Prioritising barriers to be addressed in semiconductor supply chain localisation using an evolving neutrosophic multi-criteria decision-making approach

Semiconductor supply chain localisation has emerged as a pressing trend in the semiconductor manufacturing industry, yet it has received limited attention to date. Furthermore, barriers such as unfamiliarity with local laws, cultural differences, and limited availability of local human resources have hindered the localisation efforts of wafer foundries. Notably, given the constraints in budget, time, and resources, these barriers must be prioritised for effective mitigation. Additionally, given the prolonged timeline and emerging nature of semiconductor supply chain localisation, decision-makers may face indeterminacy and should consider multiple perspectives when formulating decisions. To support this, this study proposes an evolving neutrosophic fuzzy arithmetic mean (FAM)–decomposition analytic hierarchy process–technique for order preference by similarity to ideal solution (AHP–TOPSIS) approach. This hybrid method allows a foundry to prioritise barriers to be overcome in semiconductor supply chain localisation. This methodology is novel in that it integrates multiple decision-making perspectives and incorporates an evolving mechanism to optimise the decomposition process. Herein, its effectiveness was demonstrated through application to a real-world case study. The results indicated that “legal resolvability” was the most decisive criterion for comparing barriers from two decision-making perspectives, with its advantage over other criteria being more pronounced from the second viewpoint.