ALGORITHMIC MANAGEMENT AS A BUSINESS MODEL: IMPLICATIONS FOR WORKPLACE AUTONOMY, BEHAVIOR REGULATION, AND ORGANIZATIONAL TRUST

Main Article Content

Zheng Yajun
Karshalova Alma
Mynzhanova Gulzhakan

Abstract

This research investigates algorithmic management as a nascent business model and its effects on workplace autonomy, behavioural regulation, and organizational trust. The study uses secondary data from OECD, ILO, Eurofound, McKinsey, and Gartner on 40 countries and 120 firms from 2019 to 2024. It uses a quantitative panel regression model to look at how the intensity of algorithmic management affects organizational outcomes. The results show that the use of algorithmic management went up from 27% in 2019 to 61% in 2024. At the same time, the autonomy and trust indices went down by 21% and 17%, respectively. Regression results indicate that algorithmic intensity negatively affects autonomy (β = –0.46, p < 0.01) and trust (β = –0.31, p < 0.05), but transparency in algorithmic governance mitigates these effects, improving trust by 14–18% in firms with higher disclosure.

Downloads

Download data is not yet available.

Article Details

Data Availability Statement

All data supporting the findings of this study are presented in the text of the scientific work.

Section

Business economics

Author Biographies

Zheng Yajun, Al-Farabi Kazakh National University, Al-Farabi Business School

DBA student

Karshalova Alma, Al-Farabi Kazakh National University, Al-Farabi Business School

Ph.D., Associate Professor

Mynzhanova Gulzhakan, Kazakh Ablai Khan University of International Relations and World Languages

PhD

How to Cite

Zheng, Y., Karshalova, A., & Mynzhanova, G. (2026). ALGORITHMIC MANAGEMENT AS A BUSINESS MODEL: IMPLICATIONS FOR WORKPLACE AUTONOMY, BEHAVIOR REGULATION, AND ORGANIZATIONAL TRUST. Scientific Collection «InterConf», 305, 51–60. https://interconf.openpubarchive.com/index.php/proceeding/article/view/37

References

Eurofound. (2024). Automation, digitalisation and platform work: Implications for working conditions in Europe. Publications Office of the European Union.

Felix, B., Dourado, D., & Nossa, V. (2023). Algorithmic management, preferences for autonomy/security and gig workers’ wellbeing: A matter «Scientific Horizon in the Context No of fit? Frontiers in Psychology, 14, 1088183. https://doi.org/10.3389/fpsyg.2023.1088183

Gartner. (2024). AI and algorithmic management in the workplace: The next frontier of digital leadership. Gartner Research.

International Labour Organization (ILO). (2024). Managing work in the age of algorithms: Principles and policy responses. ILO Publications.

Kinowska, H. (2023). Influence of algorithmic management practices on workplace autonomy. International Journal of Human Resource Management, 36(8–21), 179776. https://doi.org/10.1108/ITP -02-2022-0079

McKinsey & Company. (2025). Algorithmic decision -making and the future of management. McKinsey Global Institute.

Nilsson, K. H. (2025). Algorithmic management and occupational health. Safety Science, 177, 106142. https://doi.org/10.1016/j.ssci.2025.106863

Organisation for Economic Co -operation and Development (OECD). (2025). Algorithmic management in the workplace. OECD Publishing.

Robert, L. P., Pierce, C., Morris, L., Kim, S., & Alahmad, R. (2020). Designing fair AI for managing employees in organizations: A review, critique, and design agenda. arXiv Preprint arXiv:2001.11784. https://doi.org/10.48550/arXiv.2002.09054

Zhang, M. M., Cooke, F. L., Ahlstrom, D., & McNeil, N. (2025). The rise of algorithmic management and implications for work and organisations. New Technology, Work and Employment, 40(3), 1 –13. https://doi.org/10.1111/ntwe.12343

Zhou, J., Verma, S., Mittal, M., & Chen, F. (2021). Understanding relations between perception of fairness and trust in algorithmic decision making. arXiv Preprint arXiv:2106.15260. https://doi.org/10.48550/arXiv.2109.14345 60 This work is distributed under the terms of the Creative