Title: A supply chain risk identification method of foreign trade e-commerce enterprises based on social network analysis

Authors: Huilan Wu

Addresses: School of Foreign Languages, Jingdezhen University, Jingdezhen, 333400, China

Abstract: To improve the efficiency and accuracy of supply chain risk identification, a supply chain risk identification method for foreign trade e-commerce enterprises based on social network analysis is studied. Firstly, obtain supply chain risk indicators for foreign trade e-commerce enterprises and use the LLE-PCA method to reduce the dimensionality of the indicators. Then, using social network analysis method, construct a social network model with different risk indicators interconnected. Finally, degree centrality analysis and proximity centrality analysis are used to obtain the variable values of each indicator in the model, achieving the identification of supply chain risks for foreign trade e-commerce enterprises. The experiment shows that the application of this method for risk identification takes 0.25 s, with a recognition accuracy of 82%. It has high recognition efficiency and accuracy, and the application effect is good.

Keywords: social network analysis; SNA; foreign trade e-commerce enterprises; supply chain; risk identification; LLE-PCA; centrality analysis.

DOI: 10.1504/IJWBC.2025.145140

International Journal of Web Based Communities, 2025 Vol.21 No.1/2, pp.91 - 106

Received: 27 Jul 2023
Accepted: 07 Nov 2023
Published online: 21 Mar 2025 *

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