Recent advancements in digitalization have transformed the logistics sector by introducing in-novative solutions that enhance efficiency, sustainability, and decision-making. In intermodal freight transport, the adoption of digital technologies offers significant potential to optimize operations, reduce costs, and improve environmental performance. However, prioritizing these technologies is crucial for ensuring strategic investments and maximizing their impact. This study proposes a hybrid multi-criteria decision-making (MCDM) framework that integrates Cri-teria Importance Through Intercriteria Correlation (CRITIC) and Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) within a Picture Fuzzy environment to evaluate and rank digital technology applications in intermodal freight transport. The findings indicate that “Artificial Intelligence (AI) for Optimization” is the most critical digital technology, followed by “Cloud Computing and Big Data Analytics” and “Internet of Things (IoT) for Asset Tracking”. Additionally, Operational Efficiency and Economic Efficiency emerged as the most influential evaluation criteria for digital adoption. To validate the reliability and consistency of the proposed methodology, a sensitivity analysis was conducted by modifying the weight values of the criteria, with robustness tested across 15 different scenarios. The results provide logistics managers with a structured approach for selecting and implementing the most impactful digital technologies to improve efficiency, cost-effectiveness, and supply chain resilience. Furthermore, the study offers insights for the automotive industry to integrate smart vehicle technologies and AI-driven solutions, increasing connectivity, automation, and sustainability in intermodal logis-tics. Future research can extend this framework by incorporating additional MCDM methods and real-world case studies to further refine digital transformation strategies in freight transport.
Primary Language | English |
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Subjects | Automotive Engineering (Other) |
Journal Section | Articles |
Authors | |
Publication Date | June 30, 2025 |
Submission Date | February 14, 2025 |
Acceptance Date | May 10, 2025 |
Published in Issue | Year 2025 Volume: 9 Issue: 2 |
International Journal of Automotive Science and Technology (IJASTECH) is published by Society of Automotive Engineers Turkey