In recent years, with the booming development of the B2C cross-border e-commerce industry, the supply chain of B2C cross-border e-commerce faces many potential risk factors, which must be prevented. To solve this problem, this paper studies the supply chain risk factors of B2C cross-border e-commerce and puts forward avoidance strategies. First, the fitness network model of a dual local world is constructed by combining the fitness model with the local world model. Then, the fitness network model of the dual local world is verified by the risk dynamics simulation model to fit the actual network situation. On this basis, the SIRS virus transmission model is constructed to simulate the risk transmission of the B2C cross-border e-commerce supply chain, and the evaluation index system of the supply chain risk immunity ability and external risk intensity are established according to the supply chain risk immunity ability and external risk intensity. AHP is used to calculate the factors that have the greatest influence on supply chain risk immunity and external risk intensity. The results show that: from the point of view of the enterprise’s own risk immunity, it is more necessary to ensure the stability of the company’s capital and to establish a perfect risk monitoring and coping mechanism to avoid risks. From the perspective of enterprise external risk intensity, the risk should be avoided from two aspects of transaction security and logistics.

The era of digital economy has spawned new factors of production represented by big data. Data-driven sustainable growth and innovative development is the main line of enterprise digital transformation. In view of the uncertainty of supply chain demand, the optimization of supply chain management under the influence of carbon tax policy is studied from the low-carbon perspective. By introducing the fuzzy theory and a membership function to describe the need for uncertainty, a supply chain optimization model considering the influence of carbon emissions is constructed. Carbon tax policy is regarded as the constraint condition of external production. In the case of fuzzy cost changes, the optimization decision of enterprise supply chain management under carbon tax policy is explored. A trapezoidal fuzzy number is used to determine model fuzziness, and the trapezoidal fuzzy number combined with a genetic algorithm is used to solve the model. Furthermore, taking a certain enterprise as an example, the validity of the model is verified by the mathematical programming model method, considering the data driven and taking the data as the means of production.