Enabling Blockchain Based SCM Systems with a Real Time Event Monitoring Function for Preemptive Risk Management

Abstract

The risk of supply chain disruption is usually related to daily disturbances in supply chain operations (e.g., demand fluctuations) and some emergency risks, such as earthquakes and epidemic outbreaks. During a crisis, companies need agility to quickly find new suppliers and open auxiliary sales channels to meet customer needs and remain competitive. However, identifying “event” is one of the most difficult challenges of current decision support systems. If the system encounters an emergency, it is usually unable to promptly notify users of the warning to avoid risks. A sensible solution is to incorporate the real-time event-monitoring system into SCM (i.e., supply chain management) in order to share emergency information in the early stage for preemptive management in the supply chain. On the other hand, in order to process confidential supply chain data with other members, the SCM infrastructure requires secure data sharing. The blockchain-based SCM system can improve the transparency of traceability to ensure that the supply chain system provides high-quality products and protects data privacy and security. The view is taken; therefore, in this work, we combined a method of real-time event detection using collected Twitter data and blockchain technology for event monitoring to improve the visibility of the supply chain system and take preemptive measures for risk avoidance. The experiments show some interesting results and potentials for future work in the field of the agile supply chain.

A critical analysis of the integration of blockchain and artificial intelligence for supply chain

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A Systematic Literature Review of Blockchain-Enabled Supply Chain Traceability Implementations

“…Other authors use blockchain technology as leverage for developing sound SC risk management approaches. For instance, in [39] the authors combine blockchain and a real-time event-monitoring system to track and disseminate emergent knowledge for preemptive management purposes. To improve visibility, the authors in [40] propose a blockchain-based SC network model.…”

Using deep learning to interpolate the missing data in time-series for credit risks along supply chain

“…Recently, a large body of studies has shown that the data along the supply chain can help protect the upstream and downstream companies in case there would be risk spillovers along the supply chain, thereby adversely affecting the target company (Wu et al, 2022). For instance, Osadchiy et al (2016) assert that credit risk can propagate in supply chain networks and exacerbate supplier production losses; supply chain data are applied to monitoring sudden inventory, sales fluctuations, and thus optimizing the structure of the supply chain (Ni et al, 2022); and also by monitoring data of the supply chain, Lee et al (2021) succeed in timely predicting the credit risk, all of which indicate that the data of the supply chain can serve as a complementary source for CRP.…”