The Impact of Artificial Intelligence (AI)-Enabled Collaborative Approach: Achieving Sustainable Supply Chain Performance

Abstract

This study investigates the role of artificial intelligence (AI) in enhancing sustainability and efficiency within the fragmented supply chain of the tea industry. Small-scale tea gardens often face logistical inefficiencies, inconsistent quality control, and economic constraints, limiting their competitiveness. This research bridges the gap in literature by proposing an AI-enabled collaborative supply chain model tailored for small-scale tea gardens. Using a mixed-method research design incorporating extensive field studies and structural equation modeling (SEM), this study validates the model's effectiveness. Findings indicate that AI can significantly improve coordination, predictive analytics, and automation in supply chain processes, enhancing operational efficiency, profitability, and sustainability. Additionally, AI-driven collaboration fosters more transparent and data-driven decision-making among supply chain partners, reducing dependency on intermediaries. This study contributes to the theory of collaborative advantage by demonstrating AI's role in fostering cooperative synergies in agricultural supply chains. The proposed AI-enabled framework offers a scalable model for broader application in agribusiness, presenting significant policy and managerial implications.