Psychosocial drivers of conservation agriculture adoption in Iran

• Place attachment, environmental attitude, social capital, awareness, and concerns significantly drive Conservation Agriculture adoption in Iran. • Structural Equation Modeling revealed these factors explained 74.1% of adoption variance. • Findings guide policymakers to strengthen social capital and awareness for sustainable soil management. Conservation Agriculture (CA) is a sustainable approach to natural resource management that reduces soil erosion, enhances water infiltration, improves soil structure, and increases productivity through reduced tillage, retention of crop residues, and crop rotation. In addition to lowering production costs, CA supports long‑term agricultural sustainability. Despite these benefits, adoption remains limited among farmers. This study investigates the factors influencing CA adoption among Iranian farmers. The statistical population comprised 37,500 farmers in Shushtar County, Khuzestan Province (southwestern Iran), of whom 380 were selected using stratified sampling with proportional allocation based on the Krejcie and Morgan table. An exploratory conceptual framework was developed from the literature, and data were analyzed using structural equation modeling (SEM). Results indicate that place attachment (PA), environmental attitude (EA), social capital (SC), environmental awareness (EAW), and environmental concern (EC) all exert positive and significant effects on CA adoption. Together, these variables explained 74.1% of the variance in CA acceptance, demonstrating the strong explanatory power of the proposed model and its contribution to the literature on sustainable agriculture adoption. Among the predictors, SC and EAW had the greatest impact. By providing a comprehensive framework that integrates social and environmental dimensions, this study offers new insights for policymakers and planners seeking to promote soil conservation and sustainable agricultural development. The principal innovation lies in quantifying the contribution of social and environmental variables to CA adoption and presenting a model with high explanatory capacity applicable to other regions with similar conditions.