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Coalitions in the airline industry: an empirical approach

Author

Listed:
  • David Bartolini

    (Department of Economics, Università Politecnica delle Marche.)

  • Alberto Gaggero

    (Department of Economics, University of Pavia)

Abstract

This paper conducts an empirical analysis of the determinants of airline alliances. Well established airlines with large passengers' volumes are more likely to participate in an alliance and are also essential for alliance survivability. In line with this finding, older air-lines have a higher probability of being part of an alliance. Airlines operating with high load factors consider alliance participation as a significant alternative to fleet capacity expansion. As their market share grows, alliances become more appealing to airlines. Competitors' decision to enter an alliance tends to have a positive impact on alliance participation. The relatively similar magnitude and effect of the regressors' coefficients across different alliance choices, suggests that the airline's major decision is not to choose a specific alliance, but rather considering whether to enter into an alliance, as a possible strategy within its business model.

Suggested Citation

  • David Bartolini & Alberto Gaggero, 2012. "Coalitions in the airline industry: an empirical approach," Quaderni di Dipartimento 165, University of Pavia, Department of Economics and Quantitative Methods.
  • Handle: RePEc:pav:wpaper:165
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    Cited by:

    1. Alderighi, Marco & Gaggero, Alberto A. & Piga, Claudio A., 2015. "The effect of code-share agreements on the temporal profile of airline fares," Transportation Research Part A: Policy and Practice, Elsevier, vol. 79(C), pages 42-54.
    2. Czerny, Achim I. & Jost, Peter-J. & Lang, Hao & Mantin, Benny, 2021. "Carrier collaboration with endogenous networks: Or, the limits of what carrier collaboration can achieve under antitrust immunity," Journal of Air Transport Management, Elsevier, vol. 94(C).
    3. Thanh Ngo & Kan Wai Hong Tsui, 2022. "Estimating the confidence intervals for DEA efficiency scores of Asia-Pacific airlines," Operational Research, Springer, vol. 22(4), pages 3411-3434, September.
    4. Alderighi, Marco & Gaggero, Alberto A., 2014. "The effects of global alliances on international flight frequencies: Some evidence from Italy," Journal of Air Transport Management, Elsevier, vol. 39(C), pages 30-33.
    5. Volodymyr Bilotkach, 2019. "Airline Partnerships, Antitrust Immunity, and Joint Ventures: What We Know and What I Think We Would Like to Know," Review of Industrial Organization, Springer;The Industrial Organization Society, vol. 54(1), pages 37-60, February.
    6. Marco Alderighi, 2013. "Air accessibility and the export of Italian manufacture in Europe: Evidence at regional level," ERSA conference papers ersa13p1304, European Regional Science Association.
    7. Castiglioni, Marco & Gallego, à ngeles & Galán, José Luis, 2018. "The virtualization of the airline industry: A strategic process," Journal of Air Transport Management, Elsevier, vol. 67(C), pages 134-145.
    8. Meichsner, Nadine A. & O'Connell, John F. & Warnock-Smith, David, 2018. "The future for African air transport: Learning from Ethiopian Airlines," Journal of Transport Geography, Elsevier, vol. 71(C), pages 182-197.
    9. Alderighi, Marco & Gaggero, Alberto A., 2018. "Flight cancellations and airline alliances: Empirical evidence from Europe," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 116(C), pages 90-101.
    10. Button, Kenneth & Porta, Flavio & Scotti, Davide, 2020. "The role of strategic airline alliances in Africa," MPRA Paper 108265, University Library of Munich, Germany.
    11. Lu, Jin-Long & Yang, Chih-Wen, 2022. "Good or bad? Passenger feelings regarding code-share alliances among airlines," Journal of Air Transport Management, Elsevier, vol. 103(C).
    12. Gaggero, Alberto A. & Piazza, Giovanni, 2021. "Multilayer networks and route entry into the airline industry: Evidence from the U.S. domestic market," Research in Transportation Economics, Elsevier, vol. 90(C).

    More about this item

    Keywords

    Discrete choice model; Oneworld; Sky Team; Star Alliance.;
    All these keywords.

    JEL classification:

    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models
    • L10 - Industrial Organization - - Market Structure, Firm Strategy, and Market Performance - - - General
    • L93 - Industrial Organization - - Industry Studies: Transportation and Utilities - - - Air Transportation

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