Leveraging Artificial Intelligence for Optimization in Computer Supply Chain Management

Xinyi Sun, Yezhi Yuan (), Zezhong Bao, Yuankun Li, Bowen Li and Shengfeng Gu
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Xinyi Sun: University of York
Yezhi Yuan: University of Nova Gorica
Zezhong Bao: National University of Mongolia
Yuankun Li: Belarusian State University
Bowen Li: Belarusian State University
Shengfeng Gu: Belarusian State University

A chapter in Proceedings of the 2024 3rd International Conference on Economics, Smart Finance and Contemporary Trade (ESFCT 2024), 2024, pp 90-96 from Springer

Abstract: 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.

Keywords: Information Technology (IT); Global Competition; Operations and Supply Chain Management (SCM); Planning; Scheduling (search for similar items in EconPapers)
Date: 2024
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DOI: 10.2991/978-94-6463-548-5_12

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