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Predicting block times: An application of Box-Jenkins models
Journal of Airport Management,
7
(1),
45-54
(2012)
Abstract
Predictability is an important key performance area because it influences airlines’ on-time performance and passengers’ satisfaction. Predictability also plays a significant role in ensuring a successful transition from air traffic control to a managed air traffic system. Yet, predictable block times are all the more difficult to achieve as the on-time execution of a flight may be constrained by three types of delay which airlines cannot control: induced, propagated and random. This paper proposes a methodology based on the Box-Jenkins models to measure the predictability of block times as an alternative to variance or standard deviation of block delays. The padding of schedules and the timeliness of flight plans are likely to bias the variation in block delays as an indicator of predictability.
Keywords: predictability; delay; block time; airline schedule
The full article is available to subscribers to the journal.
Author's Biography
Tony Diana is the Acting Division Manager, Outreach at the US Federal Aviation Administration (FAA). He received his doctorate in policy analysis and quantitative management from the University of Maryland, Baltimore County. He is involved in the communication of progress in modernisation programmes at US airports, metroplexes and airspaces. Prior to that position, he was Division Manager, NextGen Performance in the Office of NextGen Performance and Outreach and Deputy Division Manager, Forecasting and Performance Analysis, in the Office of Aviation Policy and Plans of the FAA, where he managed the aviation system performance metrics data warehouse. At the Maryland Aviation Administration, he was involved in performance measurement and route development. Tony’s main interests are performance evaluation and benchmarking as well as the study of delay. He is a certified Lean Sigma Master Black Belt and a certified Project Management Professional.
