The Role of Data Analytics in Sustainable Decision-Making in Transport Enterprises

The increasing complexity of global transportation systems and the rapid growth of data generated by Intelligent Transportation Systems (ITS) have created new challenges for transportation data management and decision-making. This study aims to systematize existing approaches to the use of ITS and data analytics in transportation and to examine their role in supporting sustainable decision-making and improving operational efficiency in transport enterprises. The study employs a qualitative research approach based on a structured review and analysis of relevant academic literature, existing ITS technologies, transportation data management practices, and available information on digital transportation systems. The reviewed approaches are comparatively examined to identify the main applications of ITS and data analytics in transportation decision-making, operational management, safety, and sustainability. The analysis indicates that ITS technologies facilitate the collection, integration, processing, and analysis of large volumes of transportation data. Existing evidence suggests that real-time information systems and data analytics can support more informed decision-making, improve operational efficiency, enhance traffic and fleet management, and contribute to safer and more sustainable transportation services. The review also demonstrates that the integration of real-time data, digital information platforms, and smart mobility solutions can reduce the limitations associated with conventional transportation management approaches. The study concludes that ITS and data analytics have an important role in supporting sustainable decision-making in transport enterprises. Based on the reviewed approaches, the wider adoption of integrated data platforms, real-time analytics, and smart mobility technologies is recommended to improve operational effectiveness, service quality, and the sustainability of transportation systems.