DIGITAL TRANSFORMATION OF LOGISTICS INFRASTRUCTURE IN THE CONTEXT OF SMART LOGISTICS IMPLEMENTATION
Abstract
The article examines contemporary trends and strategic opportunities in the digital transformation of logistics infrastructure, focusing on the implementation of Smart Logistics systems. It is demonstrated that integrating advanced digital tools, including Internet of Things (IoT) technologies, predictive analytics, AI-driven decision-making platforms, and intelligent warehouse management systems, is essential for modernizing logistics operations, enabling real-time monitoring, process automation, and enhanced operational flexibility. Smart Logistics solutions contribute to efficient resource allocation, optimization of supply chain performance, improved route planning and inventory management, and faster response to fluctuating market demand. The study identifies key challenges in adopting these technologies, including technical limitations, workforce skill gaps, cybersecurity risks, and compliance with regulatory standards. Overcoming these obstacles requires developing digital competencies, establishing secure and interoperable infrastructure, implementing standardized data protocols, and aligning organizational processes with digital transformation strategies. Leading trends include the increased use of autonomous vehicles and drones, advanced real-time tracking systems, predictive maintenance, cloud-based platforms, and AI-assisted scheduling for logistics operations. The research further emphasizes that investing in employee digital skills, fostering innovation-oriented organizational culture, and combining AI, Big Data analytics, and IoT ensures cost reduction, strengthens competitiveness, improves resilience, and enhances agility of logistics networks. Prospects for future studies involve designing strategic frameworks for integrating data-driven management approaches and Smart Logistics principles into enterprise practices, thus promoting sustainable growth, continuous optimization of logistics processes, and more effective and evidence-based managerial decision-making in dynamically evolving supply chain environments.
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