Sistemas digitais de gestão na agricultura - benefícios e desafios na perspectiva dos produtores

Abstract

Agriculture 4.0 holds the potential to reduce costs, optimize resource allocation, and increase productivity through the incorporation of emerging technologies. However, many farmers still display resistance to adopting such innovations. Among them, Farm Management Information Systems (FMIS) stand out for enabling integrated management of agricultural activities, thereby contributing to operational efficiency. In this context, the present dissertation sought to identify the factors influencing farmers’ adoption of FMIS, analyzing both the perceived benefits and the barriers that hinder their implementation. Between August and November 2023, a field survey was conducted with 103 farmers. The farms were located in the macro-regions of Dourados—including the municipalities of Dourados, Maracaju, Rio Brilhante, and Aral Moreira—and Corumbá—including Bonito, Guia Lopes da Laguna, Jardim, and Nioaque. Data analysis was performed using a PROBIT regression model. The results indicated that variables such as technical support, infrastructure, and investment capacity exerted a positive and significant effect on FMIS adoption, reinforcing the importance of public policies and incentive strategies to expand their implementation. Conversely, barriers such as risk aversion and lack of trust in the technology reduced the likelihood of adoption, in line with the literature highlighting uncertainty regarding benefits and perceptions of complexity as critical obstacles. Among the individual characteristics of farmers, education level showed a positive and significant impact, whereas age exhibited no statistical relevance in the model. Furthermore, farmers’ perceptions regarding improvements in productivity and product quality were not decisive factors for FMIS adoption, suggesting that those seeking productivity gains may instead turn to other technological innovations, such as agricultural mechanization and biotechnology. The adjusted model presented robust statistical measures, demonstrating the adequacy of the factors analyzed. The findings of this research are expected to contribute to a better understanding of the challenges and opportunities in FMIS adoption, providing valuable insights for researchers, technology developers, and policymakers. Based on this knowledge, it becomes possible to design more effective strategies to enhance adoption, ensuring that FMIS are developed in alignment with the needs and realities of farmers.