Risk management in cyber-physical distribution center for e-commerce cross-border logistics

Abstract

In the past two decades, there has been a significant surge in cross-border e-commerce, leading to a higher demand for operational efficiency in cross-border e-commerce distribution centers. However, e-commerce distribution centers encounter more complex orders than traditional warehouses due to the greater diversity of products and faster delivery requirements. Furthermore, cross-border e-commerce orders exhibit unique characteristics, such as irregular arrival patterns, a large item count, and high service level expectations for each picking. Consequently, managing these issues poses a significant challenge, and many businesses employ inventory classification schemes, such as stock-keeping units (SKUs), to optimize inventory organization and management. To tackle these challenges, e-commerce order picking and sorting have been modernized with technology, such as the use of the Internet of Things (IoT) in ecommerce warehouses to provide order details and location information for SKUs.. This study introduces a research framework for exploring real-time planning, scheduling, and execution control in cross-border e-commerce distribution centers. Four typical scenarios are analyzed. The first scenario proposes a multi-layered cyber-physical system-enabled cloud platform to virtualize logistics assets, which allows for real-time control, execution, and reconfiguration. By leveraging this platform, the efficiency and effectiveness of cross-border e-commerce logistics can be significantly improved.". The second scenario proposes a hybrid Entropy-TOPSIS-Fuzzy Bayesian network framework to evaluate risk and provide suggestions for cross-border e-commerce supply chain management. The framework identifies multiple criteria and uses a hybrid approach to weigh and rank all risks. The third scenario proposes a group decision-making model that incorporates individual preferences to address the multicriteria ABC inventory classification problem. The study analyzes individual preferences among classification criteria and explores preferential differences and priorities. Finally, the fourth scenario verifies and validates the proposed platform technologies through a case study. The pilot implementation examines how the system facilitates auction activities and decision-making procedures in a real-life setting. This research examines real-time planning, scheduling, inventory classification management, and risk management, and develops operation mechanisms and platform technologies accordingly. This comprehensive study of cross-border e-commerce distribution centers is valuable for researchers and practitioners interested in examining logistics factors and their impact on operational performance in e-commerce.