Artificial Intelligence for Supply Chain Management (SCM): A Thematic Literature Review

Artificial intelligence (AI) is rapidly diffusing and becoming increasingly popular in the business world, as the most vital driving force to transform the business process in recent years. The applications of AI now are impacting all aspects of business operations, which also include Supply Chain Management (SCM). This research examines and discusses the current AI technologies used in logistics and SCM, including AI methods like Machine Learning (ML) and Advanced Data Analytics. We have conducted comprehensive research from literature research on available AI-based industrial applications today and explored some significant AI challenges for the SCM in business and related careers. The discussions cover AI's primary functions, including supply chain configuration, agility, demand forecasting, inventory control, scheduling, and solving SCM logistics issues. To sum up the discussions, we provided managerial implication suggestions for SCM professionals and researchers.

Authors

Publication Details

Journal
International Journal of Business & Management Studies
Published
2024-11-13
DOI
https://doi.org/10.56734/ijbms.v5n11a2
Primary Topic
Big Data and Business Intelligence
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Artificial Intelligence for Supply Chain Management (SCM): A Thematic Literature Review

Leong Chan, Christopher M. Lee, Pei Zhang, Rao Kowtha
International Journal of Business & Management Studies
Big Data and Business Intelligence
article

Artificial Intelligence for Supply Chain Management (SCM): A Thematic Literature Review

Leong Chan, Christopher M. Lee, Pei Zhang, Rao Kowtha
article en

Abstract

Artificial intelligence (AI) is rapidly diffusing and becoming increasingly popular in the business world, as the most vital driving force to transform the business process in recent years. The applications of AI now are impacting all aspects of business operations, which also include Supply Chain Management (SCM). This research examines and discusses the current AI technologies used in logistics and SCM, including AI methods like Machine Learning (ML) and Advanced Data Analytics. We have conducted comprehensive research from literature research on available AI-based industrial applications today and explored some significant AI challenges for the SCM in business and related careers. The discussions cover AI's primary functions, including supply chain configuration, agility, demand forecasting, inventory control, scheduling, and solving SCM logistics issues. To sum up the discussions, we provided managerial implication suggestions for SCM professionals and researchers.

International Journal of Business & Management StudiesVol. 05(11)
Industry, innovation and infrastructure
Openalex Percentile: Top 69%
Big Data and Business Intelligence
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.