Frontiers in Sustainable Food Systems (May 2024)
Uptake of climate-smart agricultural technologies and practices: a three-phase behavioral model
Abstract
Climate change due to human activities is a reality and a growing threat to global food security. The trend of increasing temperature and decreasing rainfall in Iran shows climate warming, the result of climate change in Iran. Climate-smart agriculture (CSA) is an approach to developing new agricultural practices that support food security against climate change. The purpose of this study was to design a behavioral model for using CSA technologies in three phases: cognitive, motivational, and volitional, using the theories of planned behavior, self-determination, and social cognition. This research is the first to combine behavioral models to understand the application of CSA technologies. The research method in this study was quantitative and non-experimental. The statistical population included 800 wheat farmers from the city of Nazarabad in the Alborz province of Iran. A sample size of 260 people was determined using the Cochran formula. Appropriate stratified sampling was selected as the sampling method. Wheat farmers were then randomly selected in each village through proportional assignment. The research data was collected through a cross-sectional survey and a questionnaire. The models and hypotheses were tested using structural equation modeling. The statistical results confirmed the theoretical model and 15 research hypotheses. Additionally, the estimated field model explained about 62% of the variance in the behavior of using CSA technologies. Therefore, cognition, motivation, and volition effectively shape the behavior of using CSA technologies. In the cognitive phase, environmental concerns have the greatest impact on attitude toward the behavior of using CSA technologies (β = 0.714). In the motivational phase, personal norms have the most impact on the intention to use CSA technologies (β = 0.643). Finally, in the volitional phase, the intention to use CSA technologies has the highest impact on the behavior of using CSA technologies (β = 0.386). The increase in the guaranteed purchase price of wheat and paying soft and long-term loans by the policymakers will lead to an increase in the intention of wheat farmers to use CSA technologies.
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