Volume
34
Issue
3
Key words
Airport pricing, Market dynamics, Competition, Quantile regression, Price equilibrium
Abstract
This study investigates the competitive dynamics of airport pricing using U.S. airport data to validate the findings. It employs linear and nonlinear ordinary differential equation models to analyze the influence of competitive interactions and internal factors on pricing decisions. The methodology involves parameter estimation via optimization techniques and quantile regression to capture heterogeneity across market segments. Mathematical analysis and simulation results show that if competitive coupling coefficients are low then there is weak competitive influence on pricing, with airports’ pricing largely driven by internal factors. Also, if the adjustment rates exhibit consistency across airports then internal dynamics are dominant in price adjustments. Using the US airports data, quantile regression further reveals that competitive effects become more pronounced in premium market segments, with variations across quantiles. The findings suggest that airport pricing strategies should focus on internal factors rather than competition. This study recommends integrating demand elasticity, capacity constraints, and stochastic elements to refine pricing models and enhance market efficiency.
Scholarly Commons Citation
Chikore,, T.,
& Nyabadza,, F.
(2025).
A Mathematical Model on the Temporal Dynamics of Aviation Competitive Pricing.
Journal of Aviation/Aerospace Education & Research, 34(3).
DOI: https://doi.org/10.58940/2329-258X.2160
Included in
Data Science Commons, Non-linear Dynamics Commons, Ordinary Differential Equations and Applied Dynamics Commons