<![CDATA[The growing number of public cloud computing service providers offering overlapping but non-identical combinations of availability, cost, security, scalability, technical support, and deployment speed has turned cloud provider selection into a genuine multi-criteria decision-making (MCDM) problem for organizations planning enterprise IT infrastructure migration. This study proposes a comparative decision support model that integrates Criteria Importance Through Intercriteria Correlation (CRITIC) for objective criteria weighting with the Combined Compromise Solution (CoCoSo) method for alternative ranking, and validates the resulting recommendation against an independent Entropy–TOPSIS pipeline. Five major cloud providers, AWS, Microsoft Azure, Google Cloud, Oracle Cloud, and Alibaba Cloud, were evaluated against six criteria: availability, monthly cost, security features, scalability, technical support, and deployment time. The CRITIC method identified security features (weight 0.203) as the most influential criterion, while CoCoSo ranked Google Cloud first with a score of 2.874, followed by AWS and Microsoft Azure. The independent Entropy–TOPSIS validation produced an identical ranking, with Google Cloud obtaining the highest closeness coefficient (0.864). A Spearman rank-order correlation of p = 1.000 between the two independent method pairs confirms full ranking consistency, indicating that the recommendation is robust to the choice of weighting and ranking technique within this illustrative case; because the underlying decision matrix is illustrative rather than independently audited vendor data, this consistency demonstrates the robustness of the method rather than a certified procurement recommendation. The proposed CRITIC–CoCoSo model, cross-validated with Entropy–TOPSIS, offers a transparent and reproducible framework for evidence-based cloud service provider selection.]]>
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