Artificial intelligence applied to supply chain operations management: a systematic literature review
Guilherme Dayrell Mendonça and
Orlando Fontes Lima Junior
International Journal of Logistics Systems and Management, 2023, vol. 45, issue 1, 1-30
Abstract:
Artificial intelligence (AI) has been a key driver to reduce operational uncertainty and improve performance in supply chain management. Due to the advent of new data gathering technologies (IoT) and greater storage capacity, big data analytics (BDA) is rapidly growing as one of the main fields within AI research. We examined a representative sample of AI works applied to SCM from 2000 to 2020 and analysed them considering the main areas of the SCOR model framework of operations. The systematic literature review was based on a meta-synthesis methodology. The main research questions addressed were: 1) What are the main research methodologies used in AI SCM literature? 2) In what areas of SCM operations is AI (including BDA) mostly applied? 3) What are the most used AI models? The discussion addressing these three questions reveals a number of research gaps, which leads to future research directions.
Keywords: artificial intelligence; supply chain management; logistics; data mining; big data analytics; BDA; machine learning; supply chain operations reference; SCOR model. (search for similar items in EconPapers)
Date: 2023
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Persistent link: https://EconPapers.repec.org/RePEc:ids:ijlsma:v:45:y:2023:i:1:p:1-30
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