Cloud-based HR systems have become central to knowledge-driven decision-making. Yet, the risks they introduce, understood here as threats to organizational knowledge assets, such as the degradation of knowledge integrity, erosion of knowledge accessibility and compromises in knowledge security within HR processes, remain insufficiently understood. This study aims to identify the key challenges associated with cloud-based HR knowledge systems and proposes a prioritized set of mitigation strategies to guide organizational decision-making for safeguarding HR knowledge in cloud environments.
Grounded in knowledge management (KM) and dynamic capabilities theory, the study examines how organizations evaluate and address cloud-related knowledge risks. Using the Fuzzy Delphi method, expert judgments were synthesized to prioritize critical challenges. The Fuzzy TOPSIS technique was then applied to evaluate and rank feasible mitigation strategies under conditions of uncertainty, enabling a systematic assessment of alternatives without extensive pairwise comparisons.
The results highlight vulnerabilities, including cyber threats, weak access governance, migration challenges and data-leakage risks that threaten knowledge integrity, accessibility and security across HR processes. The proposed mitigation strategies provide decision-makers with an actionable priority framework for resource allocation, identifying the interventions that most effectively protect HR processes while balancing the constraints.
This study advances human resource information systems and KM scholarship by repositioning cloud HR adoption as a dynamic knowledge integration and reconfiguration process. It extends Dynamic Capabilities theory by explicating how sensing, seizing and transforming capabilities shape organisational responses to cloud-related HR knowledge risks. Future research can build on this framework to examine sectoral differences, longitudinal capability development and cross-cultural variations in cloud-enabled HR KM.
The findings guide managers to view cloud HR implementation as a strategic KM initiative rather than a purely IT project. Organisations should invest in developing dynamic capabilities to sense emerging HR knowledge risks, seize appropriate mitigation strategies and continuously reconfigure HR processes and expertise. The prioritised risk and strategy framework supports evidence-based decision-making for resource allocation, vendor selection and capability building.
By strengthening organisational capabilities to manage HR knowledge in cloud environments, the study contributes to more transparent, secure and fair people management practices. Effective handling of cloud-related HR knowledge risks can enhance employee trust, data privacy and equitable access to HR services. In the long term, improved cloud-enabled HR systems support inclusive workplaces by enabling consistent policy application, better employee development and evidence-based decision-making.
This study extends the knowledge governance literature by demonstrating how cloud-based HR systems require organisations to establish governance mechanisms that balance knowledge accessibility, protection and accountability. Methodologically, the combined application of Fuzzy Delphi and Fuzzy TOPSIS offers a means of operationalizing expert knowledge under uncertainty, producing a decision-ready output grounded in KM theory.
