Industrial and agricultural activities in the world have led to an increase in the concentration of greenhouse gases such as carbon dioxide, methane and nitrogen oxide and have caused the earth's climate to become warmer. This phenomenon has caused climate change and has changed the thermal and rainfall patterns. Climate change in Iran in recent years has caused a decrease in rainfall and an increase in temperature and continuous droughts. Agricultural production in Iran has been affected by climate change and has faced a decrease in the production of crops such as wheat. Therefore, according to the government's policy of self-sufficiency in wheat production and the establishment of sustainable food security in the country, it is necessary to use climate smart agricultural technologies to sustainably increase agricultural productivity, Adapting and resilience of agriculture to climate change and reduction greenhouse gases emission from agriculture. The purpose of this study was to design a behavioral model for the use of climate smart agricultural technologies with an emphasis on motivation. The research method was quantitative, in terms of practical purpose, and research data was collected through a cross-sectional survey.The conceptual model was designed using the theory of planned behavior and the theory of norm activation. Bayesian structural equation modeling was used to test the model and hypotheses. The statistical population of this research was 800 wheat farmers of Nazarabad city, Alborz province. The sample size was calculated using Cochran formula 260 people, and stratified random sampling method with proportional assignment was determined as the sampling method. A researcher-made questionnaire was used to collect research data. The validity of the questionnaire was confirmed through agricultural extension and education experts, and its reliability was also confirmed through the pre-test and calculation of Cronbach's alpha coefficient. The findings of the research show that subjective norms, personal norms and perceived behavioral control related to the use of climate smart agricultural technologies have a significant effect on the intention to use these technologies. While the attitude towards the use of climate smart agricultural technologies do not have a significant effect on the intention to use these technologies. The variable of intention to use climate smart agricultural technologies also has a significant effect on the behavior of using these technologies.
