Skip to main navigation menu Skip to main content Skip to site footer
Español (España) | English
Editorial
Revistas / Journals
Salud, Ciencia y Tecnología Metaverse Basic and Applied Research Data & Metadata Interdisciplinary Rehabilitation Salud, Ciencia y Tecnología - Serie de Conferencias Community and Interculturality in Dialogue Seminars in Medical Writing and Education Health Leadership and Quality of Life Gamification and Augmented Reality Southern perspective / Perspectiva austral
Home
Issue
Current Issue Previous Issues Special Issue
About
About the Journal Editorial Team Privacy Statement Digital preservation policy Contact
Submissions
Author Guidelines Peer Review Process Ethical aspects Open Access Policy and Copyright Anti-plagiarism policy Crossmark policy page
Indexing
×
Español (España) | English
Editorial

Salud, Ciencia y Tecnología Metaverse Basic and Applied Research Data & Metadata Interdisciplinary Rehabilitation Salud, Ciencia y Tecnología - Serie de Conferencias Community and Interculturality in Dialogue Seminars in Medical Writing and Education Health Leadership and Quality of Life Gamification and Augmented Reality Southern perspective / Perspectiva austral
Home

Current Issue Previous Issues Special Issue

About the Journal Editorial Team Privacy Statement Digital preservation policy Contact

Author Guidelines Peer Review Process Ethical aspects Open Access Policy and Copyright Anti-plagiarism policy Crossmark policy page
Indexing
Original
Published: 2024-07-01
DOI: https://doi.org/10.56294/dm2024395

Predictive analytics on artificial intelligence in supply chain optimization

By
Anber Abraheem Shlash Mohammad ,
Anber Abraheem Shlash Mohammad

Research follower, INTI International University, 71800 Negeri Sembilan, Malaysia

Search this author on:

PubMed | Google Scholar
Iyad A.A Khanfar ,
Iyad A.A Khanfar

Business Administration Department, College of Business and Economics, Qassim University, Qassim – Saudi Arabia

Search this author on:

PubMed | Google Scholar
Badrea Al Oraini ,
Badrea Al Oraini

Zarqa University, Jordan

Search this author on:

PubMed | Google Scholar
Asokan Vasudevan ,
Asokan Vasudevan

Faculty of Business and Communications, INTI International University, 71800 Negeri Sembilan, Malaysia

Search this author on:

PubMed | Google Scholar
Suleiman Ibrahim Mohammad ,
Suleiman Ibrahim Mohammad

Research follower, INTI International University, 71800 Negeri Sembilan, Malaysia

Search this author on:

PubMed | Google Scholar
Zhou Fei ,
Zhou Fei

Shinawatra University, 99 Moo 10, Bangtoey, Samkhok, Pathum Thani, Thailand 12160

Search this author on:

PubMed | Google Scholar

Abstract

AI-powered predictive analytics is among the most important ways of optimizing supply chains. This paper on AI-powered predictive analytics will address improving the competitiveness and effectiveness of supply chain operations. Nevertheless, current methods are not always scalable or adaptable to complex supply networks and changing market environments. Therefore, this paper posits that Supply Chain Optimization using Artificial Intelligence (SCO-AI) systems can help with these concerns. SCO-AI employs real-time data analysis and advanced machine learning algorithms which results to reduced response time, enhanced logistics route optimization, improved demand planning as well as real-time inventory control. Thus, the idea herein suggested fits smoothly into existing supply chain frameworks for data-driven decisions that make companies remain agile in ever-changing market dynamics. SCO-AI implementation has seen significant improvements in inventory turnover rate, rates of on-time delivery as well as overall supply chain costs. In this period of high business turbulence, such kind of research builds up the robustness of a given supply chain wh

Keywords:

Predictive Analytics,
Artificial Intelligence,
Supply Chain Optimization,

How to Cite

1.
Shlash Mohammad AA, A Khanfar IA, Al Oraini B, Vasudevan A, Mohammad SI, Fei Z. Predictive analytics on artificial intelligence in supply chain optimization. Data and Metadata [Internet]. 2024 Jul. 1 [cited 2024 Jul. 6];3:395. Available from: https://dm.saludcyt.ar/index.php/dm/article/view/395

Copyright Notice

The article is distributed under the Creative Commons Attribution 4.0 License. Unless otherwise stated, associated published material is distributed under the same licence.

Article metrics

Google scholar: See link

Metrics

Metrics Loading ...

Vol. 3 (2024)
See full issue

The statements, opinions and data contained in the journal are solely those of the individual authors and contributors and not of the publisher and the editor(s). We stay neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Similar Articles

You may also start an advanced similarity search for this article.