## 2 Related Work
Additionally, [PERSON] proposed a notion of a digital supply chain twin, which represents network states for any given moment in real-time. A combination of model-based and data-driven approaches allows uncovering the interrelations of risk data [32]. [PERSON] verified the impact of the Big Data Analytics (BDA) mediation agency on supply chain disruptions and the company's ability to develop risk resistance when faced with supply chain disruptions. The utilization of BDA enables the company to effectively develop its ability to mitigate supply chain risks [33]. However, the crisis of supply chain disruption is not limited to the occurrence of major disasters, strikes, or severe legal disputes that will cause disruption to the supply chain [34]. [PERSON] addressed the problem of supply chain disruption and said that risk exists in virtually all firms. They employed case study data from seven purchasing organizations to explore various types of supply risks emanating from each supplier's factors and market characteristics [35]. When a supply chain disruption event occurs, the managers of each company play an important role. [PERSON] proposed three pure reactive strategies and two dynamic reactive policies for managing supply disruption. They evaluated the reactive strategies by considering the expected profits and percentage of customers during the supply disruption. The pure strategies that the manufacturer adopts will influence the demand [36]. Many unfortunate incidents such as terrorist attacks, changes in customer behavior and economic crises have made the global supply chain a vulnerable target. Among the world's 500 richest companies, only 5-25% can handle a crisis by disruptions in the supply chain [37]. Traditional supply chain management schemes reveal limitations in resources for efficient risk management. [PERSON] proposed a novel distributed ledger system for the supply chain and implemented this blockchain system on top of Hyperledger Sawtooth. The simulation-based evaluation demonstrates the feasibility of the system [38]. Regarding the issue of supply chain risk, [PERSON] conceptualized the novel blockchain technology and determined the specific application areas of blockchain technology from the perspective of risk management. Additionally, they discussed the way to leverage blockchain technology to enhance supply chain resilience in times of increased risks and uncertainty [39]. [PERSON] discussed the mean-variance (MV) method applied to global supply chain risk in air logistics and applied blockchain technology to facilitate the implementation of mean-variance risk analysis for global supply chain operations [40]. [PERSON] mentioned that information exchange among trading partners is an important factor in successful supply chain management [41]. However, information sharing is not without risks. When companies lack trust and use shared information for improper purposes, it is easy to increase the hidden cost of shared information [42]. Therefore, the mutual integration of blockchain technology can solve the problems of transparency, security, and traceability of the supply chain itself [43; 44; 45]. [PERSON] developed an effective team decision-making method by focusing on the psychological characteristics and different viewpoints considered by decision makers when selecting blockchain technology. This method combines the hybrid group decision-making method with hesitation fuzzy sets and regret theory [46]. Regarding the issue of traceability, [PERSON] has developed a blockchain-based food supply chain (FSC) traceability model, which implements a set of functions through three smart contracts to provide an end-to-end traceability flow, from raw materials acquisition to end-customer product delivery [47]. She presented a blockchain trust model (BTM) for malicious node detection in wireless sensor networks. This model used blockchain smart contracts to detect malicious nodes in 3D space.