Determinants of farmers’ intention to adopt agroforestry in Iran using a technology acceptance model and valence framework

Agroforestry is frequently presented as a sustainable land management option, yet its adoption remains limited in many regions. Understanding the determinants of farmers’ adoption decisions is therefore essential from a behavioral perspective. This study investigates the factors shaping farmers’ intention to adopt agroforestry by integrating the Technology Acceptance Model (TAM) with the Valence Framework (VF). A cross‑sectional survey was conducted, and the proposed model was tested using Partial Least Squares Structural Equation Modeling (PLS‑SEM). The integrated model explained 69.3% of the variance in adoption intention. Attitude, perceived usefulness (PU), and perceived trust (PT) emerged as the strongest positive predictors, while perceived risk (PR) and perceived cost (PC) showed significant negative effects. Perceived ease of use (PEU) also contributed positively, though to a lesser extent. These results provide empirical evidence on the relative importance of cognitive and evaluative factors in shaping farmers’ behavioral intentions. The findings contribute to theoretical discussions on agroforestry adoption and offer a basis for future research examining how these determinants operate across different contexts.