Understanding Farmers’ Adoption of Sustainable Agriculture Innovations: A Systematic Literature Review

Adoption of sustainable agriculture innovations is acknowledged to be an effective response to agro-ecological challenges, such as climate change, pests, drought, natural catastrophes, and food insecurity. However, its level of dissemination is still low across the world, particularly in the Global South. There is a need for a better understanding of the adoption determinants of these innovations in order to enhance them. This paper presents a systematic literature review focused on the use of sociopsychological determinants to understand the adoption of sustainable agriculture innovations, combining conventional bibliometric analysis with the method of vote-count. This method enabled an evaluation of the ability of the determinants considered by the models, as well as respective sociopsychological constructs, to explain the innovation adoption. Our results show a significant growth in the research employing theory and models built on sociopsychological factors to understand the decision-making processes undertaken by farmers in the context of the adoption of sustainable agriculture innovations. The development of statistical models and techniques, such as the structural equation model (SEM), has facilitated the inclusion of a growing set of sociopsychological variables. However, our review highlights that the selection of the sociopsychological constructs used by research to explain farmers’ adoption of sustainability innovations relies mainly on constructs defined for other decisional contexts, such as the adoption of innovations by firms in other sectors. Hence, the low ability evidenced by the models to explain farmers’ adoption behavior is due to a poor selection of constructs. The review highlights that this poor selection is a result of repetition of constructs, such as attitude, subjective norms, and little inclusion of other relevant constructs such as knowledge. The paper suggests the need for a better selection of the innovation determinants and measurement of respective constructs adjusted to the case of agriculture and the specificities of the diverse geographical farming contexts.