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The TECLOG theoretical model addresses the educational challenges faced by logistics and business operations students at the University of Panama. This model integrates the theories of Cohen and Levinthal (1990), Davis (1989), and Grefen et al. (2019), proposing a conceptual framework based on three fundamental variables: Logistical Competencies (LC), Technological Readiness (TR), and Perception of Trends and Future Challenges (TF). The study aims to bridge the gap between academia and the labor market through a solid and structured theoretical-conceptual approach that links education with the strategic use of technological tools. These tools are grouped into four key categories: operational automation (robotics, autonomous vehicles, digital twins), integrated management (ERP, WMS, TMS), traceability and monitoring (RFID, barcodes, real-time systems), and advanced analytics (big data, artificial intelligence, IoT, and blockchain). Proper implementation of these technologies not only optimizes operational efficiency and decision-making but also enables the adaptation of logistical processes to highly dynamic and demanding environments. Furthermore, the perception of trends and future challenges is established as a critical competency in logistics education, as it allows for anticipating transformations in the current business environment and developing more efficient strategies. The interrelationship between these variables is essential, as it strengthens students' preparedness to face digital transformation scenarios and strategic challenges across various business sectors. In conclusion, TECLOG represents a key contribution to logistics education, aligning training with the current dynamics of sector management and operations.