Unveiling a Data-Driven Circular Business Strategy Framework in a Digital Supply Chain: A Strategic Roadmapping for the Semiconductor Industry

Abstract

Unveiling a data-driven circular business strategy (CBS) framework in a digital supply chain is needed to develop a data-driven analysis owing to the necessity of reconstructing the attributes involved and concentrating on matching the operational and environmental technology together. The semiconductor industry encounters the challenge of integrating top management commitment and collaboration with digital manufacturing and production, which aligns with waste and resource management as well as operations efficiency. To achieve this challenge, this study utilizes a hybrid method using content, bibliographic, and cluster analyses, the entropy weighted method (EWM) and the fuzzy Delphi method (FDM), to validate the data-driven CBS in a digital supply 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 identified valid prioritized main attributes to support CBS in a digital supply chain. The findings indicate that digital integration capability, green innovation, waste repurposing, decision support systems, and machine learning applications can be used to enhance CBS in digital supply chains and contribute to data-driven practical guidance by using strategic roadmapping for the industry.