Institute of Transportation, MOTC

      Air connectivity in general can be defined as the ability and ease for passengers and freight to reach destinations through air transport. It is crucial for facilitating trade, tourism, investment, and economic growth, and a good index to measure the performance is valuable for evaluating the efficiency of airports. In the literature, themainstream approach, the network quality models, involves a set of sophisticated rules to convert the flight schedules into a connectivity index of airports in terms of the flight counts, which are adjusted by several factors (such as seat capacity or transit
time). However, this mature approach is probably more suitable for the cases with frequent service and strong competition, and its application to remote areas is tricky and potentially problematic. Sharing with some similarity with the concept of the Data Envelopment Analysis (DEA), this study has developed a mathematical programming model to define a new air connectivity index, which considers the airline network topology, the flight schedule information, the impact of destination airports, and the flexibility on weighing the related factors. The numerical examples were based on the
cases in Central Asia and the Pacific, and the results verify the usefulness of this novel approach.