A Multi-Stage T-SF MCDM Framework for Assessing Vulnerabilities in Cross-Border Logistics Chains

The rapid expansion of cross-border e-commerce (CBEC) has reshaped global trade while exposing supply chains to increasing vulnerabilities, including infrastructure bottlenecks, regulatory fragmentation, and operational disruptions. This study develops an integrated framework to evaluate and enhance the resilience of Vietnam's cross-border e-commerce supply chain (CBECSC). A hybrid T-spherical fuzzy (T-SF) multi-criteria decision-making framework is applied in three stages. First, the T-SF Delphi method (T-SF Delphi) is used to identify critical resilience factors. Second, the T-SF Decision-Making Trial and Evaluation Laboratory (T-SF DEMATEL) method is employed to analyze causal relationships among these factors. Third, strategic interventions are prioritized using the T-SF Combined Compromise Solution (T-SF COCOSO) method. To ensure methodological robustness, the ranking results obtained from T-SF COCOSO are further validated through comparative analysis with the T-SF Measurement Alternatives and Ranking according to Compromise Solution (T-SF MARCOS) and the T-SF Technique for Order Preference by Similarity to Ideal Solution (T-SF TOPSIS). The findings indicate that Customize Products, Mutual Contingency Plan, Trade Policies, Safety Stock Inventory, and Reconfigure Contingency Strategy exert the strongest causal influence on supply chain resilience. Although the empirical analysis focuses on Vietnam, the proposed framework offers a transferable methodology for other emerging economies facing similar CBEC challenges.

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Publication Details

Journal
Journal of Intelligent & Fuzzy Systems
Published
2026-05-08
DOI
https://doi.org/10.1177/18758967261445500
Primary Topic
E-commerce and Technology Innovations
Type
article
Field-Weighted Citation Impact
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article

A Multi-Stage T-SF MCDM Framework for Assessing Vulnerabilities in Cross-Border Logistics Chains

Phi-Hung Nguyen, Ming-Hua Lin, Thu-Hien Tran, Zhen-Hua Che et al.
Journal of Intelligent & Fuzzy Systems
E-commerce and Technology Innovations
article

A Multi-Stage T-SF MCDM Framework for Assessing Vulnerabilities in Cross-Border Logistics Chains

Phi-Hung Nguyen, Ming-Hua Lin, Thu-Hien Tran, Zhen-Hua Che, Jung-Fa Tsai
article en

Abstract

The rapid expansion of cross-border e-commerce (CBEC) has reshaped global trade while exposing supply chains to increasing vulnerabilities, including infrastructure bottlenecks, regulatory fragmentation, and operational disruptions. This study develops an integrated framework to evaluate and enhance the resilience of Vietnam's cross-border e-commerce supply chain (CBECSC). A hybrid T-spherical fuzzy (T-SF) multi-criteria decision-making framework is applied in three stages. First, the T-SF Delphi method (T-SF Delphi) is used to identify critical resilience factors. Second, the T-SF Decision-Making Trial and Evaluation Laboratory (T-SF DEMATEL) method is employed to analyze causal relationships among these factors. Third, strategic interventions are prioritized using the T-SF Combined Compromise Solution (T-SF COCOSO) method. To ensure methodological robustness, the ranking results obtained from T-SF COCOSO are further validated through comparative analysis with the T-SF Measurement Alternatives and Ranking according to Compromise Solution (T-SF MARCOS) and the T-SF Technique for Order Preference by Similarity to Ideal Solution (T-SF TOPSIS). The findings indicate that Customize Products, Mutual Contingency Plan, Trade Policies, Safety Stock Inventory, and Reconfigure Contingency Strategy exert the strongest causal influence on supply chain resilience. Although the empirical analysis focuses on Vietnam, the proposed framework offers a transferable methodology for other emerging economies facing similar CBEC challenges.

Journal of Intelligent & Fuzzy Systems
FPT University (VN), National Taipei University of Technology (TW), University of Taipei (TW), National Taipei University of Business (TW)
Openalex Percentile: Top 4%
E-commerce and Technology Innovations
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