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Productivity for airline carriers and its relation to deregulation, privatisation and membership in strategic alliances

Author

Listed:
  • Stefan Sjögren

    (School of Business, Economics and Law - GU - Göteborgs Universitet = University of Gothenburg)

  • Magnus Söderberg

    (CERNA i3 - Centre d'économie industrielle i3 - Mines Paris - PSL (École nationale supérieure des mines de Paris) - PSL - Université Paris Sciences et Lettres - I3 - Institut interdisciplinaire de l’innovation - CNRS - Centre National de la Recherche Scientifique)

Abstract

This study looks at how deregulation, privatisation and the formation of strategic alliances have affected the productivity of international airlines. We evaluate all three factors simultaneously and disaggregate the carriers' operations into production and sales and allow for unobserved firm-level heterogeneity through random parameters. Estimations of stochastic frontier models reveal that on the aggregate level, deregulation increases productivity, membership in alliances has an ambiguous effect and state ownership has no significant effect. Disaggregating the carriers' operations confirms the productivity gains from deregulation, and that state ownership and alliances have contradictory effects.

Suggested Citation

  • Stefan Sjögren & Magnus Söderberg, 2011. "Productivity for airline carriers and its relation to deregulation, privatisation and membership in strategic alliances," Post-Print hal-00659176, HAL.
    • Handle: RePEc:hal:journl:hal-00659176
    DOI: 10.1016/j.tre.2010.09.001
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    Cited by:

    1. Bianka Dettmer & Andreas Freytag & Peter Draper, 2013. "Check-in, departure and arrival times: Air cargo in Southern Africa?," Jena Economics Research Papers 2013-018, Friedrich-Schiller-University Jena.
    2. Mahmut BAKIR & Şahap AKAN & Kasım KIRACI & Darjan KARABASEVIC & Dragisa STANUJKIC & Gabrijela POPOVIC, 2020. "Multiple-Criteria Approach of the Operational Performance Evaluation in the Airline Industry: Evidence from the Emerging Markets," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(2), pages 149-172, July.
    3. Wanke, Peter & Barros, C.P., 2016. "Efficiency in Latin American airlines: A two-stage approach combining Virtual Frontier Dynamic DEA and Simplex Regression," Journal of Air Transport Management, Elsevier, vol. 54(C), pages 93-103.
    4. Chen, Zhongfei & Tzeremes, Panayiotis & Tzeremes, Nickolaos G., 2018. "Convergence in the Chinese airline industry: A Malmquist productivity analysis," Journal of Air Transport Management, Elsevier, vol. 73(C), pages 77-86.
    5. Barros, Carlos P. & Liang, Qi Bin & Peypoch, Nicolas, 2013. "The technical efficiency of US Airlines," Transportation Research Part A: Policy and Practice, Elsevier, vol. 50(C), pages 139-148.
    6. Barros, Carlos Pestana & Wanke, Peter, 2015. "An analysis of African airlines efficiency with two-stage TOPSIS and neural networks," Journal of Air Transport Management, Elsevier, vol. 44, pages 90-102.
    7. Dettmer, Bianka & Freytag, Andreas & Draper, Peter, 2014. "Air Cargo beyond Trade Barriers in Africa," Journal of Economic Integration, Center for Economic Integration, Sejong University, vol. 29, pages 95-138.
    8. Min, Hokey & Joo, Seong-Jong, 2016. "A comparative performance analysis of airline strategic alliances using data envelopment analysis," Journal of Air Transport Management, Elsevier, vol. 52(C), pages 99-110.
    9. Liu, Wei & Gao, Lixiang & Song, Hang & Huang, Mingdong, 2021. "Factor market distortion, technology change, and green growth in the Chinese civil airline industry," Journal of Asian Economics, Elsevier, vol. 77(C).
    10. Wanke, Peter & Pestana Barros, Carlos & Chen, Zhongfei, 2015. "An analysis of Asian airlines efficiency with two-stage TOPSIS and MCMC generalized linear mixed models," International Journal of Production Economics, Elsevier, vol. 169(C), pages 110-126.

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