STRENGTHENING CONSTRUCTION SUPPLY CHAINS: AN EXPLORATION OF DECISION-MAKING FRAMEWORKS FOR RESILIENCE IN THE FACE OF BLACK SWAN EVENT

The construction industry faces increasing vulnerabilities due to Black Swan Events (BSEs), high-impact, unpredictable disruptions that reshape global supply chains. Recent events, including the COVID-19 pandemic, the Suez Canal Blockade, and the Russia-Ukraine conflict, have exposed weaknesses in procurement strategies, leading to significant delays and cost escalations. The present research develops a decision-making framework to enhance supply chain resilience, focusing on procurement challenges associated with critical construction components such as electrical switchgear.

The study explore a decision-making framework to enhance supply chain resilience in construction procurement, particularly under disruptions caused by BSEs. The study follows a mixed method, integrating qualitative and quantitative approaches. Surveys validate the industry's supply chain challenges, while semi-structured interviews with industry professionals provide insights into decision-making processes under extreme uncertainty. The findings are synthesized into a three-module framework: (1) a decision tree model mapping procurement mitigation strategies based on industry responses, (2) a Choosing by Advantages (CBA) methodology for evaluating and selecting mitigation strategies under constrained conditions, and (3) planning of the implementation strategy integrating project management and contractual frameworks to guide structured execution.

Industry professionals validated the framework through structured reviews and feedback sessions. The findings highlight mitigation strategies, emphasizing early procurement, alternative sourcing, and contract adaptability as key resilience measures. The research contributes to the construction industry's preparedness by providing a structured decision-support tool, enabling professionals to navigate future supply chain disruptions effectively. The framework offers a foundation for industry adoption and future studies exploring AI-driven decision analytics for risk mitigation.