Digital transition in dairy production:(SSA)

Research Hypothesis Digital technology adoption in SSA dairy systems significantly improves productivity, operational efficiency, and market integration, but adoption barriers (e.g., infrastructure, gender disparities) vary across countries due to contextual factors. Data Collection Methodology Aspect Details Scope 137 dairy farms across Ghana (39), Kenya (41), Nigeria (16), Tanzania (16), Uganda (25) Timing November–December 2023 Tools Closed-ended smartphone questionnaires (translated to local languages) Sampling Hybrid: Random (representativeness) + Purposive (targeting tech-adopting farms) Variables Digital tool usage, barriers (cost/infrastructure), efficiency gains, gender roles, market impacts Ethics University-approved protocols; informed consent obtained Key Findings 1. Efficiency Gains: o Ghana showed highest improvement (mean: 9.38/21 codes) due to mobile/IoT tools. o Nigeria/Uganda lagged (means: 3.75–3.36). 2. Adoption Barriers: o Highest in Nigeria (mean: 20.25/33 codes: cost/infrastructure). o Lowest in Uganda (mean: 5.20). 3. Marketing Impact: o Tanzania/Ghana led in value-chain digitization (e.g., e-commerce platforms). 4. Gender Disparities: o Severe in Ghana (12:1 male-farmer ratio) vs. parity in Kenya/Tanzania. Data Interpretation Dataset How to Interpret Use Cases Q10 (Efficiency) Higher codes = advanced impacts (e.g., Code 15: AI-driven decisions) Prioritize high-impact tools (e.g., IoT over SMS) Q13 (Barriers) Codes 1–10 = structural (cost); 11–20 = technical (skills); 21–33 = social (gender) Target interventions (e.g., Ghana: subsidize costs) LDA Clustering (Fig 1) Uganda/Ghana = distinct clusters → country-specific adoption patterns Customize policies per country Gender Data (Q19) Female participation correlates with tech adoption (r=0.68, p<0.05) Design women-focused digital literacy programs Notable Conclusions • Tailored Solutions Needed: o Ghana: Address cost barriers despite efficiency gains. o Nigeria: Invest in electricity/internet. o Uganda: Scale low-barrier model regionally. • Gender Inclusion: Training + finance access for women farmers boosts adoption. • Stepwise Tech Integration: Start mobile-based (SMS/market apps), then scale to AI/IoT. Data Reusability • Access: Restricted due to confidentiality; contact author (c.vuvor@studenti.uniss.it) for requests. • Supplementary Files: S1 (questionnaires), S2 (qual-quant methodology), S3 (coding schemes) enable methodological replication. • Aggregated Data: Tables 2–4 support cross-country benchmarking (e.g., barrier severity indices). Key Insight: Digital tools can close SSA’s dairy supply-demand gap if deployed contextually—addressing gender, infrastructure, and cost barriers