Digitalization and digital technologies: The obstacles to adaptation among Hungarian farmers
Abstract
Research background: Digital technologies aim to enhance efficiency, competitiveness, and sustainability. Despite ongoing efforts, Hungary is encountering various challenges in digitalization. This research seeks to investigate the potential of digital technologies in addressing these challenges, with a particular focus on precision agriculture technologies (PA).
Purpose of the article: This study explores the utilization of digital technologies among 81 agricultural and food companies in Hungary. The study evaluates the use of advanced and less advanced digital technologies and their impact on rural areas. Additionally, the research seeks to understand the economic and social impacts resulting from the adoption of these technologies, focusing specifically on precision farming.
Methods: The study uses advanced clustering methods to categorize agricultural companies based on their use of digital technology. The research employed the two-step clustering method, which has been recognized for its robustness in clustering mixed-level variables.
Findings & value added: Farmers and food producers generally have low adoption rates of advanced digital technologies, preferring common but less advanced tools. This is mainly due to high investment costs, economies of scale, limited experience and expertise, and a lack of willingness to cooperate among farmers. The respondents could be classified into two groups: one group is aware and even understands advanced technology, but rarely uses it. In contrast, the other group is largely unaware of these technologies. The results indicate that a lack of knowledge and expertise can significantly impede the adoption of advanced technologies in agriculture. Policymakers must develop a mix of policies that collectively reduce the economic barriers to technology adoption while engaging stakeholders who may not fully understand the benefits of advanced technologies.
Keywords
digitalization, Hungarian farmers, clustering, precision agriculture
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