Recurrence in the evolution of air transport networks

TL;DR

This study introduces a recurrence-based framework to analyze the evolution of air transport networks over time, revealing carrier-specific patterns and abrupt structural changes linked to operational shifts rather than external socioeconomic events.

Contribution

The paper proposes a novel recurrence analysis framework for temporal networks and applies it to US airline data, uncovering unique carrier evolution patterns and abrupt network changes.

Findings

Different carriers show varying autocorrelation and periodicity.

Network structures change abruptly, often due to operational shifts.

Changes are more related to airline operations than socioeconomic events.

Abstract

Changes in air transport networks over time may be induced by competition among carriers, changes in regulations on airline industry, and socioeconomic events such as terrorist attacks and epidemic outbreaks. Such network changes may reflect corporate strategies of each carrier. In the present study, we propose a framework for analyzing evolution patterns in temporal networks in discrete time from the viewpoint of recurrence. Recurrence implies that the network structure returns to one relatively close to that in the past. We applied the proposed methods to four major carriers in the US from 1987 to 2019. We found that the carriers were different in terms of the autocorrelation, strength of periodicity, and changes in these quantities across decades. We also found that the network structure of the individual carriers abruptly changes from time to time. Such a network change reflects changes in their operation at their hub airports rather than famous socioeconomic events that look closely related to airline industry. The proposed methods are expected to be useful for revealing, for example, evolution of airline alliances and responses to natural disasters or infectious diseases, as well as characterizing evolution of social, biological, and other networks over time.