Artificial intelligence and prescriptive analytics for supply chain resilience: a systematic literature review and research agenda

Abstract

Artificial Intelligence (AI) and prescriptive analytics are increasingly being reported as having transformative powers to enable resilient supply chains (SC). Despite such a benefit, and the increase in popularity of AI and analytics in general, research is largely fragmented into streams based on different types of AI technologies across several SC contexts and through varying disciplinary perspectives. In response, we curate and synthesise this fragmented body of knowledge by conducting a systematic literature review of AI research in supply chains that have been published in 3* and 4* Chartered Association of Business Schools (CABS) ranked journals between 2000 and 2023. The search strategy retrieved 5, 293 studies, of which 76 were identified as primary papers relevant to this study. The study contributes to the accumulative building of knowledge by extending theoretical discourse about the specificities of AI for prescriptive analytics to enable SC resilience. This study proposes a strategic AI resilience framework to support SC decision-makers enhance the use and value of prescriptive analytics as an enabler to developing resilient SC. We make the call to action for an orchestrated effort within and between academic disciplines and organisations that are guided by a research agenda to guide future research initiatives.