When Sustainability Fails: Modeling the Impact of Sustainable Development Goal Risks on Global Supply Chain Vulnerability Using Bayesian Belief Networks

ABSTRACT

This study examines how progress toward the Sustainable Development Goals (SDGs) influences global supply chain risk and resilience by conceptualizing SDG risk as an interconnected and probabilistic source of vulnerability. Unlike prior studies treating sustainability indicators as static and isolated factors, this research models SDG risks as interdependent drivers capable of generating cascading disruptions across global supply chains. It is among the first studies to apply a Bayesian Belief Network (BBN) framework to analyze SDG interdependencies and their effects on supply chain risk across 158 countries using 2025 data from the Sustainable Development Report and CountryRisk.io. The BBN captures uncertainty, nonlinearity, and direct and indirect SDG relationships, including clusters grouped by sustainability dimensions. Validation using France and Liberia confirmed predictive reliability across contrasting development contexts. Findings show that social and institutional sustainability dimensions exert the strongest influence on supply chain vulnerability. SDG 11 (Sustainable Cities and Communities), SDG 7 (Affordable and Clean Energy), and SDG 16 (Peace, Justice and Strong Institutions) emerged as the most influential determinants of supply chain stability, with influence strengths of 0.49, 0.44, and 0.40, respectively. All countries exhibited high supply chain risk when social SDGs were assigned high‐risk conditions, emphasizing the importance of governance, institutional quality, and social cohesion. The study contributes by conceptualizing SDG risk as an interconnected vulnerability system, demonstrating the value of BBNs for modeling cascading sustainability risks, and identifying priority SDGs that strengthen supply chain resilience.