Centrality and connectivity analysis of the European airports: a weighted complex network approach

ABSTRACT

This study aims to reveal the structure of the European Airport Network (EAN) using concepts from complex network theory by utilising 2019 passenger data collected from Eurostat. Initially, the EAN was explored by computing connectivity and centrality measures and their correlations. The community structure of the EAN was also examined by modularity maximisation using the relatively new Leiden algorithm. When the network was compared with simulated models, it was observed that the EAN had small-world and scale-free properties. To measure the hub performance of the airports, their binary betweenness centrality was compared with a weighted betweenness measure employing the ratio of geographical distance to passenger traffic between the nodes. A significant difference was observed between the two centrality measures.

KEYWORDS:

• European airport network
• complex network
• community detection
• weighted betweenness

Disclosure statement

No potential conflict of interest was reported by the author(s).

Notes

1 Austria, Belgium, Bulgaria, Croatia, Cyprus, Czechia, Denmark, Estonia, Finland, France (overseas departments of France are also included: French Guiana, Guadeloupe, Martinique, Mayotte, Reunion), Germany, Greece, Hungary, Iceland, Ireland, Italy, Latvia, Lithuania, Luxembourg, Macedonia, Malta, Montenegro, Netherlands, Norway, Poland, Portugal, Romania, Serbia, Slovakia, Slovenia, Spain, Sweden, Switzerland, Turkey, United Kingdom.