Supply chain decision-making using artificial intelligence and data analytics

Akanbi, Lukman A.; Adenuga, Kayode I.; Owolabi, Hakeem

Abstract

This chapter examines the use of artificial intelligence, data analytics and other digital technologies in the management of the supply chain decision-making. The study highlights the challenges faced by supply chain managers and how the application of AI and data analytics can help in making better and more informed decisions with respect to sustainability. Data analytics, AI techniques, such as machine learning, natural language processing and other digital technologies that include Internet of Things, Robotics and Cloud computing and their applications to different areas of supply chain management, such as demand forecasting, inventory management and logistics optimisation are discussed. Some of the challenges (initial cost of physical and cloud resources, change management, ethical and legal-related issues) that the supply chain managers need to put into consideration when adopting these technologies are also presented. The chapter concludes that continuous data collection and storage across all the stakeholders in the supply chain must be ensured to enable transparent and efficient use of AI algorithms to support quick and timely supply chain decision-making.

• Online Publication Date: Oct 1, 2023
• Publication Date: 2023
• Deposit Date: Nov 13, 2023
• Publisher: Springer
• Pages: 25-34
• Series Title: Environmental Footprints and Eco-design of Products and Processes
• Book Title: Industry 4.0 Technologies: Sustainable Manufacturing Supply Chains
• ISBN: 9789819948185
• DOI: https://doi.org/10.1007/978-981-99-4819-2_2
• Public URL: https://uwe-repository.worktribe.com/output/11385253
• Additional Information: First Online: 1 October 2023