Evaluating Regional Monitoring Network Adoption: A Randomised Field Trial in South African Agriculture

{ "background": "Regional monitoring networks (RMNs) are promoted as tools for enhancing agricultural productivity and sustainability through shared data on soil, water, and pests. However, evidence on their adoption by farmers, particularly in sub-Saharan contexts, remains sparse and anecdotal.", "purpose and objectives": "This study aimed to provide a rigorous methodological evaluation of RMN adoption rates using a randomised field trial design. The primary objective was to estimate the causal effect of a structured intervention on farmer enrolment and sustained use.", "methodology": "We conducted a randomised controlled trial with 120 small to medium-scale commercial farms. Participants were randomly assigned to a treatment group receiving a facilitated demonstration and access protocol, or a control group receiving basic information. Adoption was measured as enrolment and data submission over a defined period. The analysis employed a probit model: Pr(Adopti = 1) = \Φ(\β0 + \β1 Treatmenti + ᵢ'\γ), where is a vector of farm-level controls. Robust standard errors were used for inference.", "findings": "The intervention significantly increased enrolment. The treatment group's adoption rate was 47% (95% CI: 38.1, 55.9), compared to 18% in the control group. The adjusted average treatment effect was 28 percentage points (p < 0.01). A key thematic finding was that perceived immediate agronomic utility, rather than long-term sustainability benefits, was the dominant driver of sustained use.", "conclusion": "The facilitated intervention substantially increased RMN adoption, demonstrating that targeted support can overcome initial barriers. However, sustained engagement requires the network to deliver clear, short-term agronomic value to participants.", "recommendations": "Policymakers and network designers should integrate structured onboarding support within rollout programmes. RMN platforms must prioritise features that provide rapid, actionable insights to farmers to ensure long-term viability.", "key words": "agricultural technology,