Analyzes ground times' effects on future aircraft design and airline networks, highlighting implications for efficiency.
Extended aircraft ground times between two flights are widely recognised to have the potential to increase costs, to generate network inefficiencies, and to diminish the attractiveness of both airports and airlines. As a result, minimizing ground times, and thereby maximising aircraft utilisation, has become an objective within airline operation planning. Furthermore, incorporating operational data such as ground times into scenario-based analyses has become relevant for identifying suitable design parameters in future aircraft concepts, such as the design of liquid hydrogen (LH 2 ) or electric aircraft. This study aims to explore the dynamics of ground times in relation to future aircraft design and airline networks. A dual approach is employed, combining both descriptive and analytical methods to analyse ground times across factors as aircraft types, regions, airports, and airlines. An openly available ADS-B data set to extract ground time information from flight operations between 2022 and 2024 is utilised. Additionally, flight schedules and passenger demand data are incorporated to conduct a network analysis from airport and network level, evaluating how ground times affect overall airline performance and connectivity. The analysis of ground times across aircraft categories highlights the need for range- and operation-specific insulation strategies in future LH 2 aircraft to optimise hydrogen storage. Furthermore, the regression-based network analysis reveals that reduced ground times are associated with greater network robustness, higher passenger numbers, increased connectivity, enhanced centrality, and improved aircraft utilisation at the network level, with variations observed across regions and business models. Regional differences are more evident at the airport level, while business model variations became more apparent at the network level.
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Stoebke et al. (2026) studied this question.
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