Modeling Supply Chain Finance Resilience with a Complex Adaptive SEIJR Framework

Yimeng Ye, Danqin Huang, Ziyue Li, Shujian Ma () and Wanwan Xia ()
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Yimeng Ye: School of Mathematical and Physical Sciences, Nanjing Tech University, 30 South Puzhu Road, Nanjing 211816, China
Danqin Huang: School of Mathematical and Physical Sciences, Nanjing Tech University, 30 South Puzhu Road, Nanjing 211816, China
Ziyue Li: School of Mathematical and Physical Sciences, Nanjing Tech University, 30 South Puzhu Road, Nanjing 211816, China
Shujian Ma: School of Mathematical and Physical Sciences, Nanjing Tech University, 30 South Puzhu Road, Nanjing 211816, China
Wanwan Xia: School of Mathematical and Physical Sciences, Nanjing Tech University, 30 South Puzhu Road, Nanjing 211816, China

Mathematics, 2025, vol. 13, issue 12, 1-24

Abstract: This study develops a novel framework for supply chain financial resilience (SCFR) by integrating complex adaptive systems theory with supply chain finance and resilience concepts. To explore how disruption risks propagate through the supply chain, we propose an SEIJR epidemic model that categorizes node enterprises into five distinct states: susceptible (S), exposed (E), infected (I), quarantined (J), and recovered (R). Transitions between these states are captured using differential equations. Through numerical simulations linking this epidemiological approach to financial resilience metrics, we demonstrate several key findings: first, disruption risks temporarily reduce resilience; second, properly managed risk propagation through timely isolation and effective mitigation can transform disruptions into opportunities for systemic improvement; third, isolation measures need to work alongside recovery mechanisms to significantly improve the overall resilience of supply chain finance. Our results show that optimal isolation strategies enable the system to reach a risk-free equilibrium while simultaneously elevating the supply chain’s long-term financial resilience above initial levels. These findings offer theoretical and practical guidance for dynamic, adaptive risk management strategies in supply chain finance. Empirical validation and other research topics will be explored in subsequent studies.

Keywords: complex adaptive; SEIJR; supply chain finance; resilience (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2025
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