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Efficiency assessment and output maximization possibilities of European small and medium sized airports

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  • Gutiérrez, Ester
  • Lozano, Sebastián

Abstract

The aim of this research is to investigate the operational efficiency and potential output increase scenarios of 21 small and medium sized airports (SMA) located in 10 different European countries. A key feature of the proposed Data Envelopment Analysis (DEA) models is the consideration of two novel inputs related to the number of airlines and scheduled routes operating at each airport, in addition to the more common capital non-discretionary inputs (runways, boarding gates and apron). These novel inputs are a way of considering the effects of the air transport market on airports' performance and growth prospects. In particular, a model to estimate the growth in passenger numbers, aircraft movements and cargo that can be achieved by an airport through increasing its number of airlines and routes, and assuming an efficient operation, is presented. Also, a multi-objective DEA model is proposed to explore the possible trade-offs in the output Pareto efficient frontier of a given airport. In addition, a second stage fractional regression model specific for explaining DEA efficiency scores is conducted and the results suggest that ownership structure and hub airport status are significant factors for explaining variations in the operational efficiency of European SMA.

Suggested Citation

  • Gutiérrez, Ester & Lozano, Sebastián, 2016. "Efficiency assessment and output maximization possibilities of European small and medium sized airports," Research in Transportation Economics, Elsevier, vol. 56(C), pages 3-14.
  • Handle: RePEc:eee:retrec:v:56:y:2016:i:c:p:3-14
    DOI: 10.1016/j.retrec.2016.07.001
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    Cited by:

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    2. Żółtaszek Agata & Pisarek Renata, 2016. "Effectiveness of National Airlines in Europe – the DEA Approach," Folia Oeconomica Stetinensia, Sciendo, vol. 16(2), pages 103-118, December.
    3. Raúl Pérez-Reyes & Beatriz Tovar, 2021. "Peruvian Electrical Distribution Firms’ Efficiency Revisited: A Two-Stage Data Envelopment Analysis," Sustainability, MDPI, Open Access Journal, vol. 13(18), pages 1-19, September.
    4. Güner, Samet & İbrahim Cebeci, Halil, 2021. "Multi-period efficiency analysis of major European and Asian airports under fixed proportion technologies," Transport Policy, Elsevier, vol. 107(C), pages 24-42.
    5. Güner, Samet & Cebeci, Halil İbrahim, 2021. "Output targeting and capacity utilization for a new-built airport: Analysis for the new airport in Istanbul," Socio-Economic Planning Sciences, Elsevier, vol. 76(C).
    6. Graham, Prof Anne, 2020. "Airport privatisation: A successful journey?," Journal of Air Transport Management, Elsevier, vol. 89(C).
    7. lo Storto, Corrado, 2018. "Ownership structure and the technical, cost, and revenue efficiency of Italian airports," Utilities Policy, Elsevier, vol. 50(C), pages 175-193.
    8. Yu, Hang & Zhang, Yahua & Zhang, Anming & Wang, Kun & Cui, Qiang, 2019. "A comparative study of airline efficiency in China and India: A dynamic network DEA approach," Research in Transportation Economics, Elsevier, vol. 76(C).
    9. Chaouk, Mohammed & Pagliari, Dr Romano & Moxon, Richard, 2020. "The impact of national macro-environment exogenous variables on airport efficiency," Journal of Air Transport Management, Elsevier, vol. 82(C).

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    More about this item

    Keywords

    Small and medium sized airports; Data envelopment analysis; Output Pareto efficient frontier; Augmented weighted Tchebycheff; Fractional regression; Ownership; Hub;
    All these keywords.

    JEL classification:

    • R4 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Transportation Economics
    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis

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