Unlocking Innovation: Overcoming Challenges and Harnessing Enablers in Agri-Food Systems

The NextGenerationEU investment plan in Italy allocates significant funding for research to foster innovations such as digital agriculture, cellular and gene technologies, and resource recycling within a circular economy. However, the adoption of these technologies by producers and consumers faces social and psychological barriers. Producers often perceive them as costly, both financially and in practical terms. This study explores the challenges Italian farmers encounter when adopting new technologies. We surveyed 684 producers of both permanent and non-permanent crops in Italy. Such surveys are rare, as the National Statistics Bureau (ISTAT) provides census data on farmers but does not examine innovation barriers or enabling factors. While an EU-wide survey addresses innovation barriers in corporations, it excludes farmers, who are often overlooked in innovation studies, particularly in Italy.

Our survey addresses this gap by providing an integrated approach to innovation and food systems research. We gathered data on innovations adopted by farmers over the past three years, as well as their knowledge, adoption (or adoption intent), perceptions, and diffusion within farmers' networks for technologies such as digital agriculture, wastewater reuse, enhanced efficiency fertilizers, nanotechnologies, and blockchain technology.

We found a low correlation (pwcorr 0.4) between the total innovations adopted for sustainability and the new technologies studied. Adoption rates are generally low: 34% of farmers in our sample use enhanced efficiency fertilizers, 16% use digital agriculture, and fewer than 10% have adopted other technologies. Consistent with Diffusion of Innovation theory, membership in farmers' associations predicts higher innovation adoption, especially among smaller farms (interaction effect). Social factors, such as association membership and knowing other farmers who have adopted these technologies, also are strong predictors of adoption of the new technologies studied. In line with the UTAUT model, other key predictors include knowledge and perceptions of technology efficiency, while the main barrier remains cost.