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DOI: 10.33226/1231-2037.2022.6.4
JEL: C45, C53, C55, D81, R41

The use of Big Data technology to predict the risk of delay in supply chain

In recent years, more and more attention has been paid to the use of Big data technology, machine learning and AI. Enterprises strive for a competitive advantage through the appropriate use of data analytics. Big data can be used in many different industries, e.g. in the transport or medical industry, and potentially in all of them. A huge problem in the supply chain is the risk of delay, which may be influenced by many factors, including illegible label on the package, lack of warehouse workers or congestion in cities. The article focuses on the use of Big Data technology to detect the risk of delays in the supply chains of medicinal products. Its purpose is to present the concept of Big Data, Big Data architecture for the drug supply and to present the results of research related to the prediction of the risk of delays in its implementation in a real enterprise. The set goal determined the choice of the following research methods: analysis of literature and the use of modeling, which allowed to design and implement the architecture for the drug supply chain to collect data in the studied enterprise. The last part of the article presents a logistic regression model for predicting delays in the supply chain of medicinal products. The research established that the model has a high predictive ability.

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Keywords: Big Data; supply chain management; risk management

References

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