Using NLP to Enhance Supply Chain Management Systems
Journal of Engineering Research and Reports · pp. 211–219 · Published 16 Oct 2023
10.9734/jerr/2023/v25i9994Abstract
This article explores the transformative potential of Natural Language Processing (NLP) in enhancing Supply Chain Management (SCM) software. With the digital age ushering in vast amounts of unstructured data, especially customer feedback, there is a pressing need for advanced analytical tools. NLP, a subset of artificial intelligence, offers techniques such as sentiment analysis, topic modeling, and text classification to interpret this data. By integrating these techniques, businesses can gain unparalleled insights into their supply chain operations, leading to improved operational efficiency, stakeholder satisfaction, and proactive issue management. The article reviews studies across various industries, from food delivery to railways, underscoring the versatility and efficacy of NLP in diverse contexts. The findings highlight NLP's role as a game-changer in SCM, promising a more data-driven, efficient, and customer-centric supply chain landscape.
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