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Research Article

Vol. 1 No. 1 (2025): International Journal of Multidisciplinary Research

Research On Safeguard Mechanisms And Sustainability In The Digital Transformation Of Corporate Human Resource Management

DOI
https://doi.org/10.65231/ijmr.v1i1.19
Submitted
October 19, 2025
Published
2025-10-29

Abstract

Safeguard mechanisms form the essential foundation for ensuring the digital transformation of human resource management progresses from short-term breakthroughs to sustained deepening. This study constructs a comprehensive safeguard system encompassing four dimensions: institutional, organisational, technological, and cultural. Centred on dynamic synergy as its core logic, this system provides a stable regulatory framework for transformation through institutional design; empowers implementing entities to enhance execution capabilities by leveraging organisational restructuring; establishes a robust material foundation through technological architecture; and fosters collective consensus on transformation via cultural shaping. These four dimensions do not operate in isolation but form a virtuous cycle: "institutional frameworks guide organisational behaviour; organisations deploy technological tools; technology facilitates cultural dissemination; and culture reinforces institutional commitment." Ultimately, this cycle assists enterprises in transforming fragmented digital practices into enduring organisational capabilities, thereby achieving the sustainable development of digital transformation.

References

  1. Battini, D., Berti, N., Finco, S., Zennaro, I., & Das, A. (2022). Towards industry 5.0: A multi-objective job rotation model for an inclusive workforce. International Journal of Production Economics, 250, 108619.
  2. Berhil, S., Benlahmar, H., & Labani, N. (2020). A review paper on artificial intelligence at the service of human resources management. Indonesian Journal of Electrical Engineering and Computer Science, 18(1), 32-40.
  3. Da Silva, L. B. P., Soltovski, R., Pontes, J., Treinta, F. T., Leitão, P., Mosconi, E., ... & Yoshino, R. T. (2022). Human resources management 4.0: Literature review and trends. Computers & Industrial Engineering, 168, 108111.
  4. Szwarc, E., Golińska-Dawson, P., Bocewicz, G., & Banaszak, Z. (2024). Robust scheduling of multi-skilled workforce allocation: job rotation approach. Electronics, 13(2), 392.
  5. Li, D. (2022, April). Optimization of human resource management system based on clustering algorithm. In International Conference on Multi-modal Information Analytics (pp. 84-91). Cham: Springer International Publishing.
  6. Kalinin, A., & Klishevich, D. (2022). Talent Management and HRM Practices in SOEs: Review and Opportunities for Diversity Management Research. Diversity in Action, 239-264.
  7. Liu, X., Guo, P., & Zhao, J. (2025). From adaptation to transformation: how to stimulate leaders’ change-oriented organizational citizenship behaviors in project-based temporary organizations. Journal of Organizational Change Management, 38(1), 204-229.
  8. Rinaldi, M., Fera, M., Bottani, E., & Grosse, E. H. (2022). Workforce scheduling incorporating worker skills and ergonomic constraints. Computers & Industrial Engineering, 168, 108107.
  9. Sivathanu, B., & Pillai, R. (2018). Smart HR 4.0–how industry 4.0 is disrupting HR. Human Resource Management International Digest, 26(4), 7-11.
  10. Sugiana, I., Koni, A., & Kurniawan, W. (2024). Improving The Capital Management System For Micro Small And Medium Enterprises On The Quality Of Human Resources. International Journal of Economics, Management and Accounting (IJEMA), 2(4), 487-494.
  11. Zeng, R., Wang, X., Wang, Z., & Gu, Y. (2025). Logic and Path of China's Regional Economic Disparities: From Institutional Change, Factor Flow and Technological Innovation. Journal of Global Trends in Social Science, 2(8), 32-39.https://doi.org/10.70731/s98wcs90
  12. Xu, S., Cao, Y., Wang, Z., & Tian, Y. (2025, June). Fraud Detection in Online Transactions: Toward Hybrid Supervised–Unsupervised Learning Pipelines. In Proceedings of the 2025 6th International Conference on Electronic Communication and Artificial Intelligence (ICECAI 2025), Chengdu, China (pp. 20-22).
  13. Yi, X. (2025). Real-Time Fair-Exposure Ad Allocation for SMBs and Underserved Creators via Contextual Bandits-with-Knapsacks.
  14. Wang, Y. (2025). AI-AugETM: An AI-augmented exposure–toxicity joint modeling framework for personalized dose optimization in early-phase clinical trials. Preprints. https://doi. org/10.20944/preprints202507, 637, v1.
  15. Qi, R. (2025). Interpretable Slow-Moving Inventory Forecasting: A Hybrid Neural Network Approach with Interactive Visualization.
  16. Zhang, T. (2025). A Knowledge Graph-Enhanced Multimodal AI Framework for Intelligent Tax Data Integration and Compliance Enhancement. Frontiers in Business and Finance, 2(02), 247-261.
  17. Lin, H., & Gu, Y. (2025). Research on the Path to Enhance Supply Chain Resilience of SMEs in the Context of Digital Economy. Journal of Global Trends in Social Science, 2(9), 16-21.
  18. Gu, Y., Feng, G., & Li, Y. (2025). Research on the Impact Mechanism of Environmental Economics on Study Tour Education: Transnational Cases and Student Capacity Building. Journal of Global Trends in Social Science, 2(8), 46-52.
  19. Gu, Y., Pan, D., Yang, N., & Wang, X. (2025). Research on Storage and Transportation Cost Control and Technological Breakthroughs from the Perspective of Global Hydrogen Energy Development. Journal of Sustainable Built Environment, 2(5), 33-38.