AI-Supported Fleet and Network Design for a Hybrid Airline Model: A Case Study on an Airline Startup

Abstract

The airline sector is constantly evolving in response to technological advancements, increasing competition among airlines, and changing passenger demands. With these developments, strategic decisions such as fleet planning, demand forecasting, and flight network design are becoming key elements of sustainable growth and competitive advantage for airlines. This study presents a conceptual AI-supported strategic planning framework that demonstrates the decision-making processes in which AI can be integrated into fleet planning, demand forecasting, and flight network design for a new airline with a hybrid business model in Türkiye. The study employed a qualitative research approach, and a conceptual case study was conducted within the conceptual framework to examine how AI applications can be integrated into decision-support processes. Within this framework, conceptual and strategic assessments were conducted by creating scenarios using examples from Turkish Airlines and Pegasus Airlines over a 15-year period spanning 2009-2024. Accordingly, the study includes airline business model design, demand forecasting, flight network design, schedule design, fleet design, and a SWOT analysis of the company. The research results suggest that if an airline with a hybrid business model enters the sector, a balanced fleet with a mix of aircraft types could be utilized, while a structure centered in Istanbul, Ankara, and Izmir would provide strategic advantages. In addition, the study reveals findings regarding the usability of artificial intelligence (AI) applications in airline operational processes and how they can be integrated. In this context, the study contributes to the literature on airline operations planning and offers practical recommendations for airlines.

Keywords

• Artificial intelligence
• Demand forecasting
• Fleet planning
• Flight network design
• Hybrid business model

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