Integrating Sustainable Practices and Advanced Technologies for Optimized Supply Chain Management: A Multi-Dimensional Analysis

Abstract

In contemporary global markets, the complexity of supply chains demands strategic integration of sustainability, technological innovation, and operational efficiency. This study explores the convergence of circular economy principles, Industry 4.0 technologies, and advanced logistics optimization to achieve sustainable supply chain management. Drawing on dynamic capability theory, this research examines how enterprises leverage digital transformation, predictive analytics, and big data to enhance agility, reduce environmental impact, and optimize operational performance. The study synthesizes insights from multi-echelon inventory management, last-mile logistics, just-in-time practices, and green supply chain management, highlighting both theoretical and practical implications for global enterprises. The findings suggest that integrating machine learning, predictive analytics, and sustainable resource management can significantly improve supply chain resilience, cost efficiency, and corporate sustainability. Furthermore, the research identifies challenges associated with implementation, including technological readiness, organizational culture, and regulatory compliance, offering recommendations for future research and managerial practice. The study emphasizes a holistic perspective that combines economic, environmental, and operational dimensions to foster robust, adaptable, and sustainable supply chains.