Abstract
Several studies in the past have explored the relationship between various airport related variables and operations (Javanmard et al., 2024; Khireldin & Law, Li & Trani, 2017; Mott et al., 2016). This study delves into the impacts of airport design, runway characteristics, services, classifications, and comprehensive data sets on the operational volume of Part 139 certificated airports in the United States. Employing a hierarchical multivariate regression model, the research addresses the influence of various airport-related factors on operational volumes. Initial findings indicated significant associations between several key variables such as and operational volume, with runway length and the scale of air carrier and general aviation operations being particularly influential. The research also critically evaluated and refined the selection of variables based on statistical significance and multicollinearity, leading to a focused analysis on the most impactful factors. Despite initial assumptions that all proposed variables would be significant, the study refined these inputs to better align with observed data, enhancing the model's predictive accuracy and reliability. This paper provides valuable insights into airport operational dynamics, supporting future policy decisions and strategic planning in airport management.
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