Paper Type

Complete

Abstract

Supply chain management (SCM) faces challenges such as uncertainty, volatility, and disruption. Artificial intelligence (AI) can improve SCM by enabling data-driven decision-making, automation, and optimization. However, the literature on AI in SCM is fragmented and a systematic review is lacking. This study evaluated the effectiveness of AI capabilities on supply chain performance through a systematic literature review (SLR) of empirical studies. SLR follows PRISMA guidelines and answers three research questions: (1) What are the types and amounts of AI capabilities in SCM? (2) How do AI capabilities affect supply chain performance? (3) What factors moderate or mediate the relationship between artificial intelligence and performance? SLR searches large databases for relevant articles and uses a thematic analysis approach to synthesize the data. The study explored the application of artificial intelligence in SCM, identified gaps and limitations in the literature, and provided implications and recommendations for managers.

Paper Number

1233

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Aug 16th, 12:00 AM

AI Capability and Supply Chain Performance: A Systematic Literature Review

Supply chain management (SCM) faces challenges such as uncertainty, volatility, and disruption. Artificial intelligence (AI) can improve SCM by enabling data-driven decision-making, automation, and optimization. However, the literature on AI in SCM is fragmented and a systematic review is lacking. This study evaluated the effectiveness of AI capabilities on supply chain performance through a systematic literature review (SLR) of empirical studies. SLR follows PRISMA guidelines and answers three research questions: (1) What are the types and amounts of AI capabilities in SCM? (2) How do AI capabilities affect supply chain performance? (3) What factors moderate or mediate the relationship between artificial intelligence and performance? SLR searches large databases for relevant articles and uses a thematic analysis approach to synthesize the data. The study explored the application of artificial intelligence in SCM, identified gaps and limitations in the literature, and provided implications and recommendations for managers.

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