Data-driven comparison of airline passenger flight supply using optimal transport theory

This study develops an optimal transport (OT) framework for measuring pairwise airline supply dissimilarity across heterogeneous route networks. By representing each airline as a distribution of seat capacity or flight frequency across routes and defining route-level transportation costs, the framework provides a flexible and interpretable approach to comparing carriers beyond traditional measures based on multimarket contact or aggregate concentration. To illustrate its versatility, three OT-based dissimilarity indices are introduced to capture differences in seasonal supply positioning, geographic market proximity, and route-length structure. The framework is applied to European scheduled passenger flights for 32 airlines between 2016 and 2025. The empirical results show that airline relationships are multidimensional, with different patterns of similarity emerging across carrier types and network characteristics. A longitudinal analysis relative to the 2016 baseline reveals heterogeneous adjustment trajectories across airlines and indicates post-pandemic convergence in some dimensions of network organization alongside persistent differentiation in others. Overall, the proposed OT framework provides a general tool for inferring airline similarity from transport distances, assessing resilience and recovery following shocks, and examining structural change over time. The framework can also support the construction of airline peer groups for benchmarking, and the medium- to long-term monitoring of structural network recovery following major market shocks.