Managing and predicting supply chain risks with machine learning and AI
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School of Business |
Bachelor's thesis
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Date
2024
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Major/Subject
Mcode
Degree programme
Tieto- ja palvelujohtaminen
Language
en
Pages
20+4
Series
Abstract
This thesis investigates the applications of machine learning and artificial intelligence in managing and predicting risks in supply chain networks. The thesis investigates the common supply chain risks and the elements of supply chain resilience. The thesis explores some of the flaws in traditional risk management and looks into the transformation process to machine learning-based methods, that strengthen supply chain resilience and efficiency. The thesis also explores the significance of real-time risk management, and machine learning algorithms’ ability to predict risks in supply chains. This thesis conducts a literature review from scientific articles and journals, combines some of the findings and makes new conclusions. Older and newer studies are combined to find the right balance between proven theory and applications that are used by businesses around the world.Description
Thesis advisor
Kim, SeongtaeKeywords
artificial intellegence, machine learning, risk management, risk prediction