Year: 2024
Type: article
Abstract: The article is dedicated to examining the challenges and opportunities faced by trucking companies in the context of logistics digitalization.The aim of the study is to analyze the challenges and opportunities encountered by trucking companies in logistics digitalization, as well as to identify key trends in logistics process management and the prospects for industry development through the use of artificial intelligence.The study employed general scientific methods of cognition, such as analysis, synthesis, induction, deduction, and modeling.The results indicate that modern ERP systems for tracking in the USA have become critically important for effective logistics operations management, significantly contributing to the industry's active development.The implementation of these systems facilitates the automation of route planning, real-time cargo monitoring, logistics cost optimization, document management, and regulatory compliance.The research also found that the main trends in trucking business management are related to the adoption of cloud platforms for data integration and exchange, the use of blockchain to ensure security and transparency, the application of drones for more efficient last-mile delivery, the integration of IoT and 5G for real-time cargo monitoring, and the use of artificial intelligence for risk prediction and minimization.These innovations significantly improve supply chain management, enhance customer satisfaction, and help companies maintain competitiveness in the modern market.The study shows that the trucking business faces numerous challenges, including the complexity of data integration, delay prediction, real-time monitoring, and the need to automate routine processes.The use of artificial intelligence effectively addresses these issues through data integration from various sources, predictive analytics, exception automation, and continuous process improvement.
Source: Věda a perspektivy
Author: Jamshid Bozorov
Language: English
Subfield: Industrial and Manufacturing Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: diamond
OpenAlex ID: W4402977283