Beyond adoption: Understanding data use behavior in digital agriculture

Digital Agriculture Technologies (DATs), including precision agriculture systems, IoT-enabled sensors, and digital farm management platforms, are increasingly being adopted to support data-driven decision-making in agriculture. However, the benefits of DATs depend not only on technology adoption but also on producers’ effective use of DAT-generated data in farm decision-making processes. Using unique survey data from 587 commercial crop and beef producers across Western Canada, this study examines the factors associated with post-adoption data-use behavior by measuring data-use intensity among DAT adopters. The results show that higher risk perceptions toward technology, dependence on social support, and limited digital literacy are associated with an 8.1, 4.3, and 9.8 percentage-point lower probability of high data-use intensity, respectively. In contrast, perceived usefulness of data, altruistic behavior, and openness/proactive behavior are associated with a 20.4, 8.7, and 14.9 percentage-point higher probability of high data-use intensity , respectively. The findings suggest that social and non-pecuniary motivations play an important role in shaping post-adoption engagement with DAT-generated data. By contrast, our sample shows that trust, data governance concerns, and lack of facilitating conditions, such as technical support, are not statistically significant among existing adopters, suggesting that these factors may be more relevant during the pre-adoption stage. This study contributes to digital agriculture literature by shifting attention from technology adoption to post-adoption data utilization. The findings imply that policies and industry strategies focused solely on increasing DAT adoption may be insufficient; enhancing producers’ digital skills, perceived value of data, and decision-support capabilities is essential to realizing the full benefits of digital agriculture technologies.