Ten-tier and multi-scale supplychain network analysis of medical equipment: Random failure and intelligent attack analysis

TL;DR

This study analyzes the resilience of the medical equipment supply chain during COVID-19 by examining the effects of random failures and targeted attacks across multiple tiers and scales using complex network analysis.

Contribution

It introduces a supply chain tier optimization tool and data-driven methods to identify thresholds for supply chain breakdown under various failure scenarios.

Findings

Supply chain network is highly vulnerable to targeted attacks.

Multiple tiers and scales influence supply chain resilience.

Tools developed can be applied to other industries' supply chain analysis.

Abstract

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.