Identifying flight fatigue factors: An econometric modeling approach

The paper looks at responses of crewmembers of six Taiwan air carriers who were asked to report their levels of fatigue before takeoff and after landing. Ordinal probit models are employed to estimate three fatigue models for different flight operations and serve as vehicles to investigate flight fatigue factors and identify their relative significance. The top three factors for long haul flights are found to be sleep quality at home, sleep quality on aircraft and “nod-off “experiences; for regional flights, age, extra non-flying tasks on the ground, and experiences of fatigue during flight operations are important; and for domestic flights poor cockpit environment, age, and experiences of fatigue during flight operations are relevant.     

The impact of flight delays on passenger demand and societal welfare

US airline passengers increasingly have access to flight delay information from online sources. As a result, air passenger travel decisions can be expected to be influenced by delay information. In addition, delays affect airline operations, resulting in increased block times on routes and, in general, higher carrier costs and airfares. This paper examines the impact of flight delays on both passenger demand and airfares. Delays are calculated against scheduled block times as well as against more idealized feasible flight times. Based on econometric estimations, welfare impacts of flight delays are calculated. We find that flight delays on a route reduce passenger demand and raise airfares, producing significant decreases in both consumer and producer welfare. Since producer welfare effects are estimated to be three times as large as consumer welfare effects, we conclude that from an economic efficiency rationale, airlines should be required to pay for the bulk of flight delay remediation efforts.     

The impact of hubbing concentration on flight delays within airline networks: An empirical analysis of the US domestic market

This paper explores the relationship between hubbing activities and flight delays in the United States from an airline-specific network perspective. Airline hubbing is measured with the Hubbing Concentration Index. We estimate the impact of hubbing behavior on delays, using three measures of delay, two based on delay against schedule, and the third based on buffer-corrected excess travel times. A significant (and positive) influence of hubbing concentration can only be found for the latter delay indicator. We conclude that airlines use buffer times to mitigate passenger-perceived delays against schedule that would, without buffers, arise from more complex network operations.