Economic analysis of agricultural information systems (AIS) adoption in Jordan: determinants, productivity effects, and farm-level evidence

This study examines the economic dimensions of using Agricultural Information Systems (AIS) in the Jordanian agricultural sector. Using a mixed-methods approach, this study analyzes the determinants and productivity effects of adoption based on farm-level survey data from 842 agricultural holdings in 12 governorates, supplemented by retrospective data covering 2015–2024. Uses binary logistic regression with governorate fixed effects and heteroscedasticity-robust standard errors to account for the small number of clusters (12 governorates). The results show that digital infrastructure (β = 0.156, p < 0.001), farm income (β = 0.847, p < 0.001), and operator education (β = 0.423, p < 0.001) significantly increase the likelihood of adoption with Nagelkerke R² = 0.412. Distance from urban centers reduces the probability of adoption (β = −0.089, p = 0.001). Productivity associations are estimated using OLS regression. AIS-enabled farms exhibited 104.2% yield improvement and 51.5% higher water use efficiency compared to non-adopters. Production costs decreased by 28.5%, with an average payback period of 1.8–2.7 years. The model explains 81.4% of the variance (adjusted R² = 0.814) with AIS investment intensity and implementation quality as primary drivers. The study identify significant regional differences, with adoption rates ranging from 36.5% (Ma’an) to 58.6% (Amman). Financial barriers (72.8%), limited digital skills (67.4%) and lack of infrastructure (64.7%) are the biggest obstacles to adoption. The findings confirm that AIS adoption acts as a productivity-enhancing investment in water-scarce agricultural economies, although self-selection biases suggest that the observed associations may exaggerate causal effects. Policy implications emphasize targeted infrastructure investment and human capital development in peripheral areas to bridge the digital divide.