a simulation model of credit risk in supply chain finance using a dynamic systems analysis approach

Objectives: this study aims to identify the key factors influencing credit risk in supply chain finance (scf), determine the main subsystems, and present a simulation model for credit risk in scf using a dynamic systems analysis approach.method: the research employs a two-tier supply chain financial model, consisting of a buyer company (core company) and a seller company (supplier) in the pharmaceutical industry. the factoring method is used as one of the scf techniques to construct the supply chain financial model using a dynamic systems analysis approach. vensim software is utilized for the simulation.results: the study identifies the subsystems, key factors influencing credit risk in scf, causal relationships, delays between these factors, and a systemic view of credit risk in scf. the findings show that the credit risk of small and medium-sized enterprises (smes), decreases when they participate in scf. a sensitivity analysis of three key variables was conducted by simulating changes in critical parameters over a five-year period. the results highlight that the financial conditions of both the supplier and the main company, macroeconomic and industry risk, supply chain position, the quality of credit risk management by the lending bank, and the effectiveness of risk intermediaries significantly impact credit risk in scf.innovation: this study is the first in the country to develope a simulation model of credit risk in scf using a dynamic systems analysis approach. it specifically analyzes and evaluates the credit risk of smes (supplier companies) within the context of scf participation.