Modeling Quality Risk Propagation in Multi-Level Supply Networks

초록

This study proposes an integrated analytical framework to identify critical suppliers in multi-level supply networks in terms of quality risks. By combining Bayesian networks with agent-based modeling (ABM), the framework quantifies how quality risks propagate through complex supply networks. Three key metrics are proposed as qality risk propagation, quality-based risk impact, and the quality risk persistence index. Using these metrics, the study identifies critical suppliers and analyzes their network structural characteristics through node-centric properties (degree centrality, closeness centrality, eigenvector centrality) and path-centric properties (tier connectivity score, alternative path index) across four different network types. This approach enables focal firms to allocate quality management resources more efficiently by focusing on structurally important suppliers, including lower tier suppliers that are often overlooked. By addressing the limitations of traditional supplier evaluation methods, the framework supports more targeted and effective quality risk mitigation strategies across extended supply networks.