Digital agricultural technologies, with their proven potential to enhance productivity, resilience, and resource efficiency, play a key role in achieving food security and sustainable development. However, the adoption of these technologies in developing countries like Iran faces a significant limitation. Focusing on the existing knowledge gap. This study investigates the individual and social determinants of digital technology adoption among Iranian farmers by integrating the Theory of Planned Behavior and the Technology Acceptance Model. We apply this framework to targeted research with farmers of Kermanshah Province in western Iran, using survey data (sample n = 384) analyzed through structural equation modeling. Based on the results, the integrated model demonstrated strong explanatory power. Attitude and perceived behavioral control emerged as the strongest predictors of adoption intention, with attitude itself being largely shaped by perceived usefulness and ease of use. Contrary to expectations, subjective norm exerted no significant direct effect on intention, nor was it influenced by perceived usefulness. These findings reveal that the adoption process in this context is driven primarily by individual assessments of utility and feasibility rather than social pressures. This suggests a critical need to adapt classic adoption frameworks when applied to settings with weaker social capital or less cohesive institutional structures. Consequently, extension strategies should pivot from normative campaigns to approaches that emphasize personalized financial incentives, risk mitigation guarantees, and user-centric technology design.
Alibaygi et al. (2026) studied this question.