GUARULHOS AIRPORT ANALYSIS: assessing the impact of passenger satisfaction on airports’ non-aeronautical revenue

Abstract

he study presents a case analysis focused on examining the level of passenger satisfaction that influences the non-aeronautical revenue margin of Guarulhos International Airport. The research covers the period from 2014 to 2024, divided into quarterly data for both non-aeronautical revenues and the evaluated scores and criteria. The techniques used included statistical analysis and artificial intelligence, such as Pearson correlation, linear regression, principal component analysis (PCA), and the M5P decision tree model, supported by tools such as Python and Weka, to identify the factors with the greatest impact on revenue. The results showed significant correlations between certain aspects of the passenger experience and the airport’s financial performance. Factors such as the cost-benefit of parking and the reliability of security inspection had a positive impact on revenues, while the quality of Wi-Fi and restroom cleanliness showed a negative influence, possibly due to noise or post-pandemic behavioral changes. It is concluded that the continuous monitoring of services and the use of predictive models support strategic decision-making.