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Modeling Network Evolution and Underload Cascading Failure in Multi-Tier Strategic Supply Chain Networks under a Just-in-Case Strategy

  • Yun Guo 1,2,   
  • Fuqiang Zhang 1,2,*,   
  • Kai Ding 1,2,   
  • Felix T. S. Chan 3

Received: 28 Apr 2026 | Revised: 19 Jun 2026 | Accepted: 23 Jun 2026 | Published: 06 Jul 2026

Abstract

In the context of escalating geopolitical tensions and increasing supply uncertainty, global supply chains are increasingly shifting from the efficiency-oriented just-in-time (JIT) paradigm to a more redundancy-based just-in-case (JIC) strategy. The primary objective of this study is to examine the topological and functional implications of this strategic shift. To achieve this, this study first develops a directed and weighted five-tier supply chain network evolution model that incorporates dynamic compensation mechanisms, including multi-source substitution and internal inventory reserves. The model shows that the JIC strategy alleviates the “rich get richer” effect, leading to more balanced resource allocation. Based on this model, we investigate underload cascading failures triggered by supply shortages and evaluate network robustness using the order fulfillment rate. The results show that the evolved network has obvious dual characteristics of robustness and vulnerability. It can relatively resist small random disturbances, but it is particularly vulnerable to targeted attacks on key enterprises, and the system will fail rapidly due to bidirectional load propagation. In addition, although the JIC strategy improves the resilience to severe disturbances, excessive hoarding costs increase the threshold for the network’s survival and operation, and may also lead to early underload cascading failures under slight shocks. Managerially, this implies that focal enterprises must dynamically optimize, rather than blindly maximize, their strategic reserves to balance resilience with capital lock-up costs. These findings offer a theoretical basis for understanding the trade-off between resilience and cost in strategic supply chain design and provide managerial insights for focal enterprises seeking to build more resilient supply networks under uncertainty. A limitation of this study is its reliance on numerical simulations and future research should empirically validate these mechanisms using real-world industry data.

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Guo, Y.; Zhang, F.; Ding, K.; Chan, F. T. S. Modeling Network Evolution and Underload Cascading Failure in Multi-Tier Strategic Supply Chain Networks under a Just-in-Case Strategy. Operations and Supply Chain Innovation 2026, 1 (1), 5.
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