TY - JOUR
T1 - Global semiconductor supply chain resilience challenges and mitigation strategies: A novel integrated decomposed fuzzy set Delphi, WINGS and QFD model
AU - Moktadir, Md Abdul
AU - Ren, Jingzheng
N1 - Funding Information:
The work described in this paper was supported by a grant from the Research Committee of The Hong Kong Polytechnic University under student account code RKHB (PolyU Presidential Ph.D. Fellowship awardee to: Md Abdul Moktadir). The work was also supported by a grant from The Hong Kong-Macao Joint Research Development Fund of Wuyi University (Primary Work Programme: H-ZGKG, Project ID: P0043781), a grant from Aerospace Information Research Institute, Chinese Academy of Sciences (Funding Body Ref. No: XDA19000000, Project ID: P0043964), a grant from Research Institute for Advanced Manufacturing (RIAM), The Hong Kong Polytechnic University (1-CD9G, Project ID: P0046135), and a grant from Research Centre for Resources Engineering towards Carbon Neutrality (RCRE), The Hong Kong Polytechnic University (PolyU) (Project No.1-BBEC, Project ID: P0043023).
Publisher Copyright:
© 2024 Elsevier B.V.
PY - 2024/7
Y1 - 2024/7
N2 - The recent COVID-19 pandemic, Ukrainian-Russian conflict, China-US trade war, and current environmental concerns regarding carbon emissions have all made the semiconductor supply chain (SCSC) more vulnerable. In addition, the uncertainty of global SCSC is increasingly obscured owing to several resilience challenges within the exiting supply chain network. Thus, supply chain resilience issues are becoming popular among researchers and policymakers. Unfortunately, there is a lack of systematic research on evaluation of resilience challenges and mitigation strategies for the global SCSC. Additionally, existing models are incompetent to capture the optimistic and pessimistic views of experts during interaction assessment and mitigation strategy evaluation in an uncertain environment. Hence, this research, for the first time, develops a novel integrated Decomposed Fuzzy Set (DFS)-based Delphi, Weighted Influence Non-linear Gauge System (WINGS), and Quality Function Deployment (QFD) model to identify and assess strength-interaction relationship between resilience challenges and mitigation strategies. The findings demonstrated that out of thirteen resilience challenges, seven were identified as causal group resilience challenges while the remaining six were classified as result group resilience challenges indicating that addressing the causal group resilience challenges may directly influence the mitigation of the result group resilience challenges. According to findings of DFS-WINGS analysis, the resilience challenges “Geopolitical tensions” and “Natural disasters” are the two most priority causal group resilience challenges that can significantly influence the result group system components. Furthermore, the DSF-QFD analysis confirmed that the mitigation strategies “Investing in semiconductor R&D and developing regional semiconductor manufacturing facilities” and “Diversification of key components suppliers and promoting domestic manufacturing” received the highest correlation among the mitigation strategies to address the current resilience issues faced by global SCSC. The study findings make a significant contribution to policymaking. The roles of resilience challenges and importance of mitigation strategies both can be used as benchmarks for the SCSC to make the global SCSC more resilient and sustainable.
AB - The recent COVID-19 pandemic, Ukrainian-Russian conflict, China-US trade war, and current environmental concerns regarding carbon emissions have all made the semiconductor supply chain (SCSC) more vulnerable. In addition, the uncertainty of global SCSC is increasingly obscured owing to several resilience challenges within the exiting supply chain network. Thus, supply chain resilience issues are becoming popular among researchers and policymakers. Unfortunately, there is a lack of systematic research on evaluation of resilience challenges and mitigation strategies for the global SCSC. Additionally, existing models are incompetent to capture the optimistic and pessimistic views of experts during interaction assessment and mitigation strategy evaluation in an uncertain environment. Hence, this research, for the first time, develops a novel integrated Decomposed Fuzzy Set (DFS)-based Delphi, Weighted Influence Non-linear Gauge System (WINGS), and Quality Function Deployment (QFD) model to identify and assess strength-interaction relationship between resilience challenges and mitigation strategies. The findings demonstrated that out of thirteen resilience challenges, seven were identified as causal group resilience challenges while the remaining six were classified as result group resilience challenges indicating that addressing the causal group resilience challenges may directly influence the mitigation of the result group resilience challenges. According to findings of DFS-WINGS analysis, the resilience challenges “Geopolitical tensions” and “Natural disasters” are the two most priority causal group resilience challenges that can significantly influence the result group system components. Furthermore, the DSF-QFD analysis confirmed that the mitigation strategies “Investing in semiconductor R&D and developing regional semiconductor manufacturing facilities” and “Diversification of key components suppliers and promoting domestic manufacturing” received the highest correlation among the mitigation strategies to address the current resilience issues faced by global SCSC. The study findings make a significant contribution to policymaking. The roles of resilience challenges and importance of mitigation strategies both can be used as benchmarks for the SCSC to make the global SCSC more resilient and sustainable.
KW - Decomposed fuzzy set Delphi
KW - Decomposed fuzzy set QFD
KW - Decomposed fuzzy set WINGS
KW - Mitigation strategies
KW - Resilience challenges
KW - Semiconductor supply chain
UR - http://www.scopus.com/inward/record.url?scp=85193288463&partnerID=8YFLogxK
U2 - 10.1016/j.ijpe.2024.109280
DO - 10.1016/j.ijpe.2024.109280
M3 - Journal article
AN - SCOPUS:85193288463
SN - 0925-5273
VL - 273
JO - International Journal of Production Economics
JF - International Journal of Production Economics
M1 - 109280
ER -