Optimizing Airport Operations: A Study on Passenger Flow and Terminal Efficiency

Abstract

As global air travel rebounds and expands, optimizing airport operations has become a critical priority for enhancing terminal efficiency and improving the passenger experience. This study investigates the impact of key passenger flow variables—check-in time, security screening duration, gate queue length, and the use of self-service technologies—on operational outcomes such as terminal throughput, flight delays, and passenger satisfaction. Using a quantitative cross-sectional approach, data were collected from two international airports and analyzed through descriptive statistics, Pearson correlation, multiple linear regression, and ANOVA, with visualization via heat mapping. Findings revealed that while average processing times were within expected ranges, correlations between flow variables and performance metrics were weak. Regression analysis indicated that none of the independent variables significantly predicted throughput, and ANOVA showed no major differences in flow efficiency between the two airports. Notably, the use of self-service technology did not enhance throughput as expected, suggesting potential implementation gaps. The study concludes that airport efficiency is influenced by systemic factors beyond isolated procedural metrics. It recommends adopting holistic operational strategies, improved technology integration, and collaborative decision-making models. Future research should explore multi-variable interactions and include qualitative insights to inform data-driven, scalable airport management practices.