In this work, we explore the link between the perception of complexity and the possibility of adopting precision agricultural tools (PATs). Many studies have analysed the role of perception, mostly considering it a determinant of adoption on the same level as other contextual factors. In contrast, this study contributes by assuming that farmers' perceived complexity is the main factor influencing their propensity to innovate and should be analysed on a different level. Starting from this assumption, a new theoretical model is proposed with the aim of studying the “factors–perception of complexity–adoption” (FACOPA) process. To test the validity of our hypothesis, a survey is conducted based on a purposive sample of 285 farmers. First, a linear regression model permits us to identify determinants of the perception of complexity. Then, a multinomial logistic model is used to determine which aspects of perceived complexity may affect the choice to adopt precision farming tools made by three different types of agricultural entrepreneurs: adopters, non-adopters, and planners. First, the linear regression results show that socio-structural variables have a logical relationship with perceived complexity, with age, farm size, the intensity of information and the intensity of work being significant. Then, the multinomial logistic model highlights that non-adopters perceive almost all aspects of complexity as barriers to adoption. Planners show a lower perception of complexity than non-adopters, with complexity being determined by financial and network aspects. The results provide interesting suggestions for policy-makers. Indeed, the FACOPA model offers insights into an intervention framework in which policy measures can be diversified to disseminate PATs based on farmer categories. Non-adopters require a broader set of policy instruments, while planners should be encouraged to become adopters through financial support and the activation of innovation networks.

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Italy is among the most important countries in Europe for milk production. The new European policies encourage a transition towards sustainability and are leading European dairy farms to follow new trajectories to increase their economic efficiency, reduce their environmental impact, and ensure social sustainability. Few studies have attempted to classify dairy farms by analyzing the relationships between the structural profiles of farms and the social, environmental, and economic dimensions of sustainability. This work intends to pursue this aim through an exploratory analysis in the Italian production context. The cluster analysis technique made it possible to identify three types of dairy farms, which were characterized on the basis of indicators that represented the three dimensions of sustainability (environmental, social, and economic sustainability) and the emerging structural relationships based on the structural characteristics of the dairy farms. The classification made it possible to describe the state of the art of the Italian dairy sector in terms of sustainability and to understand how different types of farms can respond to the new European trajectories.

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