Journal of Global Information Management, volume 32, issue 1, pages 1-27

Supply Chain Management in the Digital Economy

Anzhong Huang 1
Jianming Zhuang 2
YuHeng Ren 3
Yun Rao 4
Sang-Bing Tsai 5
Publication typeJournal Article
Publication date2024-11-22
scimago Q1
SJR0.838
CiteScore5.8
Impact factor4.5
ISSN10627375, 15337995
Abstract

Supply chain management (SCM) is pivotal in orchestrating the flow of goods and services from suppliers to consumers, fundamentally shaping business operations worldwide. However, traditional SCM faces significant limitations, such as inefficiencies in handling complex data structures and adapting to rapid market changes, which undermine operational effectiveness. The application of deep learning technologies in SCM is increasingly recognized as crucial, offering powerful tools for real-time visibility, predictive analytics, and enhanced decision-making capabilities. We propose a VAE-GNN-DRL network model that integrates Variational Autoencoder (VAE), Graph Neural Network (GNN), and Deep Reinforcement Learning (DRL) to address these challenges by efficiently processing and analyzing complex supply chain data.

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