Airline Schedule Competition

Review of Industrial Organization (Impact Factor: 0.48). 02/2007; 30(3):161-177. DOI: 10.1007/s11151-007-9140-1
Source: RePEc


This paper presents a simple model of airline schedule competition that circumvents the complexities of the spatial approach used in earlier papers. Consumers choose between two duopoly carriers, each of which has evenly spaced flights, by comparing the combinations of fare and expected schedule delay that they offer. In contrast to the spatial approach, the particular departure times of individual flights are thus not relevant. The model generates a number of useful comparative-static predictions, while welfare analysis shows that equilibrium flight frequencies tend to be inefficiently low.

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    • "Norman and Strandenes [17] also calibrate model parameters using empirical data but for a strategic form game. None of the studies mentioned so far provides any guarantee or conditions for existence or uniqueness of a pure strategy equilibrium. Brueckner and Flores-Fillol [10] and Brueckner [9] obtain closed form expressions for equilibrium decisions analytically. They focus on symmetric equilibria while ignoring the possibility of any asymmetric equilibria. "
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    ABSTRACT: Frequency competition influences capacity allocation decisions in airline markets and has important implica-tions to airline profitability and airport congestion. Market share of a competing airline is a function of its frequency share and the relationship between the two is pivotal for understanding the impacts of frequency competition on airline business. Based on the most commonly accepted form of this relationship, we propose a game-theoretic model of airline frequency competition. We characterize the conditions for existence and uniqueness of a Nash equilibrium for the 2-player case. We analyze two different myopic learning dynamics for the non-equilibrium situations and prove their convergence to Nash equilibrium under mild conditions. For the N-player game between identical players, we characterize all the pure strategy equilibria and identify the worst-case equilibrium, i.e. the equilibrium with maximum total cost. We provide an expression for the measure of inefficiency, similar to the price of anarchy, which is the ratio of the total cost of the worst-case equilibrium to the total cost of the cost minimizing solution and investigate its dependence on different parameters of the game.
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    • "Though these results are derived for a monopoly model, similar results hold in a competitive model (Brueckner and Flores-Fillol, 2007). "
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    ABSTRACT: This paper assesses the determinants of aircraft size and frequency of flights on airline routes by considering market demographics, airport characteristics, airline characteristics and route characteristics. The paper shows that frequency and aircraft size increase with population, income, and runway length. An increase in the proportion of managerial workers in the labor force or the proportion of population below the age of 25 results in greater frequency with the use of small planes. Slot constrained airports and an increase in the number of nearby airports lead to lower flight frequency with the use of smaller planes. Hubs and low cost carriers are associated with larger plane sizes and higher frequency, while regional airline ownership leads to higher frequency and the use of smaller planes. An increase in distance between the endpoints leads to lower frequency with the use of larger planes. As airport delay rises, airlines reduce frequency and use smaller planes, though when airport cancellations rise, flight frequency increases with the use of larger planes. This finding suggests airlines utilize frequency and aircraft size to hedge against flight cancellations.
    Journal of Air Transport Management 12/2007; 16(4). DOI:10.1016/j.jairtraman.2009.08.001 · 0.91 Impact Factor
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    ABSTRACT: This paper tests whether it is possible to address the hub location problem using the industrial organization framework. In particular, it focuses on the scheduling effect on the demand side and the number of passengers traveling between each city pair. The study shows that the hub city is not always chosen such that the number of rim passengers is minimized. If this number increases, the monopoly airline loses revenue because many passengers use the airline service with lower airfare. However, the increase in rim passengers can strengthen scheduling effects, thereby increasing revenue. Additional simulation analyses with this strategy further show that the probability of choosing a hub city that is not socially preferable is small. JEL ClassificationL93–R41
    The Annals of Regional Science 01/2009; 49(3):1-15. DOI:10.1007/s00168-011-0446-4 · 1.03 Impact Factor
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