E-Commerce Payments And SME Growth In China: Key Influencing Factors

This paper proposes a hybrid impact model (HIM) that integrates the technology acceptance model (TAM) and transaction cost theory, and quantifies the dynamic relationship between e-commerce payment factors and small and medium-sized enterprise (SME) growth through computer algorithms. The model relies on computer programming to implement nonlinear operations of four core factors (perceived usefulness, ease of use, privacy/security, and leadership), builds an algorithm framework through six core formulas, and completes computer simulation verification based on 392 Chinese SME data. The results show that HIM performs best in computer simulation tests: the test data R² reaches 0.75, the root mean square error (RMSE) is 0.34, and the sensitivity to outliers is only 0.12, which is significantly better than the multiple linear regression (MLR) and random forest (RF) algorithms. Computer simulation clearly shows that the e-commerce payment adoption index (ECPAI) has the highest growth efficiency when it is 1.5–1.7, and through computer visualization analysis, it is found that privacy/security contributes the most (37%) in the high ECPAI range (1.6–2.0). The study confirmed that perceived privacy and security (correlation coefficient 0.762) derived from computer modeling had the strongest impact on SME growth, and HIM provided a quantitative tool for computer-assisted SME payment strategy optimization.