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Resilient Supply Chain Networks Post-Pandemic: A Multi-Criteria Decision Analysis
Subject area: Science,Engineering and Technology · Area of research: Supply Chain Management
Abstract
The COVID-19 pandemic exposed critical vulnerabilities in global supply chains, prompting the urgent need for resilient and adaptive supply chain network designs. This study presents a comprehensive framework utilizing Multi-Criteria Decision Analysis (MCDA) to evaluate and optimize post-pandemic supply chain resilience. By integrating qualitative and quantitative factors, the research identifies and prioritizes key resilience dimensions, including flexibility, redundancy, responsiveness, collaboration, and digitalization. A hybrid MCDA approach, combining Analytic Hierarchy Process (AHP) and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS), is employed to assess alternative supply chain configurations under uncertainty. The criteria are derived through expert consultation and literature synthesis, ensuring contextual relevance to post-pandemic disruptions such as labor shortages, transport constraints, geopolitical shifts, and demand volatility. Case application in the manufacturing sector demonstrates the practical relevance of the model. Results reveal that supply chains emphasizing local sourcing, agile distribution strategies, and digital integration outperform traditional cost-centric models in resilience rankings. Moreover, the incorporation of real-time data sharing and supplier diversification significantly enhances adaptability and recovery capabilities. The analysis provides strategic insights into trade-offs between efficiency and resilience, supporting decision-makers in reconfiguring supply chains to withstand future shocks. This research contributes to the growing body of knowledge on resilient supply chain design by offering a structured, data-driven method to navigate complexity and uncertainty in a post-pandemic world. It highlights the importance of adopting a holistic perspective that balances operational performance with long-term sustainability and risk mitigation. The proposed MCDA framework can serve as a decision-support tool for supply chain managers, policymakers, and stakeholders aiming to enhance systemic resilience without compromising competitiveness. Future research directions include integrating fuzzy logic for handling ambiguity and expanding the model to account for environmental and social sustainability metrics, ensuring alignment with broader sustainable development goals.
Keywords
Resilient Supply Chain, Multi-Criteria Decision Analysis, Post-Pandemic Logistics, AHP, TOPSIS, Supply Chain Disruption, Risk Mitigation, Supply Network Design, Sustainability, Decision Support.
References
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How to cite this paper
@article{1709599,
author = {Opeyemi Morenike Filani, John Oluwaseun Olajide, Grace Omotunde Osho},
title = {Resilient Supply Chain Networks Post-Pandemic: A Multi-Criteria Decision Analysis},
journal = {Iconic Research And Engineering Journals},
year = {2019},
volume = {2},
number = {9},
pages = {224-241},
issn = {2456-8880},
url = {https://www.irejournals.com/formatedpaper/1709599.pdf},
abstract = {The COVID-19 pandemic exposed critical vulnerabilities in global supply chains, prompting the urgent need for resilient and adaptive supply chain network designs. This study presents a comprehensive framework utilizing Multi-Criteria Decision Analysis (MCDA) to evaluate and optimize post-pandemic supply chain resilience. By integrating qualitative and quantitative factors, the research identifies and prioritizes key resilience dimensions, including flexibility, redundancy, responsiveness, collaboration, and digitalization. A hybrid MCDA approach, combining Analytic Hierarchy Process (AHP) and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS), is employed to assess alternative supply chain configurations under uncertainty. The criteria are derived through expert consultation and literature synthesis, ensuring contextual relevance to post-pandemic disruptions such as labor shortages, transport constraints, geopolitical shifts, and demand volatility. Case application in the manufacturing sector demonstrates the practical relevance of the model. Results reveal that supply chains emphasizing local sourcing, agile distribution strategies, and digital integration outperform traditional cost-centric models in resilience rankings. Moreover, the incorporation of real-time data sharing and supplier diversification significantly enhances adaptability and recovery capabilities. The analysis provides strategic insights into trade-offs between efficiency and resilience, supporting decision-makers in reconfiguring supply chains to withstand future shocks. This research contributes to the growing body of knowledge on resilient supply chain design by offering a structured, data-driven method to navigate complexity and uncertainty in a post-pandemic world. It highlights the importance of adopting a holistic perspective that balances operational performance with long-term sustainability and risk mitigation. The proposed MCDA framework can serve as a decision-support tool for supply chain managers, policymakers, and stakeholders aiming to enhance systemic resilience without compromising competitiveness. Future research directions include integrating fuzzy logic for handling ambiguity and expanding the model to account for environmental and social sustainability metrics, ensuring alignment with broader sustainable development goals.},
keywords = {Resilient Supply Chain, Multi-Criteria Decision Analysis, Post-Pandemic Logistics, AHP, TOPSIS, Supply Chain Disruption, Risk Mitigation, Supply Network Design, Sustainability, Decision Support.},
month = {March},
}