Journal of Computing and Information Science in Engineering
Supply chains are complex global networks vital to the creation and distribution of goods and services. Recent black swan events, such as the COVID-19 pandemic, widespread IT disruptions, regional conflicts, and natural disasters, have underscored the need for resilient supply networks capable of delivering essential goods and services across diverse markets and populations. Emerging challenges, including climate change, labor market shifts, and evolving geopolitical dynamics, further emphasize the need for leveraging advanced digital technologies and artificial intelligence (AI) solutions to maintain stability and adaptability in global supply chains. Next-Generation Digital Supply Networks rely on data-driven and AI-powered tools to enhance predictability, transparency, and end-to-end visibility. Technologies like digital twins, generative AI, blockchain, knowledge graphs, cloud computing, and the industrial internet of things (IIoT) enable predictive analytics, adaptive controls, real-time data integration, and traceability. Together, these innovations facilitate greater operational flexibility and agility, essential for meeting complex market demands and enhancing resilience against disruptions. This special issue seeks to explore state-of-the-art developments in digital supply networks, emphasizing the transformative impact of data-driven and AI-based technologies.
Topic Areas
THE SCOPE OF THIS ISSUE INCLUDES BUT IS NOT LIMITED TO:
- Cloud platforms, and digital twins for manufacturing and logistics supply networks
- Ontologies and knowledge graphs for supply network information integration
- Large Language Model (LLM) and generative AI applications in supply networks
- Systematic approaches for stress-testing, risk management, and resilience analysis in supply networks
- Computational and AI-based methods for supplier discovery and supply network deployment
- Cybersecurity, traceability, counterfeiting, and blockchain in complex digital supply networks
- Computational models for service-oriented and distributed digital supply networks
- Sustainable supply chain practices enabled by information and communication technologies
- Supplier development programs for digital and analytical capabilities development
- Supply chain data and systems interoperability
Special Issue Publication Dates
Paper submission deadline: May 31, 2025Initial review completed: July 31, 2025
Publication date: March 2026
Submission Instructions
Papers should be submitted electronically to the journal through the ASME Journal Tool. If you already have an account, log in as an author and select Submit Paper. If you do not have an account, you can create one here.
Once at the Paper Submittal page, select the Journal of Computing and Information Science in Engineering, and then select the Special Issue on Next-Generation Digital Supply Networks.
Papers received after the deadline or papers not selected for the Special Issue may be accepted for publication in a regular issue.
Guest Editors
Farhad Ameri, Arizona State University, USA (farhad.ameri@asu.edu)
Thorsten Wuest, University of South Carolina, USA (twuest@mailbox.sc.edu)
David Romero, Tecnológico de Monterrey, Mexico (dromero@tec.mex)
Boonserm Kulvatunyou, National Institute of Standards and Technology, USA (boonserm.kulvatunyou@nist.gov)