Resilient and sustainable supplier selection: a chance-constrained approach under disruption risk

Purpose In today’s volatile business environment, firms are required to balance cost efficiency, sustainability and operational resilience to sustain competitiveness. Supplier selection plays a pivotal role in this context; however, traditional models often fail to capture disruption risks caused by geopolitical tensions, health crises or natural disasters. This study aims to address this gap by developing a framework that explicitly incorporates disruption probabilities into sustainable supplier selection. Design/methodology/approach A chance-constrained goal programming (GP) model, enriched with Value-at-Risk (VaR) metrics, is proposed. The framework integrates disruption probabilities, demand variability, procurement costs and sustainability performance indicators to jointly optimize supplier choice. A real-world case from the automotive sector is used to demonstrate the applicability and robustness of the model under varying risk tolerance levels. Findings The empirical results reveal that the model consistently selects resilient supplier portfolios even under high uncertainty. It ensures cost control, safeguards sustainability thresholds and prevents excessive dependence on a small number of suppliers. The analysis highlights that incorporating probabilistic disruption modeling significantly improves procurement stability compared to conventional approaches. Originality/value Unlike prior studies that consider sustainability and disruption risk separately, this research offers an integrated framework that simultaneously accounts for financial, environmental and disruption-related concerns. By embedding disruption probabilities and diversification constraints into supplier selection, the study addresses a critical gap in procurement planning and contributes a novel methodological advancement for sustainable sourcing under uncertainty.