Digital Transformation in Airline Logistics: Enhancing Operational Efficiency through AI-Driven Predictive Analytics and Blockchain Integration

This study aims to develop and validate a Predictive AI-Based Supply Chain Visibility Framework (PASCVF) tailored for airline logistics management. Employing a mixed-methods approach within a Design Science Research framework, the research integrates advanced digital technologies including IoT, RFID, blockchain, and AI-driven predictive analytics to enhance operational transparency, reduce lead times, and optimize inventory management. Data were collected from major international airlines using structured interviews, operational records, and simulation modeling. The results reveal significant improvements, including a 20% reduction in lead time, a 25% decrease in stock-out frequency, and a 5-10% reduction in Cost per Available Seat Kilometer (CASK). These findings provide empirical support for the framework, offering actionable insights for enhancing strategic decision-making and operational resilience in the aviation industry. The study contributes to academic theory by extending digital transformation models and has practical implications, recommending that airline executives invest in integrated digital solutions to achieve sustainable performance gains.