Título: Modelos SARIMA para pronóstico de pasajeros en vuelos nacionales e internacionales en Colombia

Autor(es): GARZON PEREZ LUIS ANDRÉS, HERNANDEZ RUEDA ERIK PAUL, MELO OBANDO JORGE LUIS

Fecha de publicación: 28-mar-2023

Resumen: Colombia's air transport sector has positioned itself as the third country with the highest increase in airport operations in Latin America and the Caribbean. This positioning is due to the dynamism of the air transport sector and the signing of international agreements for the liberalization of commercial airspace. This progress has allowed for the diversification and increase of flight offerings with new airline operators. In order to achieve sustainable growth in the airport sector, it is necessary to have planning that identifies the requirements for modernization and the creation of newairport terminals. This planning should be organized with respect to the forecast of national operations in the terminals based on passenger estimates, in order to avoid the underutilization of airports.In this context of operational planning, this studyaims to focus on a short-term predictive forecast model that determines the number of passengers on domestic flights in Colombia. The SARIMA model approach is applied to the monthly time series data of passengers, based on monthly records of the number ofpassengers on regular domestic flights registered by Aerocivil between 2005 and 2020. The SARIMA (0,1,0) × (0,1,0)12 model for the international flight passenger time series was the most appropriate with an RMSEA estimation of 3.1%. This short-term predictive forecast model shows high performance in the calculated results and can be applied within operational planning as a valid tool to support decision-making.As an extension of this study, it would be appropriate to consider market parameters of air transport that could be integrated into the model and better characterize certain atypical variations found.Improved title: Forecasting Short-Term Domestic Flight Passengers in Colombia Using SARIMA Models for Operational Planning

Palabras clave: passengers;SARIMA;forecast;flights.Artículo recibido 15 febrero 2023Aceptado para publicación: 05 marzo 2023

DOI: https://doi.org/10.37811/cl_rcm.v7i2.5339

ISSN: 2707-2207

Tipo publicación: Artículo