R. Kelly Rainer Jr., Robert Glenn Richey Jr., Soumyadeb Chowdhury
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引用次数: 0
Abstract
The Journal of Business Logistics has been the top location for publishing logistics and supply chain-related technological research for over forty years. With digital transformation, reshoring of manufacturing, labor shortages, decreasing birth rates, and aging workforces, companies are increasingly adopting artificial intelligence-supported robotics to increase the ability of supply chains to react quickly and effectively to changes in customer demand, market conditions, or disruptions. This paper analyzes the use of hardware robots across the logistics fulfillment process. The study addresses the evolution of robotic training from explicit programming to machine learning and continues with a detailed discussion of generative machine learning. We then provide an overview of key hardware robots driven by generative machine learning models that are used in the fulfillment process. The paper examines the challenges that robot adoption presents to organizations and concludes with explicit directions for further research using the Theory of Resource Orchestration.
期刊介绍:
Supply chain management and logistics processes play a crucial role in the success of businesses, both in terms of operations, strategy, and finances. To gain a deep understanding of these processes, it is essential to explore academic literature such as The Journal of Business Logistics. This journal serves as a scholarly platform for sharing original ideas, research findings, and effective strategies in the field of logistics and supply chain management. By providing innovative insights and research-driven knowledge, it equips organizations with the necessary tools to navigate the ever-changing business environment.