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Machine Impact in Supply Chain Management

Authors: Dr. Dena Bateh;

Machine Impact in Supply Chain Management

Abstract

This paper is an analysis on the impact machine learning, Artificial Intelligence, and robotics has on the supply chain management. The analysis covers the basis of AI in the SCM mechanisms while defining it from the ground up. Later on, to shed a true light on supply first the paper zooms in on the effects of machines in marketing. From what particular methodologies are deployed in today’s environment extending all the way to its anticipated outcomes. As the reader progresses he/she will find valuable studies on the main segments of machine learning within the supply chain itself. Certain novelties and innovations are scrutinized regarding SCM alongside these studies. These innovations are exemplified by certain cases presented in Part 3. The penultimate section briefly examines the possible drawbacks of the surge in machine application in SCM. The final section compiles the ideas presented in the paper as a whole and gives a glimpse of an estimate for the near future.

{"references": ["Vaillancourt, S. (2018, October 02). AI In Supply Chain Management: It's Only As Good As Your Data. Retrieved 2019, from", "Supply And Demand Quotes (17 quotes). (n.d.). Retrieved March 31, 2019, from", "Columbus, L. (2018, February 27). 10 Ways Machine Learning Is Revolutionizing Marketing. Retrieved March 31, 2019, from", "Community, K. R. (2017, October 26). 6 Applications of Artificial Intelligence for your Supply Chain. Retrieved March 31, 2019, from", "Banker, S. (2019, January 08). 20 Things To Know About Artificial Intelligence For Supply Chain Management. Retrieved March 31, 2019, from", "Columbus, L. (2018, June 21). 10 Ways Machine Learning Is Revolutionizing Supply Chain Management. Retrieved March 30, 2019, from"]}

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Keywords

Artificial Intelligence, Machine Learning, Supply Chain Management, Artificial Intelligence,, Supply Chain Management, Machine Learning,

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This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
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This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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