Enhancing Decision-Making and Supply Chain Agility through Artificial Intelligence

dc.contributor.authorMahama U.F.A.
dc.contributor.authorBoison D.K.
dc.contributor.authorDoumbia M.O.
dc.contributor.authorAntwi-Boampong A.
dc.date.accessioned2025-03-04T04:25:15Z
dc.date.accessioned2025-03-04T06:21:24Z
dc.date.issued2024
dc.description.abstractThis study evaluates AI's effectiveness in boosting real-time decision-making and supply chain agility in West African ports. Utilizing Structural Equation Modeling (SEM), data from 250 supply chain experts across several countries, including Ghana and Nigeria, were analyzed. Results indicate significant enhancements in supply chain agility, particularly through improved data processing speed, system integration, prediction accuracy, and user interface quality, with the latter having the most substantial impact. The study underscores the importance of user-friendly AI systems, supported by Dynamic Capabilities Theory, which facilitates organizational adaptability to market changes. Recommendations focus on developing AI systems with robust user interfaces and ensuring seamless integration with existing IT infrastructures. This research contributes to the literature by empirically demonstrating AI's role in improving operational adaptability and filling theoretical gaps, with a unique regional focus and methodological approach. � Umar Farouk Aliu Mahama et al., 2024. Published with license by Koninklijke Brill BV.
dc.identifier.issn15691500
dc.identifier.uri10.1163/15691497-12341692
dc.identifier.urihttp://162.250.124.58:4000/handle/123456789/70
dc.language.isoen
dc.publisherBrill Academic Publishers
dc.subjectartificial intelligence in supply chain
dc.subjectdynamic capabilities theory
dc.subjectreal-time decision-making
dc.subjectsupply chain agility
dc.subjectWest African ports
dc.titleEnhancing Decision-Making and Supply Chain Agility through Artificial Intelligence
dc.typeArticle

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