Analyzing the Socio-Economic and Institutional Determinants of Climate-Smart Agricultural Practices Adoption among Smallholder Green Gram Farmers in Masinga Sub-County, Kenya

Abstract

Climate-smart agriculture (CSA) holds significant potential for enhancing productivity and climate resilience among smallholder farmers. In Masinga Sub-County, approximately 9,900 green gram farmers face erratic rainfall, droughts, and soil degradation, resulting in mean yields of only 460 kg/ha against a potential of 1.5 tons/ha. This study examined the socio-economic and institutional determinants, incentives, and constraints influencing CSA adoption. Anchored in the Theory of Planned Behavior and the Technology Acceptance Model, the study employed a descriptive cross-sectional design. Data were collected using semi-structured questionnaires administered to 390 green gram farmers selected through stratified random sampling across the five wards of Masinga Sub-County. Data were analysed using descriptive statistics in SPSS Version 29. Results showed that 54.0% of respondents had adopted at least two CSA practices, with drought-resistant seed varieties (43.2%) and minimum tillage (42.4%) being the most common. The binary logistic regression model demonstrated a good fit (McFadden Pseudo R² = 0.395; overall classification accuracy = 80.4%) and identified significant positive predictors: access to input subsidies (OR = 2.33, p < 0.001), perceived government policy support (OR = 2.37, p = 0.002), annual household income (OR = 2.09, p = 0.006), and market linkages (OR = 1.74, p = 0.049). High input costs were the main significant barrier (OR = 0.42, p = 0.002). Thematic analysis confirmed infrastructure deficits, financial barriers, and awareness gaps as interconnected obstacles. The study findings provided valuable insights for the academic literature by addressing gaps in research on CSA adoption in semi-arid regions, particularly for drought-prone crops like green gram. Additionally, the study findings benefit policymakers by offering data-driven recommendations for designing and developing policies that enhance CSA adoption and sustainability in smallholder farming. Agricultural extension services and development organisations may use these findings to design targeted programmes that address key incentives and constraints. The study concluded that income level and access to input subsidies were the primary drivers of CSA adoption, while high input costs constituted the foremost structural barrier, with incentives and constraints each operating as integrated, mutually reinforcing systems rather than isolated factors.