Promoting the clean energy transition in rural areas is essential for achieving China’s “dual carbon” goals and advancing rural revitalization, with important implications for ecological sustainability and household welfare. However, empirical evidence on rural household energy transitions remains limited, largely due to the scarcity of high-quality micro-level data. Using household survey data from Jiangxi Province, this study applies binary and ordered Probit models to examine the mechanisms underlying rural households’ clean energy adoption and usage intensity. The results indicate that modernity-related mechanisms, including education level and non-agricultural employment experience, as well as capability-based mechanisms such as participation in commercial and industrial activities, significantly increase both the probability of adopting clean energy and the intensity of its use. By contrast, identity-based mechanisms, including party membership and village cadre status, do not exhibit statistically significant effects on adoption decisions, suggesting a limited role. In addition, proximity-related factors reflecting transportation accessibility and infrastructure conditions exert the strongest influence on usage intensity. Marginal effects analysis supports these findings, while heterogeneity analysis reveals clear age-based differences: younger households respond more strongly to modernity and accessibility, whereas older households rely primarily on economic capacity and logistical convenience. This study underscores the importance of infrastructure conditions and household endowments in shaping rural clean energy transitions and offers policy-relevant insights for promoting inclusive and low-carbon household energy use in China and other developing economies.
Xu et al. (2026) studied this question.