Understanding Chinese Farmers’ Behavioral Intentions to Use Alternative Fuel Machinery: Insights from the Technology Acceptance Model and Theory of Planned Behavior

Mitigating greenhouse gas emissions and reducing fossil fuel dependence have heightened interest in alternative fuels, particularly in agriculture, a key energy-intensive sector. This study investigates the use of the Technology Acceptance Model and the Theory of Planned Behavior to analyze Chinese farmers’ behavioral intentions to adopt alternative fuel machinery. In 2023, a total of 281 full-time farmers were sampled from Jiangsu, Sichuan, and Hebei provinces, followed by path analysis conducted using PLS-SEM. The results underline that perceived usefulness β = 0.369, p < 0.001, and social norms β = 0.185, p < 0.001 are strong drivers for the adoption of alternative fuel machinery, while perceived barriers to operate and infrastructure gaps act as inhibitors. Also, perceived benefits β = 0.235, p = 0.002, and perceived behavior control β = 0.157, p = 0.027 positively predict behavior intentions. This thus suggests that improvement in the technological infrastructure and increasing farmers’ awareness of the practical and economic benefits of alternative fuel machinery could result in a serious increase in adoption rates. This study does have weaknesses, as its focus on 50 mid-sized farms in the Midwest and utilization of self-reported data may limit the generalizability of its findings. This study, however, has major implications for policy and manufacturers to underscore the fact that targeted interventions through subsidies, training programs, and infrastructural development would be necessary to permit a transition toward sustainable energy in agriculture.