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A game theoretic approach to optimal pricing of flights and passengers at congested airports

A game theoretic approach to optimal pricing of flights and passengers at congested airports PurposeThis paper aims to embark a mathematical model based on investigation and comparison of airport pricing policies under various types of competition, considering both per-passenger and per-flight charges at congested airports.Design/methodology/approachIn this model, four-game theoretic strategies are assessed and closed-form formulas have been proved for each of the mentioned strategies. Numerical examples and graphical representations of the optimal solutions are provided to illustrate the models.FindingsThe rectitude of the presented formulas is evaluated with sensitivity analysis and numerical examples have been put forward. Finally, managerial implications are suggested by means of the proposed analysis.Research limitations/implicationsThe represented model is inherently limited to investigate all the available and influential factors in the field of congestion pricing. With this regard, several studies can be implemented as the future research of this study. The applications of other game theoretic approaches such as Cartel games and its combination with the four mentioned games seem to be worthwhile. Moreover, it is recommended to investigate the effectiveness of the proposed model and formulations with a large-scale database.Originality/valueThe authors formulate a novel strategy that put forwards a four-game theoretic strategy, which helps managers to select the best suitable ones for their specific airline and/or air traveling companies. The authors find that by means of the proposed model, the application of Stackelberg–Bertrand behavior in the field of airport congestion pricing will rebound to a more profitable strategy in contrast with the other three represented methods. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Journal of Modelling in Management Emerald Publishing

A game theoretic approach to optimal pricing of flights and passengers at congested airports

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References (43)

Publisher
Emerald Publishing
Copyright
Copyright © Emerald Group Publishing Limited
ISSN
1746-5664
DOI
10.1108/JM2-01-2017-0006
Publisher site
See Article on Publisher Site

Abstract

PurposeThis paper aims to embark a mathematical model based on investigation and comparison of airport pricing policies under various types of competition, considering both per-passenger and per-flight charges at congested airports.Design/methodology/approachIn this model, four-game theoretic strategies are assessed and closed-form formulas have been proved for each of the mentioned strategies. Numerical examples and graphical representations of the optimal solutions are provided to illustrate the models.FindingsThe rectitude of the presented formulas is evaluated with sensitivity analysis and numerical examples have been put forward. Finally, managerial implications are suggested by means of the proposed analysis.Research limitations/implicationsThe represented model is inherently limited to investigate all the available and influential factors in the field of congestion pricing. With this regard, several studies can be implemented as the future research of this study. The applications of other game theoretic approaches such as Cartel games and its combination with the four mentioned games seem to be worthwhile. Moreover, it is recommended to investigate the effectiveness of the proposed model and formulations with a large-scale database.Originality/valueThe authors formulate a novel strategy that put forwards a four-game theoretic strategy, which helps managers to select the best suitable ones for their specific airline and/or air traveling companies. The authors find that by means of the proposed model, the application of Stackelberg–Bertrand behavior in the field of airport congestion pricing will rebound to a more profitable strategy in contrast with the other three represented methods.

Journal

Journal of Modelling in Management – Emerald Publishing

Published: May 14, 2018

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