Abstract The civil aviation industry is critical to the economic development of any nation. Being a key infrastructure service, the performance of the civil aviation industry spills over to other segments of the economy. We investigate service failure among US airlines, using departure delay, and model its likelihood using mixed-logit regression. We characterize arrival performance for delayed departures using a service recovery/double deviation framework. We model the likelihood of different arrival possibilities using multinomial logistic regression. We use the chosen airline, temporality, and flight duration as predictors. Our key results include: (i) Afternoon/evening flights, and longer duration flights are more likely to depart late; (ii) Delta Airlines is most likely to depart on time; (iii) Southwest Airlines is best in recovering from delayed departures; (iv) United Airlines is most likely to aggravate delays.
Highlights Service failures are rampant in the US civil aviation sector. We analyze delays using a novel service recovery/double deviation framework. We identify consumer-centric factors as predictors of departure and arrival delays. We predict delay likelihoods using mixed-logit and multinomial regression.
Effect of airline choice and temporality on flight delays
2020-03-27
Aufsatz (Zeitschrift)
Elektronische Ressource
Englisch
Security Flight data software bug may have caused airline delays
British Library Online Contents | 2005
A Decision Support Framework for Airline Flight Cancellations and Delays
Online Contents | 1993
|Econometric Analysis of U.S. Airline Flight Delays with Time-of-Day Effects
Online Contents | 2006
|Letters - Comments on Airline Delays
Online Contents | 2001
|Econometric Analysis of U.S. Airline Flight Delays with Time-of-Day Effects
British Library Conference Proceedings | 2006
|