Multi-Cloud and Cloud-Native Strategies for Digital Human Capital Management in Saudi Arabia: Building Scalable and Future-Ready HR Technology Platforms

References

[1] Alonso J, Orue-Echevarria L, Casola V, et al. Understanding the challenges and novel architectural models of multi-cloud native applications: a systematic literature review. Journal of Cloud Computing. 2023;12:6. https://doi.org/10.1186/s13677-022-00367-6

[2] Hasan MH, Osman MH, Admodisastro NI, Muhammad MS. Legacy systems to cloud migration: a review from the architectural perspective. Journal of Systems and Software. 2023;202:111702. https://doi.org/10.1016/j.jss.2023.111702

[3] Michael Ayas H, Leitner P, Hebig R. An empirical study of the systemic and technical migration towards microservices. Empirical Software Engineering. 2023;28:85. https://doi.org/10.1007/s10664-023-10308-9

[4] Velepucha V, Flores P. A survey on microservices architecture: principles, patterns and migration challenges. IEEE Access. 2023;11:88339–88358. https://doi.org/10.1109/ACCESS.2023.3305687

[5] Nordli ET, Haugeland SG, Nguyen PH, Song H, Chauvel F. Migrating monoliths to cloud-native microservices for customizable SaaS. Information and Software Technology. 2023;160:107230. https://doi.org/10.1016/j.infsof.2023.107230

[6] Zhang X, Cui L, Shen W, et al. File processing security detection in multi-cloud environments: a process mining approach. Journal of Cloud Computing. 2023;12:100. https://doi.org/10.1186/s13677-023-00474-y

[7] Martin R, Vidal I, Valera F. A software-defined connectivity service for multi-cluster cloud native applications. Computer Networks. 2024;248:110479. https://doi.org/10.1016/j.comnet.2024.110479

[8] Singh B, Kaur R, Woodside M, Chinneck JW. Low-power multi-cloud deployment of large distributed service applications with response-time constraints. Journal of Cloud Computing. 2023;12:1. https://doi.org/10.1186/s13677-022-00363-w

[9] Lin J, Xie D, Huang J, Liao Z, Ye L. A multi-dimensional extensible cloud-native service stack for enterprises. Journal of Cloud Computing. 2022;11:83. https://doi.org/10.1186/s13677-022-00366-7

[10] Ni K, Mondal SK, Kabir HMD, Tan T, Dai HN. Toward security quantification of serverless computing. Journal of Cloud Computing. 2024;13:140. https://doi.org/10.1186/s13677-024-00703-y

[11] Park J, Jeong S, Yeom K. Private cloud bespoke orchestrator: techniques for constructing and operating bespoke-private cloud virtual machine environments for cloud users. Journal of Cloud Computing. 2025;14:34. https://doi.org/10.1186/s13677-025-00760-x

[12] Alouffi B, Hasnain M, Alharbi A, Alosaimi W, Alyami H, Ayaz M. A systematic literature review on cloud computing security: threats and mitigation strategies. IEEE Access. 2021;9:57792–57807. https://doi.org/10.1109/ACCESS.2021.3073203

[13] Nassif AB, Talib MA, Nasir Q, Albadani H, Dakalbab FM. Machine learning for cloud security: a systematic review. IEEE Access. 2021;9:20717–20735. https://doi.org/10.1109/ACCESS.2021.3054129

[14] Alghaith W. The role of trust in cloud service providers on the adoption of cloud computing in Saudi Arabia: an empirical investigation. Journal of Computer Science. 2023;19(9):1107–1123. https://doi.org/10.3844/jcssp.2023.1107.1123

[15] Alamri N, Alzahrani S. Navigating the clouds: an exploratory research of cloud computing adoption in Saudi Arabia’s small and medium enterprises. Engineering, Technology & Applied Science Research. 2024;14(6):17859–17869. https://doi.org/10.48084/etasr.8435

[16] Alshahrani A. Adopting emerging technologies in digital government: a multi-case analysis of drivers, enablers, and challenges in Saudi Arabia. Digital Government: Research and Practice. 2025;6(3):36. https://doi.org/10.1145/3719297

[17] Al-Hawamleh AM. Investigating the multifaceted dynamics of cybersecurity practices and their impact on the quality of e-government services: evidence from the KSA. Digital Policy, Regulation and Governance. 2024;26(3):317–336. https://doi.org/10.1108/DPRG-11-2023-0168

[18] Alrashedi AK. Future workforce skills for Saudi Arabia: a PLS-SEM analysis of Vision 2030 readiness. Information Development. 2025. https://doi.org/10.1177/02666669251357311

[19] Hassan AB, Al-Subhi RA, Bajaber N. The impacts of digital transformation on HR efficiency in KSA. International Journal of Financial, Administrative and Economic Sciences. 2024;3(10):278–319. https://doi.org/10.59992/IJFAES.2024.v3n10p8

