Application Of Stochastic Processes In Tamilnadu Airport Connectivity

Abstract

The rapid growth of air transportation in Tamil Nadu has increased the need for robust analytical frameworks to evaluate airport connectivity under uncertainty. Airport operations are inherently stochastic due to fluctuating passenger demand, variable flight schedules, and operational disruptions, rendering deterministic connectivity measures insufficient. This study develops and applies a stochastic network-based Airport Connectivity Quality Index (ACQI) to assess and compare airport connectivity across Tamil Nadu between 2017 and 2022. The proposed methodology integrates stochastic process modeling with a hierarchical airport network representation, incorporating flight frequency, destination diversity, and airport importance weighted by normalized passenger throughput. Passenger arrivals are modeled probabilistically, and airport connectivity is quantified as an expected value measure using the ACQI framework. Empirical analysis is conducted using annual flight schedules, passenger volumes, and seat capacity data obtained from the Airports Authority of India. The results reveal a highly centralized connectivity structure dominated by Chennai International Airport, which recorded an ACQI value of 168.39 in 2022, placing it in the excellent connectivity category. In contrast, regional airports such as Coimbatore (ACQI = 7.85), Madurai (6.12), Tiruchirappalli (5.85), and Tuticorin (5.77) exhibit limited to moderate connectivity. Despite these disparities, connectivity improved across all airport categories during the study period. Medium hub airports experienced the highest relative growth in connectivity, with ACQI values increasing by 92.01% between 2017 and 2022, followed by small hubs (89.32%) and large hubs (88.23%). A comparison of connectivity growth with capacity indicators shows that increases in ACQI consistently outpaced growth in both scheduled domestic flights and available seat capacity. This finding indicates the presence of capacity discipline, whereby airlines enhanced network connectivity through scheduling efficiency and route optimization rather than proportional capacity expansion. Overall, the study demonstrates that stochastic ACQI modeling provides a realistic and scalable approach for evaluating regional airport connectivity and offers policy-relevant insights for infrastructure planning, network optimization, and sustainable air transport development.