Cost‑Benefit Analysis of Precision Agriculture Adoption in Developing Countries

Abstract

Despite the significant potential of precision agriculture technologies to boost resource use efficiency and crop productivity, the adoption of these technologies in small and medium scale farms is low in developing areas, which is attributed to financial, infrastructure and socio-technical constraints. The study used a mixed methods sequential explanatory design, combining cost-benefit, logistic regression modeling, sensitivity analysis and thematic analysis of qualitative interviews to analyze the economic feasibility and factors influencing the adoption of precision agriculture technologies in 240 farms across three agricultural regions. This shows a clear farm size threshold with farms smaller than two hectares having negative NPVs for all crops while farms larger than five hectares provide strong positive returns up to 1678.92 USD per hectare. The logistic regression showed that reliable internet connection was the most significant predictor of adoption with a higher increase of adoption by 6.51 times for every additional USD per hectare in capital cost, the odds of adoption decreased by about one percent per increase in capital cost. Crop sale price was the most sensitive parameter, with a value of 2.24, which shows high vulnerability of the market fluctuation. There were considerable improvements in environmental outcomes, including a 30.01 percent decrease in water use and a 36.62 percent decrease in pesticide application. The results of the qualitative study were largely corroborative, with high capital costs (reported by 88.3 per cent of farmers) and poor internet connection (81.7 per cent) being identified as the main constraints. Multi-criteria ranking of intervention resulted the most effective interventions as capital subsidies with a composite index score of 87.6, and digital literacy training with a composite index score of 86.5. The study concludes that precision agriculture adoption can't be necessarily recommended to all the different sizes of farms across the developing regions and the policies aimed at precision agriculture should be context-specific, be mindful of equity and should involve the implementation of shared equipment models, investments in rural internet infrastructure, and the implementation of targeted training programs to enable sustainable and inclusive adoption.