TOE Drivers and Farm Performance: The Mediating Role of AI Adoption in Omani Hydroponics—An Exploratory Sequential Mixed-Methods Study

Artificial intelligence (AI) provides significant benefits for hydroponic systems by enabling precise nutrient management, efficient water recycling, and predictive decision support. However, adoption of AI in Omani hydroponic operations remains inconsistent, and the mechanisms linking contextual factors to farm-level performance are not well understood. This study investigates how technological, organizational, and environmental conditions relate to AI adoption, the association between adoption and perceived performance, and the mediating role of adoption in this relationship. An exploratory sequential mixed-methods approach, based on the Technology–Organization–Environment (TOE) framework, was employed. Data from nineteen interviews produced 563 coded references, and that material then shaped the item wording of a structured survey we administered to seventy-nine respondents. Reliability analysis using Cronbach’s alpha demonstrated acceptable to excellent internal consistency (α = 0.71–0.92). All three TOE dimensions were significant predictors of AI adoption (β = 0.29–0.33; R2 = 0.58). AI adoption emerged as the sole significant direct predictor of perceived performance (β = 0.70; R2 = 0.67), with none of the TOE dimensions retaining a significant direct association. Bootstrap analysis with five thousand resamples confirmed significant indirect effects for the Technological and Environmental dimensions, while the indirect effect for the Organizational dimension was inconclusive: its confidence interval crossing zero—a pattern we read as jointly reflecting heterogeneous organizational capacity across farms and the limited statistical power of a study this size for smaller effects. This study advances the TOE framework within Gulf-region hydroponic agriculture, identifies AI adoption as a key mediating mechanism, and provides evidence-based recommendations for policymakers, agricultural institutions, and technology providers. Since we define performance here in terms of water recycling, resource use and yield stability, the observed associations speak directly to sustainable production in arid settings.