Data Envelopment Analysis (DEA) has become an established approach for analyzing and comparing efficiency results of corporate organizations or economic agents. It has also found wide application in comparative studies on airport efficiency. The standard DEA approach to comparative airport efficiency analysis has two feeble elements, viz. a methodological and a substantive weakness. The methodological weakness originates from the choice of uniform efficiency improvement assessment, while the substantive weakness in airport efficiency analysis concerns the insufficient attention for short-term and long-term adjustment possibilities in the production inputs determining airport efficiency. The present paper aims to address both flaws by: (i) designing a data-instigated Distance Friction Minimization (DFM) model as a generalization of the standard Banker-Charnes-Cooper (BCC) model with a view to the development of a more appropriate efficiency improvement projection model in the BCC version of DEA; (ii) including as factor inputs also lumpy or rigid factors that are characterized by short-term indivisibility or inertia (and hence not suitable for short-run flexible adjustment in new efficiency stages), as is the case for runways of airports. This so-called fixed factor (FF) case will be included in the DFM submodel of DEA. This extended DEA – with a DFM and an FF component – will be applied to a comparative performance analysis of several major airports in Europe. Finally, our comparative study on airport efficiency analysis will be extended by incorporating also the added value of the presence of shopping facilities at airports for their relative economic performance.
Transportation Demand Supply and Congestion Safety and Accidents Transportation Noise