Introduction: As an important ICT-enabled business model, rural e-commerce has attracted growing attention, yet existing studies predominantly focus on binary adoption while overlooking heterogeneity in farmers’ participation depth, participation breadth, and platform choice. This study examines the multidimensional characteristics of farmers’ e-commerce participation. Methods: Using data from 2,508 farm households in the 2020 China Rural Revitalization Survey, this study examines factors associated with four dimensions of e-commerce participation and uses ISM to identify the hierarchy of factors associated with participation decisions. Results: (1) E-commerce training is positively associated with participation decision, depth, and breadth and with the probabilities of choosing social and traditional e-commerce. The household head’s education is positively associated with participation decision, depth, and breadth and negatively associated with the probability of remaining offline. In contrast, age is negatively associated with participation decision and depth and with the probabilities of choosing social and traditional e-commerce. (2) Cultivated land area is positively associated with participation decision and depth and with the probabilities of choosing social and traditional e-commerce. Organizational participation is positively associated with participation decision and depth, while average household education is positively associated with participation decision, depth, and breadth. Village e-commerce service stations are positively associated with participation decision and depth and with the probability of choosing social e-commerce. Local non-farm industrial development is positively associated only with participation breadth. (3) Within the ISM hierarchy of factors associated with participation decisions, e-commerce training is identified as a surface direct factor; organizational participation and village e-commerce service stations as shallow indirect factors; cultivated land area and average household education as middle-level indirect factors; and the household head’s age and education as deep-seated root factors. Discussion: These findings demonstrate the multidimensional nature of farmers’ e-commerce participation and show that the same factor may have differentiated associations across dimensions. Policies should therefore shift from general encouragement to dimension-specific support through targeted training, organizational services, village e-commerce facilities, resource matching, and locally adapted industrial support.

Based on data from the 2020 China Rural Revitalization Comprehensive Survey, this study uses a sample of 2508 farm households from 10 provinces to empirically examine the effect of farmers’ e-commerce participation on common prosperity and its underlying mechanisms. The benchmark regression results indicate that farmers’ e-commerce participation significantly promotes common prosperity. The findings remain robust after a series of robustness checks, including propensity score matching (PSM), Tobit estimation, instrumental variable approaches, and alternative measures of the core explanatory variable. Heterogeneity analysis indicates that farmers’ engagement in e-commerce business has a significantly positive effect on common prosperity in the eastern, central, and western regions, with the largest estimated effect observed in the central region. Moreover, farmers’ engagement in e-commerce business significantly enhances common prosperity across groups with different income levels and average household educational attainment, with larger estimated effects among low-income households and those with lower average education levels, indicating greater benefits for relatively disadvantaged groups. Mechanism analysis results indicate that farmers’ participation in e-commerce operations mainly promotes common prosperity through two pathways: improving rural credit accessibility and enhancing information acquisition capabilities.