Supplementary file 1_Assessing rural sustainability in Guoliang village, China: an expectation livelihood prophecy approach.docx

Rural sustainability is key to maintaining prosperity in developed rural areas, yet many existing evaluation methods focus on material resources while overlooking villagers’ perceptions. This study introduces an ecological–livelihood–perception (ELP) model that extends the sustainable livelihoods framework (SLF) by refining its natural capital dimension to explicitly incorporate ecological quality and villagers’ environmental perceptions, alongside a psychological perception derived from a self-fulfilling prophecy theory. We conducted a structured survey of 100 households in Guoliang village. Then, 21 standardized indicators spanning the natural, financial, physical, social, human, and ecological dimensions were introduced to evaluate the survey data. After reliability screening, principal component analysis (PCA) was applied to construct a single composite score for each capital, capturing the dominant variance in the data without multicollinearity. PCA combined with entropy-based weighting was applied to reduce collinearity and derive indicator weights. Descriptive results show that normalized indicator means range from 0.15 to 0.86, and indicator weights are relatively balanced, ranging from 0.044 to 0.051, with the highest-weight indicator reaching 0.051. The sustainable individual perception (SIP) index was calculated from qualitative items and was linked to the six capital scores through an ordinary least squares regression. The results reveal a threshold pattern: once a basic level of natural capital is met, it leads to further gains, especially in social and ecological assets, which are strongly associated with higher psychological optimism. Households exhibiting high SIP consistently possess balanced and multidimensional capital portfolios, whereas those with low SIP show deficits across most dimensions. The ELP model, therefore, provides a more comprehensive tool for rural sustainability evaluation by integrating objective livelihood assets with subjective perceptions, offering practical insights for targeted policy interventions and development strategies.