The triangular structure beyond pairwise interactions affects the robustness of the world trade networks

Unlike hollow triangles formed through pairwise interactions, a filled triangle or two-simplex comprises three nodes that form a group and represent the most fundamental higher-order interaction. To analyze the effects of higher-order triangles on the robustness of world trade networks, we integrate multilateral regional trade agreements and import-export world trade data to construct two-simplex higher-order trade networks. The topological characteristics indicate a significant growth in the scale and complexity of trade networks over time, with a notable decline in 2020. Then, we introduce node attack strategies designed to simulate scenarios where the key countries or regions withdraw from the trade network. It is revealed that network robustness has improved along with size and complexity, although it diminished in 2020. To further explore the factors influencing the changes in network robustness, we generate higher-order synthetic trade networks based on the random simplicial complex (RSC) model and the scale-free simplicial complex (SFSC) model. The synthetic trade networks demonstrate that increasing the average degree enhances robustness, while merely increasing the number of nodes or filled triangles can weaken it. Additionally, scale-free higher-order networks exhibit lower robustness due to vulnerability of the hub nodes, in contrast to the higher resilience of random simplicial complexes. These insights emphasize the importance of fostering multilateral interactions and strengthening ties for network robustness.

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Publication Details

Journal
Chaos An Interdisciplinary Journal of Nonlinear Science
Published
2025-02-01
DOI
https://doi.org/10.1063/5.0245093
Primary Topic
Complex Network Analysis Techniques
Type
article
Field-Weighted Citation Impact
0.00

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article

The triangular structure beyond pairwise interactions affects the robustness of the world trade networks

Wenli Du, Zhuo-Ming Ren, Tongfeng Weng, Yu Lin et al.
Chaos An Interdisciplinary Journal of Nonlinear Science
Complex Network Analysis Techniques
article

The triangular structure beyond pairwise interactions affects the robustness of the world trade networks

Wenli Du, Zhuo-Ming Ren, Tongfeng Weng, Yu Lin, Wan Wang
article en

Abstract

Unlike hollow triangles formed through pairwise interactions, a filled triangle or two-simplex comprises three nodes that form a group and represent the most fundamental higher-order interaction. To analyze the effects of higher-order triangles on the robustness of world trade networks, we integrate multilateral regional trade agreements and import-export world trade data to construct two-simplex higher-order trade networks. The topological characteristics indicate a significant growth in the scale and complexity of trade networks over time, with a notable decline in 2020. Then, we introduce node attack strategies designed to simulate scenarios where the key countries or regions withdraw from the trade network. It is revealed that network robustness has improved along with size and complexity, although it diminished in 2020. To further explore the factors influencing the changes in network robustness, we generate higher-order synthetic trade networks based on the random simplicial complex (RSC) model and the scale-free simplicial complex (SFSC) model. The synthetic trade networks demonstrate that increasing the average degree enhances robustness, while merely increasing the number of nodes or filled triangles can weaken it. Additionally, scale-free higher-order networks exhibit lower robustness due to vulnerability of the hub nodes, in contrast to the higher resilience of random simplicial complexes. These insights emphasize the importance of fostering multilateral interactions and strengthening ties for network robustness.

Chaos An Interdisciplinary Journal of Nonlinear ScienceVol. 35(2)
Hangzhou Normal University (CN), Scuola Superiore Meridionale (IT)
National Natural Science Foundation of China
Partnerships for the goals
Openalex Percentile: Top 97%
Complex Network Analysis Techniques
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