The artificial intelligence and machine learning in the supply chain industry
Keywords:
learning, intelligence, companies, chain industryAbstract
The authors highlight the various applications of these technologies, including demand forecasting, inventory management, transportation optimization, quality control, and supplier management. They also identify the challenges that companies face when implementing these technologies, such as data quality issues, lack of expertise, and resistance to change. Despite the challenges, the authors argue that the benefits of AI and ML in the supply chain industry are significant. These technologies can help companies optimize their operations, reduce costs, and enhance customer satisfaction. However, the authors emphasize the need for companies to develop a clear strategy for implementing AI and ML in their supply chain operations.
Key Words: The authors highlight the various applications of these technologies, including demand forecasting, inventory management, transportation optimization, quality control, and supplier management. They also identify the challenges that companies face when implementing these technologies, such as data quality issues, lack of expertise, and resistance to change. Despite the challenges, the authors argue that the benefits of AI and ML in the supply chain industry are significant. These technologies can help companies optimize their operations, reduce costs, and enhance customer satisfaction. However, the authors emphasize the need for companies to develop a clear strategy for implementing AI and ML in their supply chain operations.
References
Chen, Y., Wang, Z., & Zhang, X. (2019). The application of machine learning in supply chain management: A systematic review and future research agenda. International Journal of Production Research, 57(7), 2161-2185.
Li, Y., Wang, X., Li, Z., & Li, Y. (2021). Supply chain optimization: A review of artificial intelligence and machine learning approaches. Computers & Industrial Engineering, 152, 107065.
Modi, S. B., Mabert, V. A., & Venkataramanan, M. A. (2020). Artificial intelligence in supply chain management: A comprehensive literature review and future research directions. International Journal of Logistics Management, 31(1), 110-129.
Ngai, E. W., & Moon, K. K. (2019). Machine learning approaches for supply chain management: A comprehensive review and future directions. European Journal of Operational Research, 273(3), 1079-1104.
Sarker, S., & Lee, J. (2018). Artificial intelligence in supply chain management: A comprehensive literature review and implications for future research. International Journal of Supply Chain Management, 7(6), 231-250.
Wang, W., Li, L., Wang, Y., Li, Z., & Li, Y. (2020). Applications of artificial intelligence in supply chain management: A comprehensive review and future directions. Technological Forecasting and Social Change, 158, 120166.
Xie, Y., & Liu, Y. (2021). A review of artificial intelligence and machine learning in supply chain management: Applications, opportunities, and challenges. Journal of Cleaner Production, 311, 127747.
Downloads
Published
How to Cite
Issue
Section
License
This work is licensed under a Creative Commons Attribution 4.0 International License.
Re-users must give appropriate credit, provide a link to the license, and indicate if changes were made. You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you or your use. This license allows for redistribution, commercial and non-commercial, as long as the original work is properly credited.
