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Aviation infrastructure performance and airline cost: a statistical cost estimation approach

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  • Hansen, Mark M.
  • Gillen, David
  • Djafarian-Tehrani, Reza

Abstract

The relationship between the performance of the US National Airspace System (NAS) and airline costs is examined by estimating airline cost functions that include NAS performance metrics as arguments, using quarterly data for 10 US domestic airlines. Performance metrics that vary by airline and quarter are developed by applying principal component analysis to seven underlying variables, including average delay, delay variance, and the proportion of flights that is cancelled. This analysis reveals that variation in the seven variables can be adequately captured by three or fewer factors, which we term NAS performance factors. If three factors are used, they can be interpretted as "delay", "variability", and "disruption", the latter two of which are merged into a single "irregularity" factor in the two-factor model. Cost function estimation results confirm the anticipated link between NAS performance and airline cost. In the cost models with two and three performance factors, the irregularity and disruption factors are found to have the strongest cost impacts. These results challenge the prevailing assumption that delay reduction is the most important benefit from NAS enhancements. Using the estimated cost models, we predict airline cost savings from substantially improved NAS performance in the range $1-4 billion annually.

Suggested Citation

  • Hansen, Mark M. & Gillen, David & Djafarian-Tehrani, Reza, 2001. "Aviation infrastructure performance and airline cost: a statistical cost estimation approach," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 37(1), pages 1-23, March.
  • Handle: RePEc:eee:transe:v:37:y:2001:i:1:p:1-23
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    Cited by:

    1. Ismail, Noor Azina & Jenatabadi, Hashem Salarzadeh, 2014. "The influence of firm age on the relationships of airline performance, economic situation and internal operation," Transportation Research Part A: Policy and Practice, Elsevier, vol. 67(C), pages 212-224.
    2. Zou, Bo & Hansen, Mark, 2012. "Impact of operational performance on air carrier cost structure: Evidence from US airlines," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 48(5), pages 1032-1048.
    3. Hanif D. Sherali & Raymond W. Staats & Antonio A. Trani, 2006. "An Airspace-Planning and Collaborative Decision-Making Model: Part II---Cost Model, Data Considerations, and Computations," Transportation Science, INFORMS, vol. 40(2), pages 147-164, May.
    4. Fan, Terence Ping Ching, 2019. "Schedule creep – In search of an uncongested baseline block time by examining scheduled flight block times worldwide 1986–2016," Transportation Research Part A: Policy and Practice, Elsevier, vol. 121(C), pages 192-217.
    5. Dunkerley Fay & Andre de Palma & Proost Stef, 2005. "Asymmetric Duopoly in Space - what policies work?," Energy, Transport and Environment Working Papers Series ete0509, KU Leuven, Department of Economics - Research Group Energy, Transport and Environment.
    6. Goh, Mark & Yong, Jongsay, 2006. "Impacts of code-share alliances on airline cost structure: A truncated third-order translog estimation," International Journal of Industrial Organization, Elsevier, vol. 24(4), pages 835-866, July.
    7. Xiong, Jing & Hansen, Mark, 2013. "Modelling airline flight cancellation decisions," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 56(C), pages 64-80.
    8. Hashem Salarzadeh Jenatabadi & Peyman Babashamsi & Datis Khajeheian & Nader Seyyed Amiri, 2016. "Airline Sustainability Modeling: A New Framework with Application of Bayesian Structural Equation Modeling," Sustainability, MDPI, vol. 8(11), pages 1-17, November.
    9. Zou, Bo & Hansen, Mark, 2014. "Flight delay impact on airfare and flight frequency: A comprehensive assessment," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 69(C), pages 54-74.
    10. M. Selim Aktürk & Alper Atamtürk & Sinan Gürel, 2014. "Aircraft Rescheduling with Cruise Speed Control," Operations Research, INFORMS, vol. 62(4), pages 829-845, August.
    11. Birisci, Esma & McGarvey, Ronald G., 2016. "Inferring shortfall costs and integrating environmental costs into optimal production levels for an all-you-care-to-eat food service operation," International Journal of Production Economics, Elsevier, vol. 182(C), pages 157-164.
    12. Zou, Bo & Hansen, Mark, 2012. "Flight delays, capacity investment and social welfare under air transport supply-demand equilibrium," Transportation Research Part A: Policy and Practice, Elsevier, vol. 46(6), pages 965-980.
    13. Hugo Salgado & Manuel Romero-Hernández, 2006. "Economies of Density, Network Size and Spatial Scope in the European Airline Industry," Working Papers 2006-13, FEDEA.
    14. Zou, Bo & Elke, Matthew & Hansen, Mark & Kafle, Nabin, 2014. "Evaluating air carrier fuel efficiency in the US airline industry," Transportation Research Part A: Policy and Practice, Elsevier, vol. 59(C), pages 306-330.
    15. Romero-Hernandez, Manuel & Salgado, Hugo, 2005. "Economies of Density, Network Size and Spatial Scope in the European Airline Industry," Institute of Transportation Studies, Research Reports, Working Papers, Proceedings qt9609m6hs, Institute of Transportation Studies, UC Berkeley.
    16. Ryerson, Megan S., 2010. "Optimal Intercity Transportation Services with Heterogeneous Demand and Variable Fuel Price," University of California Transportation Center, Working Papers qt8696z26t, University of California Transportation Center.
    17. Zuidberg, Joost, 2014. "Identifying airline cost economies: An econometric analysis of the factors affecting aircraft operating costs," Journal of Air Transport Management, Elsevier, vol. 40(C), pages 86-95.
    18. Singh, Jagroop & Sharma, Somesh Kumar & Srivastava, Rajnish, 2019. "What drives Indian Airlines operational expense: An econometric model," Journal of Air Transport Management, Elsevier, vol. 77(C), pages 32-38.
    19. Kaukin, Andrey (Каукин, Андрей), 2018. "Diagnosis of the Growth Model of the Russian Air Transportation Market: Bottlenecks and Directions of Development [Диагностика Модели Роста Российского Рынка Авиаперевозок: Узкие Места И Направлени," Working Papers 061830, Russian Presidential Academy of National Economy and Public Administration.

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