Abstract
Abstract
We formulate and implement a new metric for identifying multiple airport regions (MARs) around the world, based
on the temporal distance between airports. This metric, opposed to existing studies based on spatial distance, takes
into account the real travel time between airports of latent passengers and their journeys via ground transportation.
We investigate a variety of properties of the newly built MARs network at the global scale for the year 2015, including
the importance of MARs in global air transportation, similarity clustering, destination overlap, and airport roles inside
a MAR. Commonalities and differences to the simplified spatial distance are identified.
We formulate and implement a new metric for identifying multiple airport regions (MARs) around the world, based
on the temporal distance between airports. This metric, opposed to existing studies based on spatial distance, takes
into account the real travel time between airports of latent passengers and their journeys via ground transportation.
We investigate a variety of properties of the newly built MARs network at the global scale for the year 2015, including
the importance of MARs in global air transportation, similarity clustering, destination overlap, and airport roles inside
a MAR. Commonalities and differences to the simplified spatial distance are identified.
| Original language | English |
|---|---|
| Pages (from-to) | 84-98 |
| Number of pages | 15 |
| Journal | Transportation Research, Part E: Logistics and Transportation Review |
| Volume | 101 |
| DOIs | |
| Publication status | Published - 2017 |