International Journal of Empirical Research Methods

ISSN NO : 2995-6110

The International Journal of Empirical Research Methods is dedicated to promoting and advancing empirical research methodologies across various disciplines. This journal aims to provide a platform for researchers, scholars, educators, and practitioners to share insights, methodologies, and findings that contribute to the improvement of empirical research practices and the enhancement of evidence-based decision-making.

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ARTIFICIAL INTELLIGENCE AND MACHINE LEARNING FOR SUPPLY CHAIN RESILIENCE

1 Arab Academy For Science, Technology & Maritime Transport, Alexandria,,Egypt

Volume 1

Issue 1

Page: [23 - 28]

Published Online: October 31, 2023

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  • Abstract

    This Research Paper Offers A Thorough Examination Of The Use Of Artificial-Intelligence & Machine-Learning In Sustainable Supply Chain Management . This Paper Evaluates The Existing Usage, Advantages, Problems, And Future Prospects Of AI & ML Within The Supply Chain Operations By Analyzing The Available Literature. The Findings Emphasize The Potential Of Artificial-Intelligence & Machine-Learning Technology To Improve Decision-Making Processes, Optimize Resource Allocation, Increase Supply Chain Visibility, And Promote Sustainable Practices. The Report Underlines That, While AI & ML Provide Tremendous Benefits, Some Difficulties Must Be Solved Before They Can Be Successfully Implemented. These Include Assuring Data Quality, Selecting Suitable Algorithms, Dealing With Interpretability Issues, And Dealing With Ethical Problems.

    Keywords: Artificial Intelligence Machine Learning Sustainable Supply Chain Management

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