Bayesian network analysis to investigate the determinants affecting passenger capacity at Kuwait airport

Since its inception in 1960, Kuwait International Airport has played a pivotal role in transforming Kuwait from an oil-centric economy to a prominent aviation hub in the region. This research utilizes Bayesian Network analysis to investigate the determinants affecting passenger (pax) capacity at the airport from 2011 to 2021. Passenger capacity refers to the maximum number of passengers that the airport can accommodate within a specific period, which is influenced by factors such as the number of available flights, aircraft size, and passenger demand. The analysis encompasses aviation data from both scheduled and non-scheduled passenger flights, divided into two distinct five-year periods to capture the changing dynamics influencing the aviation network. In this study, the data sources include official aviation reports, economic indicators such as GDP, population statistics, and fuel price records. The primary data sources for this study include Kuwait Civil Aviation on monthly flight movements. The study focuses on key economic variables such as GDP, population, jet fuel prices, inflation rates, and exchange rates. Findings indicate that in the first half of the decade, GDP was the sole significant factor driving passenger capacity. In the latter half, the impact of population growth and fuel prices became more pronounced. A detailed sensitivity analysis reveals that a 10 % increase in GDP correlates with a 59 % change in passenger capacity over the entire decade. Furthermore, during the period from 2016 to 2021, fuel prices emerged as a sensitive factor, with a 10 % hike resulting in a 33 % rise in passenger capacity. This abstract summarizes the study's objectives and significant findings, underscoring the essential economic factors that have shaped the passenger capacity at Kuwait International Airport over the analyzed period.