Network-centric benchmarking of operational performance in aviation

Performance analysis of the air traffic operations is challenging because of the need to account for weather impacts and network effects. In this paper, we propose a framework that uses network clustering to identify baselines for benchmarking airline on-time performance. We demonstrate our framework by computing cancellation and departure delay baselines using US flight data for the years 2014?16. Subsequently, we use these baselines to benchmark daily on-time performance at the system-wide, airline-, and airport-specific levels, for both mainline and regional carriers. This framework enables an airline to conduct self- and peer-comparisons, evaluate improvements over time, and diagnose causes of poor on-time performance. Furthermore, our framework can be used by system operators to identify long-term trends in traffic management initiatives.

Automated summary

The study introduces a framework that uses network clustering to identify baseline benchmarks for airline on-time performance, demonstrated using US flight data from 2014 to 2016. This framework enables airlines to conduct self- and peer-comparisons, evaluate improvements over time, and diagnose causes of poor on-time performance.