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Quantifying the Relationship Between Airline Load Factors and Flight Cancellation Trends Tien, Shin-Lai ; Churchill, Andrew M ; Ball, Michael

By: Contributor(s): Series: ; 2106Publication details: Washington DC Transportation Research Record: Journal of the Transportation Research Board, 2009Description: s. 38-46ISBN:
  • 9780309126212
Subject(s): Bibl.nr: VTI P8167:2106Location: Abstract: Flight cancellation decisions depend on many observed and unobserved variables. Of those, load factor plays an important role and has shown a significantly increasing trend over recent years. The statistical relationship between aggregate flight cancellation rates and load factors at the nationwide level was researched by using a quantile regression model. From analysis of a full range of conditional quantiles of cancellation rate, it was observed that, at high quantiles in the distribution of flight cancellation rates, load factor is the limiting consideration driving flight cancellation rate; that is, load factor has an increasing impact as the tendency to cancel flights becomes more pronounced. The influence of external events-for example, the effect of the September 11, 2001, terrorist attacks-is also illustrated by comparing the estimation results from quantile regression and ordinary least squares models. Further categorizing of data by business type of carriers, showed that the flight cancellation rate of network carriers shows a rather different relationship to load factor than that of the low-cost carriers.
Item type: Reports, conferences, monographs
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Statens väg- och transportforskningsinstitut Available

Flight cancellation decisions depend on many observed and unobserved variables. Of those, load factor plays an important role and has shown a significantly increasing trend over recent years. The statistical relationship between aggregate flight cancellation rates and load factors at the nationwide level was researched by using a quantile regression model. From analysis of a full range of conditional quantiles of cancellation rate, it was observed that, at high quantiles in the distribution of flight cancellation rates, load factor is the limiting consideration driving flight cancellation rate; that is, load factor has an increasing impact as the tendency to cancel flights becomes more pronounced. The influence of external events-for example, the effect of the September 11, 2001, terrorist attacks-is also illustrated by comparing the estimation results from quantile regression and ordinary least squares models. Further categorizing of data by business type of carriers, showed that the flight cancellation rate of network carriers shows a rather different relationship to load factor than that of the low-cost carriers.