Risk propagation in supply-chain network considering node heterogeneity

Yucheng Chen, Yongxiang Xia and Zhen Hua

Physica A: Statistical Mechanics and its Applications, 2025, vol. 657, issue C

Abstract: In the current highly interconnected global economy, risk propagation within supply-chain networks has drawn significant attention from researchers because of its profound impact. Given the varying risk-propagation capabilities of different firms within the supply chain, we propose a risk-propagation model that considers the heterogeneity between nodes, referred to as the Degree-Dependent Risk Propagation (DDRP) model. We analyze the effects of different heterogeneity parameters on the performance of risk propagation in the supply-chain network and further explore how these effects influence the efficiency of logistics within the supply-chain network. The results indicate that the heterogeneity between nodes significantly increases the vulnerability of the supply-chain network, making it less efficient when facing risk propagation. In a highly heterogeneous network, more nodes become infected, leading to a notable decline in logistics-transportation efficiency, which severely disrupts the normal functioning of the entire supply chain. Our research not only provides a novel theoretical model for risk propagation in supply-chain networks, but also offers valuable practical insights for managers and decision-makers. By identifying and understanding the influence of heterogeneity on risk propagation, decision-makers can formulate more effective risk-management strategies, thereby enhancing supply-chain resilience and efficiency.

Keywords: Complex networks; Supply chain; Heterogeneity; Risk propagation (search for similar items in EconPapers)
Date: 2025
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0378437124007453
Full text for ScienceDirect subscribers only. Journal offers the option of making the article available online on Science direct for a fee of $3,000

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:phsmap:v:657:y:2025:i:c:s0378437124007453

DOI: 10.1016/j.physa.2024.130236

Access Statistics for this article

Physica A: Statistical Mechanics and its Applications is currently edited by K. A. Dawson, J. O. Indekeu, H.E. Stanley and C. Tsallis

More articles in Physica A: Statistical Mechanics and its Applications from Elsevier
Bibliographic data for series maintained by Catherine Liu ().