Supply chain viability concerns the entire supply system rather than one company or one single chain to survive COVID-19 disruptions. Mobility restriction and overall demand decline lead to systematically cascading disruptions that are more severe and longer lasting than those caused by natural disasters and political conflicts. In the present study, the authors find that large companies and manufacturers with traditional advantages suffer greater losses than small ones, which is conceptualized as the “Hub Paradox” by empirically investigating one Warp Knitting Industrial Zone of China. An underload cascading failure model is employed to simulate supply chain viability under disruptions. Numerical simulations demonstrate that when the load decreases beyond a threshold, the viability will drop down critically. Besides, supply chain viability depends on two aspects: the adaptive capability of the manufacturers themselves and the adaptive capability of the connections of the supply network. The comparison study demonstrates that enhancing cooperative relations between hub and non-hub manufacturers will facilitate the entire supply network viability. The present study sheds light on viable supply chain management. Compared with conventionally linear or resilient supply chains, intertwined supply networks can leverage viability with higher adaptation of redistributing production capacities among manufacturers to re-establish overall scale advantages. Finally, the present study also suggests solving the “Hub Paradox” from the perspective of complex adaptive system.

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The outbreak of COVID-19 has caused problems such as shortage of workforce, cost increase, cash flow tension, and uncertainty of supply chain. It has a specific negative impact on the raw material supply, procurement management, production resumption, logistics, and market of the supply chain, which can trigger cascading failures in supply chain networks. Aiming at the failure of upstream/downstream firms in supply chain networks due to the decreased product demand/material supply under the COVID-19, the present study adopted an underload cascading failure model for the supply chain networks. In this model, the hierarchical supply chain networks were constructed based on the Erdos Renyi (ER) model and Barabasi Albert (BA) model. The validity of the model was verified under random attack and target attack. In the random attack mode, the influences of model parameters were studied, and in the target attack mode, the influence of target protection and random protection measures on enhancing network invulnerability was also studied. Simulation results showed that the initial load and capacity lower bound of nodes impact cascading failure size. The former has a positive correlation with cascading failure size, while the latter negatively correlates with cascading failure size. Furthermore, random protection measures are more practical to prevent cascading failures.

Financial fraud is more likely to spread and produce serious and adverse results through social networks. This study investigates four protection strategies: the uniform protection strategy, the random protection strategy, the targeted protection strategy, and the acquaintance protection strategy based on the potential-investor-divestor (PID) model. The simulation results show that the targeted protection strategy is the best solution for both ER and BA networks. The random protection strategy is the least efficient solution, as it requires spreading a large number of anti-fraud messages to achieve a relatively good performance. The acquaintance protection strategy performs closely to the targeted protection strategy in terms of social dynamics. However, the uniform protection strategy is better than the acquaintance protection strategy, as it involves fewer victims when it collapses. This study suggests that the regulators should protect investors from financial fraud collapses by promoting the financial literacy education and regulating the behaviors of influential people.