The Influence of Agricultural Technology Adoption on Coffee Productivity: Case of Smallholder Farmers in Mouamenam, Littoral Region of Cameroon

Njoume Ngolle Verdi^1, and Fomena Neuchy Larissa²

¹Independent Researcher, Bamenda, North West Region, Cameroon

²Independent Researcher, Quebec, Canada

Cite this paper:
Njoume Ngolle Verdi and Fomena Neuchy Larissa. The Influence of Agricultural Technology Adoption on Coffee Productivity: Case of Smallholder Farmers in Mouamenam, Littoral Region of Cameroon. Journal of Applied Agricultural Economics and Policy Analysis. 2026; 7(1):13-24. doi: 10.12691/jaaepa-7-1-1

Abstract

: This study examines the influence of agricultural technology adoption on coffee productivity among smallholder farmers in Mouamenam. Using a quantitative cross-sectional design, data were collected from 358 farmers via structured questionnaires. The study focuses on key agricultural technologies including improved coffee seedlings, fertilizer and pesticide use, mechanized tools, and access to extension services. Coffee productivity was measured in kilograms per hectare. Empirical analysis employed Ordinary Least Squares (OLS), log-linear models, Propensity Score Matching (PSM), and Instrumental Variables (IV)/Two-Stage Least Squares (2SLS) to account for potential endogeneity. OLS results indicate that improved seedling adoption (IS) increases productivity by 48.5% (β = 0.485, p < 0.01), mechanized tools (MT) by 32.3% (β = 0.323, p < 0.01), fertilizer and pesticide use (ln_FPU) by 9.2% (β = 0.092, p < 0.01), and extension contacts (ESC) by 12.4% per visit (β = 0.124, p < 0.01). Access to credit (AC) and cooperative membership (Coop) also positively affect productivity (β = 0.211 and β = 0.131, p < 0.01). IV/2SLS results confirm the causal impact of improved seedling adoption (β = 4.286, p = 0.020) and mechanization (β = 0.809, p < 0.01), while fertilizer and pesticide use shows a weak negative effect (β = -1.219, p < 0.10). PSM results further reveal that experience (β = 0.052, p < 0.05) and fertilizer use (β = 8.568, p < 0.01) significantly increase adoption likelihood. Findings underscore that technology adoption, mechanization, and institutional support are key drivers of coffee productivity, while structural constraints and inefficient input use continue to limit potential gains. The study recommends large-scale distribution of improved coffee seedlings, strengthened extension services, expanded credit access, and revitalization of farmer cooperatives to enhance adoption and sustainably increase coffee productivity in Mouamenam.

Keywords:
Agricultural technology adoption Coffee productivity Smallholder farmers Propensity score matching Instrumental variables Extension services Cameroon

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