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Artificial intelligence applications in supply chain: A descriptive bibliometric analysis and future research directions

机译:供应链中的人工智能应用:描述性的老毛管计量分析和未来的研究方向

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摘要

Today?s supply chains are very different from those of just a few years ago, and they continue to evolve within an extremely competitive economy. Dynamic supply chain processes require a technology that can cope with their increasing complexity. In recent years, several functional supply chain applications based on artificial intelligence (AI) have emerged, yet very few studies have addressed the applications of AI in supply chain processes. Machine learning, natural language processing, and robotics are all potential enablers of supply chain transformation. Aware of the potential advantages of AI implementation in supply chains and of the paucity of work done regarding it, we explore what researchers have done so far with respect to AI and what needs further exploration. We reviewed 136 research papers published between 1996 and 2020 from the Scopus database and provided a classification of the research material according to four critical structural dimensions (level of analytics, AI algorithms or techniques, sector or industry of application, and supply chain processes). This study is the first attempt to study the AI applications in SC from a process perspective and provides a decisional framework for adequate use of AI techniques in the different SC processes.
机译:今天的供应链与几年前的供应链截然不同,他们继续在极具竞争力的经济中发展。动态供应链流程需要一种可以应对他们越来越复杂的技术。近年来,出现了基于人工智能(AI)的几个功能供应链应用,但很少有研究已经解决了AI在供应链过程中的应用。机器学习,自然语言处理和机器人都是供应链转型的潜在推动者。意识到AI在供应链中的潜在优势和对其的工作缺乏,我们探讨了迄今为止的研究人员,以及需要进一步的探索。我们审查了1996年至2020年间的136名研究论文来自Scopus数据库,并根据四个关键结构尺寸(分析,AI算法或技术,应用程序或应用和供应链流程的水平,以及供应链流程的分析水平,提供了研究材料的分类。本研究首次尝试从过程的角度来研究SC中的AI应用,并提供了用于在不同SC过程中充分使用AI技术的果断框架。

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