Aug 2026· International Journal on Advanced Science, Engineering and Information Technology· Vol 16, pp. 1389-1396· 0 citations
TL;DR
The proposed Enhanced Suitability Assessment for Return on Investment in Cloud Migration (E-SARoIC) is an integrated decision-support framework that combines all aspects, including migration strategy assessment, organizational suitability evaluation, Return on Investment analysis, and cloud configuration recommendations within a unified process.
Abstract
Cloud migration today has become a priority for organizations using digital transformation. However, existing decision-support approaches often assess migration suitability and financial feasibility separately, resulting in fragmented pre-migration planning. This study proposes the Enhanced Suitability Assessment for Return on Investment in Cloud Migration (E-SARoIC), an integrated decision-support framework that combines all aspects, including migration strategy assessment, organizational suitability evaluation, Return on Investment (RoI) analysis, and cloud configuration recommendations within a unified process. It is developed using the Design Science Research (DSR) methodology; the framework was implemented as the Cloud Suitability Investment Analysis System (CSIAS) prototype and evaluated using expert validation, an organizational case study, and a Technology Acceptance Model (TAM) assessment. Overall, the results demonstrate that E-SARoIC improves assessment effectiveness, efficiency, transparency, decision consistency, and usability while generating practical recommendations aligned with organizational and financial objectives. By integrating technical, organizational, and financial perspectives into a single decision-support environment, the proposed framework provides an approach to cloud migration planning and establishes a foundation for future intelligent cloud migration systems. Future studies should test the framework across industries and contexts to improve generalizability. Enhancing CSIAS with recommendation techniques, predictive analytics, and automation may strengthen support for complex cloud migrations. These advances could extend E-SARoIC's practical value and research contributions.
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