Probabilistic model for the impact of fear of flying on airline network structures

Abstract

Many passengers experience nervousness and/or anxiety when they fly and, on average, they make fewer trips than those who are not afraid. This might reduce airline revenues and profits. In this paper, a new mathematical model of profitability of different airline network choices in a liberalized market is proposed in terms of two particular personal features of passengers: the loyalty to a preferred airline and the fear of flying, which are assumed to be random. A detailed analysis of different network-type structures is presented and optimal solutions depending on the impact of these two random attributes for each of the networks are characterized in terms of the model parameters. The main finding is that the symmetric networks (hub-and-spoke or point-to-point) may not always be the optimal configuration, but a hybrid network configuration may be favoured in some cases. It is also shown that under certain conditions, the point-to-point network structure provides a higher total number of flights due to the fear of flying, which pushes the airlines to reduce the number of indirect routes.