Modeling Cloud Computing Adoption and its Impact on the Performance of IT Personnel in the Public Sector

This study investigates the factors influencing cloud computing adoption in the public sector, emphasizing the performance of IT personnel. Through qualitative interviews with five IT management professionals in the public sector, we identify key challenges in integrating cloud computing systems. The primary issues include technical complexity, skill and knowledge deficits in data governance and budget constraints. These insights inform the development of the Cloud Computing Capacity and Integration Model for the Public Sector, which proposes a comprehensive strategy to address these barriers. Our findings identified five key challenges to cloud computing adoption in the public sector. First, compatibility issues and system integration challenges resulting from conflicts between cloud platforms and older infrastructure contributed to operational inefficiency. Second, data migration issues due to incompatible formats and structures resulted in data loss and delays. Third, network constraints, such as limited bandwidth and high latency, hampered cloud service performance. Finally, a lack of staff training and budget constraints hampered successful cloud integration, emphasizing the importance of focused capacity-building initiatives and additional financial support. Thus, the "Cloud Computing Integration and Cloud Computing Acceptance and Performance Model" (CCAPM) presented in this research paper aims to deliver a comprehensive model that tackles a wide array of technical, operational, and human resource challenges to create an effective cloud computing ecosystem, enhance the adoption of cloud computing within the public sector, elevate the capabilities of public sector IT personnel, and develop a secure, resilient, and sustainable cloud computing environment in the public sector.

@article{Mahusin2025,
  title     = {Modeling Cloud Computing Adoption and its Impact on the Performance of IT Personnel in the Public Sector},
  journal   = {International Journal of Advanced Computer Science and Applications},
  volume    = {16},
  number    = {2},
  year      = {2025},
  publisher = {The Science and Information Organization},
  author    = {Noorbaiti Mahusin and Hasimi Sallehudin and Nurhizam Safie Mohd Satar and Azana Hafizah Mohd Aman and Farashazillah Yahya},
  doi       = {10.14569/IJACSA.2025.0160242},
  url       = {https://doi.org/10.14569/IJACSA.2025.0160242}
}