<p>In recent years, the rapid development of the market economy has led to increased competition among e-commerce enterprises, which is now largely determined by the competition among supply chains. Efficient supply chain management can effectively reduce warehousing and distribution costs, thereby enhancing profitability. However, supply chain risks are still prevalent, and traditional risk early-warning mechanisms are no longer sufficient to meet the needs of e-commerce transactions. To address this issue, this paper proposes an intuitionistic fuzzy TOPSIS model based on combined weighting to assess and analyze e-commerce supply chain risks. Specifically, the study first examines the characteristics, advantages, and risk identification principles of e-commerce supply chain management through practical research to identify the key risk factors. Subsequently, the intuitionistic fuzzy weighted arithmetic average operator is employed to aggregate expert evaluations, resulting in an intuitionistic fuzzy aggregated decision risk matrix. To improve the comprehensiveness and accuracy of risk assessment, subjective weights are calculated using the intuitionistic fuzzy SWARA method, while objective weights are derived through a normal distribution approach. The combined weighting method integrates these two approaches, overcoming the limitations of single-weighting methods and utilizing multi-source information for more scientific and balanced weight allocation. The ranking of risk factors is then determined based on their relative closeness to ideal solutions, which facilitates targeted risk mitigation measures. Finally, a case study of a Chinese e-commerce platform is conducted, and sensitivity analysis is performed to validate the model’s accuracy and effectiveness.</p>