[20] Abubakar AA, Al-Mamary YH, Singh HP, Singh A, Alam F, Agrawal V. Exploring factors influencing sustainable human capital development: insights from Saudi Arabia. Heliyon. 2024;10(16):e35676. https://doi.org/10.1016/j.heliyon.2024.e35676

[21] Zhou Y, Cheng Y, Zou Y, Liu G. e-HRM: a meta-analysis of the antecedents, consequences, and cross-national moderators. Human Resource Management Review. 2022;32(4):100862. https://doi.org/10.1016/j.hrmr.2021.100862

[22] da Silva LBP, Soltovski R, Pontes J, et al. Human resources management 4.0: literature review and trends. Computers & Industrial Engineering. 2022;168:108111. https://doi.org/10.1016/j.cie.2022.108111

[23] Bansal A, Panchal T, Jabeen F, Mangla SK, Singh G. A study of human resource digital transformation (HRDT): a phenomenon of innovation capability led by digital and individual factors. Journal of Business Research. 2023;157:113611. https://doi.org/10.1016/j.jbusres.2022.113611

[24] Malik A, Budhwar P, Kazmi BA. Artificial intelligence (AI)-assisted HRM: towards an extended strategic framework. Human Resource Management Review. 2023;33(1):100940. https://doi.org/10.1016/j.hrmr.2022.100940

[25] Basu S, Majumdar B, Mukherjee K, Munjal S, Palaksha C. Artificial intelligence–HRM interactions and outcomes: a systematic review and causal configurational explanation. Human Resource Management Review. 2023;33(1):100893. https://doi.org/10.1016/j.hrmr.2022.100893

[26] Bar-Gil O, Ron T, Czerniak O. AI for the people? Embedding AI ethics in HR and people analytics projects. Technology in Society. 2024;77:102527. https://doi.org/10.1016/j.techsoc.2024.102527

[27] Manroop L, Malik A, Milner M. The ethical implications of big data in human resource management. Human Resource Management Review. 2024;34(2):101012. https://doi.org/10.1016/j.hrmr.2024.101012

[28] Montero Guerra JM, Danvila-del-Valle I, Méndez-Suárez M. The impact of digital transformation on talent management. Technological Forecasting and Social Change. 2023;188:122291. https://doi.org/10.1016/j.techfore.2022.122291

[29] Pan Y, Froese FJ. An interdisciplinary review of AI and HRM: challenges and future directions. Human Resource Management Review. 2023;33(1):100924. https://doi.org/10.1016/j.hrmr.2022.100924

[30] Pereira V, Hadjielias E, Christofi M, Vrontis D. A systematic literature review on the impact of artificial intelligence on workplace outcomes: a multi-process perspective. Human Resource Management Review. 2023;33(1):100857. https://doi.org/10.1016/j.hrmr.2021.100857

@article{1723995,
      author = {Faraz Jameel Siddiqui},
      title = {Multi-Cloud and Cloud-Native Strategies for Digital Human Capital Management in Saudi Arabia: Building Scalable and Future-Ready HR Technology Platforms},
      journal = {Iconic Research And Engineering Journals},
      year = {2026},
      volume = {10},
      number = {4},
      pages = {2134-2147},
      issn = {2456-8880},
      url = {https://www.irejournals.com/formatedpaper/1723995.pdf},
      abstract = {Digital human capital management increasingly depends on interconnected recruitment, payroll, learning, workforce planning and employee-service applications. Yet distributing these functions across cloud providers does not automatically produce integration, resilience or trustworthy personnel decisions. This integrative review examines how multi-cloud and cloud-native strategies can support scalable human resource technology platforms in Saudi Arabia while preserving information accountability and employee confidence. Thirty peer-reviewed publications issued during 2020–2025 are examined across software architecture, electronic human resource management, cyber security and Saudi digital transformation. The synthesis distinguishes application portability from data portability, technical availability from operational continuity, and analytic capability from legitimate data use. It proposes a layered reference architecture combining domain-oriented services, controlled integration, sovereign data stewardship, interoperable identity and observable operations. A staged implementation pathway is developed for organisations modernising heterogeneous enterprise systems, together with indicators for evaluating capability, fairness, resilience and economic sustainability. The evidence suggests that selective workload placement and disciplined platform engineering are more defensible than indiscriminate replication across providers. The principal contribution is an HR-specific governance framework that links technical architectural choices to human capital outcomes and Saudi institutional requirements. The framework remains conceptual and requires empirical evaluation before performance or compliance benefits can be asserted.},
      keywords = {digital human capital management; multi-cloud; cloud-native architecture; Saudi Arabia; human resource information systems; data governance; Vision 2030},
      month = {October},
  }