EES Article Type: “Risk-aware Supply Chain Intelligence”
Modern supply chains are a major part of the world economy affecting the success of regional and global economic growth. With the globalization of business operations, supply chains especially the logistics process are threatened by all kinds of uncertainties and disruptions, which have resulted in an increasing interest in supply chain and logistics management considering various risk factors [1,2]. As modern supply chains and logistics systems are dynamic [3], complexly networked [4] and sometimes difficult to model using mathematical tools [5], their efficient management becomes a challenging task and often requires rich information, mass data and intensive human knowledge to accomplish.
With decision science entering the big data era, computation-based artificial intelligence (AI) has been used more and more in business risk management [6]. This special track focuses on the exploitation of data-driven, knowledge-intensive AI approaches to solve a wide spectrum of supply chain management scenarios where risk factors are taken into consideration. Theoretical and methodological research aimed at facilitating supply chain and logistics risk identification, classification and assessment is welcomed. The optimization of supply chains and logistics models taking risk as constraints or objectives is another important topic to be included in the special track. Works on defining, characterizing and analyzing the essential risks of modern supply chains such as cross-border and e-commerce supply chains are also encouraged. In addition to quality, originality, and applicability, the selection criteria for articles includes proposed methods relevant to supply chain knowledge acquisition, data analysis and synthesis advancing supply chain risk management, risk-aware supply chain optimization tested using real supply chain data, and AI technologies and methodologies for smart service applications in e-commerce, logistics management and supply chain management.
Relevant topics include, but are not limited to, the following:
- Identification and characterization of cross-border e-commerce, supply chain, logistics risks.
- AI technologies and methodologies for smart service applications in e-commerce, logistics management and supply chain management considering risks.
- Clarification of risk effects on the complexity, scalability, sustainability and adaptability of supply chain and logistics operations.