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Machine Learning for Proactive Supply Chain Risk Management: Predicting Delays and Enhancing Operational Efficiency Cover

Machine Learning for Proactive Supply Chain Risk Management: Predicting Delays and Enhancing Operational Efficiency

Management Systems in Production Engineering
Volume 32 (2024): Issue 3 (August 2024)
By: Nisrine Rezki and  Mohamed Mansouri  
Open Access
|Sep 2024

Authors

Nisrine Rezki

n.rezki@uhp.ac.ma

National School of Applied Sciences Berrechid, Hassan First University, Morocco

Mohamed Mansouri

mohamed1969@yahoo.com

National School of Applied Sciences Berrechid, Hassan First University, Morocco
DOI: https://doi.org/10.2478/mspe-2024-0033 | Journal eISSN: 2450-5781 | Journal ISSN: 2299-0461
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Language: English
Page range: 345 - 356
Submitted on: Mar 1, 2024
|
Accepted on: Jul 1, 2024
|
Published on: Sep 5, 2024
Published by: STE Group sp. z.o.o.
In partnership with: Paradigm Publishing Services
Publication frequency: 4 issues per year
Keywords:
SC risk management,
order delay,
machine learning,
SC disruption,
supplier performance
Related subjects:
Engineering,
Mechanical engineering,
Tools and methods,
Production technology,
Process engineering and industrial engineering,
Business and economics,
Business management,
Management accounting, financial controlling, cost calculation, investment

© 2024 Nisrine Rezki, Mohamed Mansouri, published by STE Group sp. z.o.o.
This work is licensed under the Creative Commons Attribution 4.0 License.

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