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

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Business Information Systems (BIS 2019)

Part of the book series: Lecture Notes in Business Information Processing ((LNBIP,volume 354))

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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.

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Notes

  1. 1.

    Frequent words that carry irrelevant information (i.e. pronouns, prepositions, conjunctions, etc.) [22]. In https://github.com/stopwords-iso/stopwords-de/blob/master/raw/stop-words-german.txt (accessed 09.08.2018).

  2. 2.

    Stemming is the process of removing suffixes from a term to generate word stems [27].

  3. 3.

    http://ana.cachopo.org/datasets-for-single-label-text-categorization.

  4. 4.

    http://www.cad.zju.edu.cn/home/dengcai/Data/TextData.html.

  5. 5.

    http://sites.labic.icmc.usp.br/text.

  6. 6.

    http://qwone.com/~jason/20Newsgroups/.

  7. 7.

    https://opennlp.apache.org/docs/1.8.0/manual/opennlp.html#tools.tokenizer.

  8. 8.

    https://github.com/stopwords-iso/stopwords-de/blob/master/stopwords-de.txt.

  9. 9.

    https://github.com/snowballstem.

  10. 10.

    http://snowballstem.org/algorithms/german/stemmer.html.

  11. 11.

    The distribution of the supply risk is approximately retained in training and test set.

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Author information

Authors and Affiliations

  1. Department of Computing Science, Oldenburg University, Oldenburg, Germany

    Ahmad Pajam Hassan

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  1. Ahmad Pajam Hassan
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Correspondence to Ahmad Pajam Hassan .

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Editors and Affiliations

  1. Poznań University of Economics and Business, Poznań, Poland

    Witold Abramowicz

  2. ETSI Informática, University of Seville, Seville, Spain

    Rafael Corchuelo

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Hassan, A.P. (2019). Enhancing Supply Chain Risk Management by Applying Machine Learning to Identify Risks. In: Abramowicz, W., Corchuelo, R. (eds) Business Information Systems. BIS 2019. Lecture Notes in Business Information Processing, vol 354. Springer, Cham. https://doi.org/10.1007/978-3-030-20482-2_16

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  • DOI: https://doi.org/10.1007/978-3-030-20482-2_16

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