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Machine Learning Techniques in Supply Chain Management: An Exploratory Literature Review

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Smart Mobility and Industrial Technologies (ICATH 2022)

Part of the book series: Advances in Science, Technology & Innovation ((ASTI))

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Abstract

Supply chain processes demand the use of a technology that can handle their growing complexity. Therefore, this study aims to investigate how machine learning techniques contribute to the management of the supply chain, by analyzing the current literature. Using an exploratory literature review methodology, this study analyzes the publications available in scientific databases: Scopus, Web of Science, and Science Direct. We have found 94 references that we extracted and analyzed using three tools: Zotero, NVIVO, and SPSS. We present, in this paper, an analysis of the meta-data, then we discuss machine learning techniques used in the different departments of the company, finally we present the perspectives of our study.

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Author information

Authors and Affiliations

  1. Laboratory of Engineering Sciences, National School of Applied Sciences, Ibn Tofail University, Kenitra, Morocco

    Samia Haman, Aniss Moumen & Younes El Bouzekri El Idrissi

  2. Smartilab, EMSI, Rabat, Morocco

    Kaoutar Jenoui & Brahim Elbhiri

Authors
  1. Samia Haman
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  2. Aniss Moumen
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  3. Kaoutar Jenoui
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  4. Brahim Elbhiri
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  5. Younes El Bouzekri El Idrissi
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Corresponding author

Correspondence to Samia Haman .

Editor information

Editors and Affiliations

  1. Ecole Marocaine Des Science De L'ingénieur (EMSI), Rabat, Morocco

    Brahim El Bhiri

  2. Institut National de Statistique et d'Economie Appliquée (INSEA), Rabat-Institut, Rabat, Morocco

    Rajaa Saidi

  3. Ecole Marocaine Des Science De L'ingénieur (EMSI), Rabat, Morocco

    Mohammed Essaaidi

  4. University of North Dakota (UND), Grand Forks, ND, USA

    Naima Kaabouch

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Haman, S., Moumen, A., Jenoui, K., Elbhiri, B., El Bouzekri El Idrissi, Y. (2024). Machine Learning Techniques in Supply Chain Management: An Exploratory Literature Review. In: El Bhiri, B., Saidi, R., Essaaidi, M., Kaabouch, N. (eds) Smart Mobility and Industrial Technologies. ICATH 2022. Advances in Science, Technology & Innovation. Springer, Cham. https://doi.org/10.1007/978-3-031-46849-0_17

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