Analysis of Network Robustness in Weighted and Unweighted Approaches: A Case Study of the Air Transport Network in the Belt and Road Region

Abstract

Aviation transport is one of the most important and critical infrastructures in today’s global economy. Failure in its proper operations can seriously impact regional economic development, which is why it is important to evaluate network robustness. Previous analyses of robustness have mainly been conducted with an unweighted approach. In the development of air transport, however, the demand for route configuration has gradually decreased, while the demand for flight adjustments has increased. Consequently, the aviation network has developed unevenly, so adhering to a uniform approach for evaluating network robustness may lead to inaccurate results. Therefore, we examined which centrality sequence is the most sensitive to network robustness in both unweighted and weighted approaches. The air transport network selected for the case study comprised the six subregions of the Eurasian landmass of the Belt and Road region. The study results showed the following: (a) in the network constructed as an unweighted one, betweenness, and degree centrality had higher priorities in preserving network functionalities than eigenvector and closeness centrality; (b) in the network constructed as a weighted one, recursive power had a higher priority in preserving network functionalities than recursive centrality; and (c) no particular centrality measurement had a significant advantage in representing the totality of robustness. The betweenness centrality sequence was sensitive to the average shortest path length and global efficiency; the recursive power sequence was sensitive to the clustering coefficient, while degree centrality was sensitive to graph diversity. The findings of this study support the decisions about managing air transportation in the Belt and Road region.

Centrality anomalies for the domestic air transportation networks in the USA: an empirical benchmark

“…Finally, like the betweenness, eigenvector centrality is also the benchmark of identifying important nodes [ 27 , 51 , 52 ] and analyzing the robustness [ 43 , 50 , 53 ] of networks. Zhang et al [ 53 ] pointed out wrong results would be caused as evaluating the network robustness without considering the link weights. This could be attributed to the anomalous centralities actually, which misestimate the role of nodes.…”

“…This could be attributed to the anomalous centralities actually, which misestimate the role of nodes. Our work has the directed significance to the researches of measuring the influence of nodes [ 30 , 31 ], evaluating the robustness [ 43 , 50 , 53 ] and modeling the dynamical process [ 54 ] with the eigenvector centrality. In addition, other real networks embedded in two-dimensional space (such as bus networks [ 29 , 55 ], railway networks [ 56 ], power grid networks [ 57 ]) might also have similar behaviors of eigenvector centralities, empirical investigations on them would generalize our conclusions to other real systems.…”

The Construction of an Aircraft Control Multilayer Network and Its Robustness Analysis

“…In addition, Ren and Li [34] compare the characteristics of air trafc networks between China and the United States. Over the past two years, the robustness of aviation networks has also received attention [35,36].…”

Research on Deep Integration of the “Belt and Road” Aviation Network Based on Community Structure from the Perspective of China

“…Te "Belt and Road" countries are from Asia, Europe, and Africa, so the distribution of the international airports and routes is endowed with distinct regional features. China airport neither has close links with air transport hubs in the "Belt and Road" countries nor leads a prominent position in the "Belt and Road" aviation network [4]. To enhance economic, trade, and personnel exchanges between the "Belt and Road" countries, it is necessary to integrate and optimize the existing aviation network and promote its deep integration [5].…”