Skip to main navigation menu Skip to main content Skip to site footer

Research Article

Vol. 1 No. 3 (2025): International Journal of Multidisciplinary Research

Risk Assessment and Response Strategies for Corporate Human Resource Integration in the Context of Mergers and Acquisitions

DOI
https://doi.org/10.65231/ijmr.v1i3.108
Submitted
January 10, 2026
Published
2025-12-30

Abstract

Against the backdrop of intensified market competition, mergers and acquisitions (M&A) and restructuring have become an important path for enterprises to optimize resource allocation, yet improper human resource integration is a major cause of M&A failures. This paper, supported by Hofstede's Cultural Dimensions Theory, Human Capital Theory, and other relevant theories, focuses on two core risks: cultural conflicts and staff placement. It combines multiple types of cases, such as cross-border M&A and mixed-ownership reforms of state-owned enterprises, and applies scientific assessment methods including core talent inventory and cultural compatibility evaluation.Through the in-depth integration of theory and practice, the paper draws logical countermeasures from successful cases, including respecting cultural differences, locking in core talents, implementing incremental integration, and enabling mutual empowerment. It aims to achieve prevention before M&A, implementation during M&A, and optimization after M&A, providing a reference with both theoretical depth and practical value for human resource integration in enterprise M&A and restructuring, and helping to realize the M&A value of "1+1>2".

References

  1. Renneboog, L., & Vansteenkiste, C. (2019). Failure and success in mergers and acquisitions. Journal of Corporate Finance, 58(10), 650–699.
  2. Xie, H. J., & Qi, X. (2025). Digital technology and firm value: A study based on the digital M&A scenario. Journal of Management World, 41(10), 146–175. https://doi.org/10.19744/j.cnki.11-1235/f.2025.0129
  3. Vrontis, D., Christofi, M., Pereira, V., et al. (2022). Artificial intelligence, robotics, advanced technologies and human resource management: A systematic review. The International Journal of Human Resource Management, 33(3), 1237–1266.
  4. Zhao, Y. X., & Wei, D. X. (2025). Research on the incentive mechanism of AI - driven human resource management based on human capital flexibility and human resource management value calibration. Chinese Journal of Management, 22(10), 1826–1838.
  5. Liu, Y. B. (2018). Cultural conflicts and integration strategies in cross - border M&As of enterprises. Communication of Finance and Accounting, (29), 97–100. https://doi.org/10.16144/j.cnki.issn1002-8072.2018.29.024
  6. Luo, J. H., & Li, Y. (2025). The governance effect of monitoring - type minority shareholders: Evidence from M&A performance commitments. Accounting Research, (08), 62–73.
  7. Qi, R. (2025). Enterprise Financial Distress Prediction Based on Machine Learning and SHAP Interpretability Analysis.
  8. Zhang, T. (2025). From Black Box to Actionable Insights: An Adaptive Explainable AI Framework for Proactive Tax Risk Mitigation in Small and Medium Enterprises.
  9. 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.
  10. Qi, R. (2025). AUBIQ: A Generative AI-Powered Framework for Automating Business Intelligence Requirements in Resource-Constrained Enterprises. Frontiers in Business and Finance, 2(01), 86-88.
  11. Yi, X. (2025). Federated Incentive Learning: A Privacy-Preserving Framework for Ad Monetization and Creator Rewards in High-Concurrency Environments. American Journal Of Big Data, 6(3), 60-88.
  12. Yi, X. (2025). Real-Time Fair-Exposure Ad Allocation for SMBs and Underserved Creators via Contextual Bandits-with-Knapsacks.
  13. Qi, R. (2025, July). DecisionFlow for SMEs: A Lightweight Visual Framework for Multi-Task Joint Prediction and Anomaly Detection. In Proceedings of the 2025 International Conference on Economic Management and Big Data Application (pp. 899-903).
  14. Li, B. (2025). From Maps to Decisions: A GeoAI Framework for Multi-Hazard Infrastructure Resilience and Equitable Emergency Management. American Journal Of Big Data, 6(3), 139-153.
  15. Zhang, T. (2025). A Neuro-Symbolic and Blockchain-Enhanced Multi-Agent Framework for Fair and Consistent Cross-Regulatory Audit Intelligence.
  16. Tian, Y., Xu, S., Cao, Y., Wang, Z., & Wei, Z. (2025). An Empirical Comparison of Machine Learning and Deep Learning Models for Automated Fake News Detection. Mathematics, 13(13), 2088.