Airport Performance Analysis and Forecasting

• Autor(a) principal: Valente, Nuno Rafael
• Data de Publicação: 2017
• Tipo de documento: Dissertação
• Idioma: eng
• Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
• Texto Completo: http://hdl.handle.net/10400.6/7962
• topic: Alisamento Exponencial; Desempenho Aeroportuário; Macbeth; Mcda; Previsão; Domínio/Área Científica::Engenharia e Tecnologia::Engenharia Aeronáutica

Airports are an essential part of air transport system, providing infrastructures to enable the transfer of passengers and freight between the land surface and air vehicles, to store and maintain aircraft and to accommodate other service providers needful to air transportation. Moreover, airports have strategic importance to the regions they serve as they bring wealth, employment opportunities, promote regional tourism and encourage economic development. Over the years, air traffic has grown exponentially without a corresponding investment in airport infrastructures and is now reaching a stage where airports may face congestion due to lack of capacity. Due to these facts, there is a growing pressure to manage the air transport system more efficiently. Therefore, it is of utmost importance to analyse airport performance and predict the development of the factors that may affect it. This study addresses airport performance by predicting it through the passengers and aircraft movements forecasts. For this purpose, airport performance is measured through Measuring Attractiveness by a Categorical Based Evaluation Technique (MACBETH) methodology by adopting Performance Efficiency Support Analysis – Airport Global Benchmarking (PESA-AGB) model. The forecasting method consists of an exponential smoothing technique that could be easily used by airport managers and that allow creating three different scenarios of development. Results show the forecasted number of passengers and aircraft movements at a fictitious airport representative of a major Portuguese airport as well as its consequent performance score. Moreover, it is shown that the weight, empirically assigned by experts, that each indicator has on airport performance may invert when considering the direct impact on other indicators.