Digital agriculture technologies are widely promoted as enablers of climate-resilient and efficient farming, yet empirical assessments of their financial, social, and ecological viability in tropical small and medium-sized enterprises (SMEs) remain limited. This study evaluates the perceived return on investment, cost efficiency, and socio-environmental co-benefits of DATs among 389 agro-SMEs across Costa Rica's seven provinces using a structural equation modelling (SEM) approach. The analysis focuses on three commonly adopted technologies: sensor-based irrigation systems, GPS-enabled machinery, and drone-assisted crop monitoring. The analysis integrates the Technology Acceptance Model, Technology-Organisation-Environment, and classical investment theory to explain adoption behaviour and performance outcomes. Results show a mean return on investment of 34.8% and a median pay-back of 2.4 years, driven primarily by improved input management. Financial access significantly moderates the relationship between technology use and economic returns, with supported adopters achieving higher economic returns. Socio-environmental benefits, such as reduced resource use and improved labour quality, are partially mediated by gains in cost efficiency. Robustness checks confirm that outcomes are consistent across regions, firm sizes, and digital service types. The findings suggest that digital agriculture technologies represent a viable investment even in fragmented, resource-constrained contexts, provided that financial and infrastructural barriers are addressed. Policy recommendations include targeted loan guarantees, rural broadband corridors, inclusive training programmes, and results-based public–private partnerships. The study contributes to the evidence base for scaling digitalisation in tropical agriculture and positions digital technologies as drivers of productivity, inclusivity, and sustainability. Future research should expand longitudinal tracking, explore fintech-enabled models, and quantify environmental co-benefits for climate-finance eligibility.
Okot et al. (Wed,) studied this question.