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In this review, we identify the key drivers that affect the intention to adopt Precision Agriculture (PA) technologies. Research articles concerning the adoption of PA were collected and subdivided into two groups: (1) ex-post assessments that make use of utility-based models, and (2) ex-ante assessments that make use of predictive models. Principal classes of constructs were identified and utilized to interpret what factors promoted the use of PA technologies by farmers. Three classes of drivers influencing PA adoption are presented. This review confirms the necessity to focus on the design of an appropriated adoption process and on innovation's features.
Pierpaoli et al. (Tue,) studied this question.