Beyond throughput: Incorporating air transport network topology in airport performance measurement

Airport ranking studies have traditionally focused on throughput criteria such as passenger and cargo volume, overlooking the importance of air transport network topology in assessing airport performance. In this work, we propose a novel approach that incorporates both traditional throughput criteria and air transport network topology criteria, such as degree centrality (direct connections) and betweenness centrality (transit connections). To ensure unbiased criteria weight estimation, we combine objective and subjective weights using Bayes' theorem. Using our approach, we develop a Global Airport Performance Score (GAPS) to measure the performance of airports. We then apply this methodology to rank the top 50 international commercial service airports in 2019, published by Airports Council International, to validate our proposed methodology. Furthermore, we conduct a sensitivity analysis to demonstrate the robustness of our method. The results reveal valuable insights for benchmarking airports in the worldwide air transportation network. By considering both traditional throughput criteria and air transport network topology, our approach can help airport operators, policymakers, and other stakeholders make more informed decisions about airport investments and improvements.