reactions of the employees in the context of digitalization of the workplace. It analyzes the impact mechanisms of these factors on work engagement, organizational identification, and innovative behavior from the dimensions of technology trust, psychological security, perceived algorithmic fairness, and job security. Simultaneously, a multi-scenario simulation analysis model is constructed to compare the psychological and behavioral characteristics of employees under different digital work environments. The results show that in human-machine collaboration scenarios, employee technology trust increases from 2.45 in the traditional manual model to 4.28, psychological security increases from 3.82 to 4.36, and work engagement and innovative behavior levels reach 4.37 and 4.41 respectively, indicating that intelligent systems can effectively stimulate employee creativity and work enthusiasm after undertaking repetitive tasks.

KEYWORDS

Human-machine collaboration; Algorithm management; Digital workforce; Employee psychology; Employee behavior

CITE THIS PAPER

Yuan Song. Employee Psychology and Behavior in Human-Machine Collaboration, Algorithm Management, and Digital Workforce Scenarios. Journal of Human Resource Development (2026). Vol. 8, No. 1, 22-31. DOI: http://dx.doi.org/10.23977/jhrd.2026.080104.

REFERENCES

[1] Okatta C G, Ajayi F A, Olawale O. Navigating the future: integrating AI and machine learning in hr practices for a digital workforce[J]. Computer science & IT research journal, 2024, 5(4): 1008-1030.
[2] Muduli A, Choudhury A. Exploring the role of workforce agility on digital transformation: a systematic literature review[J]. Benchmarking: An International Journal, 2025, 32(2): 492-512.
[3] Akter S, Biswas K, Vrontis D, et al. Mastering digital transformation in workforce management[J]. Production Planning & Control, 2024, 35(13): 1525-1532.
[4] Calvo-Sotomayor I, Atutxa E. Workforce aging, labour productivity, and digital empowerment in Europe[J]. Public Administration and Policy, 2025, 28(1): 33-47.
[5] Kadhim M J. Digital literacy and its importance in the modern workforce[J]. International Journal of Social Trends, 2024, 2(2): 44-50.
[6] Mohiuddin D. HR tech adoption in digital banking: Implications for workforce development and financial sector growth in emerging economies[J]. Journal of Business Insight and Innovation, 2025, 4(2): 77-90.
[7] Tona O, Leidner D E, van Der Meulen N, et al. The Deployment of AI to Infer Employee Skills: Insights From Johnson & Johnson's Digital‐First Workforce Initiative[J]. Information Systems Journal, 2025, 35(6): 1516-1527.
[8] Rajamanickam S, Rus R C, Raji M N A. Enhancing tvet for a digital-ready workforce: A systematic literature review[J]. International Journal of Modern Education (IJMOE), 2024, 6(23): 865-881.
[9] Oostveen A M, Eimontaite I, Fletcher S. Human factors in digital manufacturing technology adoption: a workforce perspective[J]. The International Journal of Advanced Manufacturing Technology, 2025, 140(11): 6575-6593.
[10] Sharma K, Nigam N, Jha J K, et al. Role of readiness to change in the relationship between workforce agility and digital transformation: a two-timeframe study[J]. Journal of Global Information Management (JGIM), 2024, 32(1): 1-22.

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