LGNov 2, 2021

Discovering Supply Chain Links with Augmented Intelligence

arXiv:2111.01878v11 citations
Originality Synthesis-oriented
AI Analysis

This addresses supply chain risk analysis for companies, but it is incremental as it applies existing GNN methods to a specific domain.

The paper tackled the problem of predicting unknown suppliers and customers of companies using graph neural networks, achieving strong performance by combining model predictions with domain expertise.

One of the key components in analyzing the risk of a company is understanding a company's supply chain. Supply chains are constantly disrupted, whether by tariffs, pandemics, severe weather, etc. In this paper, we tackle the problem of predicting previously unknown suppliers and customers of companies using graph neural networks (GNNs) and show strong performance in finding previously unknown connections by combining the predictions of our model and the domain expertise of supply chain analysts.

Foundations

The foundational work for this paper's niche, ranked by how specifically the neighbourhood builds on it — not by global fame.

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