This study investigates farmers' intentions to adopt live streaming e-commerce using the Technology Acceptance Model (TAM) and incorporates government support, platform support, and social learning as additional factors. Based on data from 424 Chinese farmers, the findings reveal that TAM is applicable to assess farmers' intentions to adopt live streaming e-commerce. Government support positively impacts perceived usefulness, platform support positively affects both perceived ease of use and usefulness, and social learning enhances perceived ease of use. The applicability of the TAM varies among different farmer groups: government support has a greater impact on perceived ease of use among traditional farmers, social learning has a stronger effect on perceived ease of use among high-educated farmers, and platform support has a more significant influence on perceived usefulness among experienced e-commerce farmers. These findings suggest that differentiated strategies are needed to promote live streaming e-commerce adoption, with the government providing support and e-commerce platforms offering efficient services and education. A multi-party collaboration model involving the government, platforms, and farmers is essential for the healthy development of rural live streaming e-commerce. The study also highlights the importance of considering external factors such as government support, platform support, and social learning in the TAM framework. The results provide insights into the factors influencing farmers' adoption intentions and the interactions among these factors, offering practical recommendations for policymakers and e-commerce platforms. The study contributes to the theoretical understanding of technology acceptance by validating TAM's applicability to farmers and identifying new influencing factors. It also emphasizes the need for tailored approaches to technology acceptance in different farmer groups.This study investigates farmers' intentions to adopt live streaming e-commerce using the Technology Acceptance Model (TAM) and incorporates government support, platform support, and social learning as additional factors. Based on data from 424 Chinese farmers, the findings reveal that TAM is applicable to assess farmers' intentions to adopt live streaming e-commerce. Government support positively impacts perceived usefulness, platform support positively affects both perceived ease of use and usefulness, and social learning enhances perceived ease of use. The applicability of the TAM varies among different farmer groups: government support has a greater impact on perceived ease of use among traditional farmers, social learning has a stronger effect on perceived ease of use among high-educated farmers, and platform support has a more significant influence on perceived usefulness among experienced e-commerce farmers. These findings suggest that differentiated strategies are needed to promote live streaming e-commerce adoption, with the government providing support and e-commerce platforms offering efficient services and education. A multi-party collaboration model involving the government, platforms, and farmers is essential for the healthy development of rural live streaming e-commerce. The study also highlights the importance of considering external factors such as government support, platform support, and social learning in the TAM framework. The results provide insights into the factors influencing farmers' adoption intentions and the interactions among these factors, offering practical recommendations for policymakers and e-commerce platforms. The study contributes to the theoretical understanding of technology acceptance by validating TAM's applicability to farmers and identifying new influencing factors. It also emphasizes the need for tailored approaches to technology acceptance in different farmer groups.