Uncovering the Determinants of the Transition to Digital Agriculture: A Survey-Based Tobit Analysis

This study examines the state of digital agriculture in the Republic of Armenia, a sector characterized by small farm sizes, extensive production models, and limited financial capacity. Using a stratified sample of 400 farms, the research assesses the extent of digital technology adoption, key obstacles, and the determinants of digital penetration. Descriptive findings reveal low adoption rates across most digital tools, driven by high costs, limited awareness, insufficient digital literacy, and skepticism toward digital practices. To provide a more rigorous empirical assessment, a Tobit regression model was applied. The results show that all included variables significantly influence digital adoption, with farm size exerting the strongest positive effect, underscoring the importance of economies of scale. Education, income, production orientation, production model, and age also significantly shape adoption likelihood. The combined descriptive and econometric evidence indicates that the discussed digital gap is largely rooted in structural limitations, particularly the prevalence of very small farms. The study concludes by recommending targeted policies (land consolidation, financial assistance, and farmer training) to support a more modern, efficient, and digitally integrated agricultural sector.