Evaluation of deregulated airline networks using data envelopment analysis combined with principal component analysis with an application to Western Europe

Abstract US experience shows that deregulation of the airline industry leads to the formation of hub-and-spoke (HS) airline networks. Viewing potential HS networks as decision-making units, we use data envelopment analysis (DEA) to select the most efficient networks configurations from the many that are possible in the deregulated European Union airline market. To overcome the difficulties that DEA encounters when there is an excessive number of inputs or outputs, we employ principal component analysis (PCA) to aggregate certain, clustered data, whilst ensuring very similar results to those achieved under the original DEA model. The DEA–PCA formulation is then illustrated with real-world data gathered from the West European air transportation industry.