Unveiling a data-driven circular business strategy (CBS) framework in a digital supply chain is needed to develop a data-drivenanalysis owing to the necessity of reconstructing the attributes involved and concentrating on matching the operational and en-vironmental technology together. The semiconductor industry encounters the challenge of integrating top management commit-ment and collaboration with digital manufacturing and production, which aligns with waste and resource management as wellas operations efficiency. To achieve this challenge, this study utilizes a hybrid method using content, bibliographic, and clusteranalyses, the entropy weighted method (EWM) and the fuzzy Delphi method (FDM), to validate the data- driven CBS in a digitalsupply chain. Furthermore, the fuzzy synthetic evaluation–decision-making trial and evaluation laboratory (FSE-DEMATEL)developed strategic data-driven circular business roadmapping. Hence, this study constructed a hierarchical structure and iden-tified valid prioritized main attributes to support CBS in a digital supply chain. The findings indicate that digital integrationcapability, green innovation, waste repurposing, decision support systems, and machine learning applications can be used toenhance CBS in digital supply chains and contribute to data-driven practical guidance by using strategic roadmapping for theindustry.