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                <text>This study examines the role of artificial intelligence (AI) in enhancing supply chain performance through improved supplier collaboration in West Africa. It explores how AI technologies optimize supplier interactions and overall supply chain efficiency, integrating Transaction Cost Economics (TCE) and Resource-Based View (RBV) theories. TCE highlights AI's ability to reduce transaction costs and uncertainties, while RBV emphasizes AI's role in resource allocation and logistics optimization. A quantitative approach with a correlational research design is used, complemented by qualitative insights from interviews and surveys. The sample includes 250 suppliers involved in collaborative supply chain initiatives utilizing AI technologies. Structural Equation Modeling (SEM) analyzes the data, revealing significant relationships between AI-driven communication tools, automation in collaboration processes, real-time data sharing, supplier network integration, and supply chain performance. The findings underscore AI's substantial impact on supply chain performance metrics. AI-driven communication tools, automation, and real-time data sharing capabilities are significant predictors of supply chain performance. Supplier network integration shows a strong positive relationship with supply chain performance, indicating its critical role in enhancing efficiency. Recommendations include adopting AI-driven communication tools and automation to streamline supplier interactions and optimize operations. Investing in real-time data sharing capabilities and fostering supplier network integration is essential for sustainable supply chain improvements. This study …</text>
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