Abstract
AbstractSupply networks need to exhibit stability in order to remain functional. Here, we apply a generalized modeling (GM) approach, which has a strong pedigree in the analysis of dynamical systems, to study the stability of real‐world supply networks. It goes beyond purely structural network analysis approaches by incorporating material flows, which are defining characteristics of supply networks. The analysis focuses on the network of interactions between material flows, providing new conceptualizations to capture key aspects of production and inventory policies. We provide stability analyses of two contrasting real‐world networks—that of an industrial engine manufacturer and an industry‐level network in the luxury goods sector. We highlight the criticality of links with suppliers that involve the dispatch, processing, and return of parts or sub‐assemblies, cyclic motifs that involve separate paths from a common supplier to a common firm downstream, and competing demands of different end products at specific nodes. Based on a critical discussion of our findings in the context of the supply chain management literature, we generate five propositions to advance knowledge and understanding of supply network stability. We discuss the implications of the propositions for the effective management, control, and development of supply networks. The GM approach enables fast screening to identify hidden vulnerabilities in extensive supply networks.
Highlights
Networks need to remain functional in the presence of disturbances and disruptions (Tang, 2006)
We are interested in the stability of material flows in supply networks, where its loss manifests itself by divergence from an equilibrium state and by oscillations, leading to uncontrolled inventory build-ups and/or stock-outs, production overtime and/or production shutdowns, all of which will typically have very costly consequences (Venkateswaran & Son, 2007)
The impact of network structure on performance in real-world supply networks remains an open research question. We address this gap in the context of supply network stability by applying generalized modeling (GM), a dynamical systems method from ecology, to two real networks
Summary
Networks need to remain functional in the presence of disturbances and disruptions (Tang, 2006). Even if a focal organization invests resources to analyze the structure of its entire supply network, there are a multitude of operational details that cannot be captured, for example, different suppliers may use different modes of production and different inventory management policies.
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