Cost leadership strategies in low-cost airlines: A deep learning-based comparative analysis of Ryanair and Pegasus

Abstract

Air transportation plays a crucial role in the development of the global tourism industry, facilitating the movement of travellers across different regions and enhancing accessibility to tourism destinations. Airline companies generally operate under traditional, low-cost, non-scheduled, or regional business models. This study focuses on low-cost carriers (LCCs) that implement a cost leadership strategy to maintain competitiveness in the industry. It investigates whether these airlines effectively apply this strategy, identifies their similarities and differences, and evaluates the impact of their cost leadership approach on social media perceptions. A mixed-methods approach was employed, incorporating two key methodologies: (a) document analysis of airline financial reports to assess cost leadership practices and (b) sentiment analysis of customer perceptions using deep learning algorithms, including recurrent neural networks (RNNs), long short-term memory (LSTM), bidirectional LSTM (Bi-LSTM), and gated recurrent units (GRUs). This AI-driven analysis ensured a high degree of classification accuracy in sentiment evaluation. The results indicate that Ryanair strictly adheres to its cost leadership strategy, yet it experiences lower customer satisfaction levels on social media. Conversely, Pegasus Airlines receives higher customer satisfaction ratings, but its cost leadership implementation is less effective. These results highlight the trade-off between operational cost efficiency and the overall tourism experience, offering valuable insights for airline executives, tourism policymakers and industry researchers.