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Enhancing Supply Chain Risk Management by Applying Machine Learning to Identify Risks

  • Ahmad Pajam HassanEmail author
Conference paper
Part of the Lecture Notes in Business Information Processing book series (LNBIP, volume 354)

Abstract

Supply chain risks negatively affect the success of an OEM in automotive industry. Finding relevant information for supply chain risk management (SCRM) is a critical task. This investigation utilizes machine learning to find risk within textual documents. It contributes to the supply chain management (SCM) by designing (i) a conceptual model for supply risk identification in textual data. This addresses the requirement to see the direct connection between data analytics and SCM. (ii) An experiment in which a prototype is evaluated contributes the requirement to have more empirical insight in the interdisciplinary field of data analytics in SCRM.

Keywords

Supply chain risk management NLP Data analytics Machine learning Risk identification 

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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.Department of Computing ScienceOldenburg UniversityOldenburgGermany

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