  Motivated by the COVID-19 pandemic, this paper explores the supply chain
viability of medical equipment, an industry whose supply chain was put under a
crucial test during the pandemic. This paper includes an empirical
network-level analysis of supplier reachability under Random Failure Experiment
(RFE) and Intelligent Attack Experiment (IAE). Specifically, this study
investigates the effect of RFA and IAE across multiple tiers and scales. The
global supply chain data was mined and analyzed from about 45,000 firms with
about 115,000 intertwined relationships spanning across 10 tiers of the
backward supply chain of medical equipment. This complex supply chain network
was analyzed at four scales, namely: firm, country-industry, industry, and
country. A notable contribution of this study is the application of a supply
chain tier optimization tool to identify the lowest tier of the supply chain
that can provide adequate resolution for the study of the supply chain pattern.
We also developed data-driven-tools to identify the thresholds for breakdown
and fragmentation of the medical equipment supply chain when faced with random
failures or different intelligent attack scenarios. The novel network analysis
tools utilized in the study can be applied to the study of supply chain
reachability and viability in other industries.
