Proceedings of the 2024 3rd International Conference on Economics, Smart Finance and Contemporary Trade (ESFCT 2024)

<Previous Article In Volume
Next Article In Volume>

Leveraging Artificial Intelligence for Optimization in Computer Supply Chain Management

Authors
Xinyi Sun1, Yezhi Yuan2, *, Zezhong Bao3, Yuankun Li4, Bowen Li4, Shengfeng Gu4
1University of York, M3J 1P3, York, England
2University of Nova Gorica, 999151, Nova Gorica, Slovenia
3National University of Mongolia, 999097, Ulaanbaatar, Mongolia
4Belarusian State University, 220030, Minsk, Belarus
*Corresponding author. Email: yuanyezhiknight@foxmail.com
Corresponding Author
Yezhi Yuan
Available Online 21 October 2024.
DOI
10.2991/978-94-6463-548-5_12How to use a DOI?
Keywords
Information Technology (IT); Global Competition; Operations and Supply Chain Management (SCM); Planning; Scheduling
Abstract

As information technology continues to advance and evolve, the landscape of global competition has become increasingly fierce. Numerous organizations anticipate a significant transformation in the realm of operations and supply chain management (SCM), encompassing aspects such as planning, scheduling, optimization, and transportation, all under the influence of artificial intelligence (AI). There is a growing interest in leveraging machine learning, AI, and other smart technologies within SCM frameworks. Against this backdrop, the present study offers a comprehensive examination of AI and SCM concepts. It delves into a timely and critical evaluation of AI-powered supply chain research and practical implementations. Through this exploratory investigation, the study scrutinizes the emerging AI-centric business models of various case studies. It assesses their pertinent AI solutions and the consequent value these bring to the organizations. Consequently, this research highlights multiple domains where AI application can generate value within the supply chain. Furthermore, it suggests a methodology for crafting business models tailored to AI applications in supply chain settings.

Copyright
© 2024 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Download article (PDF)

<Previous Article In Volume
Next Article In Volume>
Volume Title
Proceedings of the 2024 3rd International Conference on Economics, Smart Finance and Contemporary Trade (ESFCT 2024)
Series
Advances in Economics, Business and Management Research
Publication Date
21 October 2024
ISBN
978-94-6463-548-5
ISSN
2352-5428
DOI
10.2991/978-94-6463-548-5_12How to use a DOI?
Copyright
© 2024 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Cite this article

risenwbib
TY  - CONF
AU  - Xinyi Sun
AU  - Yezhi Yuan
AU  - Zezhong Bao
AU  - Yuankun Li
AU  - Bowen Li
AU  - Shengfeng Gu
PY  - 2024
DA  - 2024/10/21
TI  - Leveraging Artificial Intelligence for Optimization in Computer Supply Chain Management
BT  - Proceedings of the 2024 3rd International Conference on Economics, Smart Finance and Contemporary Trade (ESFCT 2024)
PB  - Atlantis Press
SP  - 90
EP  - 96
SN  - 2352-5428
UR  - https://doi.org/10.2991/978-94-6463-548-5_12
DO  - 10.2991/978-94-6463-548-5_12
ID  - Sun2024
ER  -