Sustainable Green (SG) technologies are increasingly promoted as pathways for improving soil health, farm productivity, and resilience among smallholder farmers in sub-Saharan Africa. This study examines the determinants of adoption, use intensity, and disadoption of SG Packs among rural households in Northern Nigeria. Primary data were collected from smallholder farmers across five states using multistage sampling. The data were analyzed using a Triple-Hurdle Model to capture the sequential decision processes of adoption, intensity, and dis-adoption. The correlation parameters across the three stages are significant, confirming the presence of unobserved heterogeneity and supporting the use of the Triple-Hurdle framework. The results show that education, farm size, access to credit, hired labour, productive and non-productive assets, and membership in farmer associations significantly increase the likelihood of adoption, while household dependency burden reduces it. The intensity of use is positively influenced by farm size, productive assets, and hired labour, suggesting that better-resourced farmers are more able to expand the use of SG practices. The dis-adoption results indicate that gender, household size, number of dependents, and non-productive assets increase the likelihood of discontinuing SG technologies, whereas education, larger farm sizes, hired labour, and productive assets reduce the probability of dis-adoption. The findings suggest that while farmers adopt SG technologies, sustained use depends largely on economic capacity, labour availability, and institutional support. Strengthening access to credit, extension services, and asset accumulation could therefore improve sustained adoption of SG technologies. • SG Packs integrate soil fertility management, drought-tolerant seeds, and conservation agriculture to boost resilience in Northern Nigeria. • A Triple-Hurdle Model captures the stages of adoption, intensity of use, and dis-adoption among 800 smallholder households. • Education, credit access, hired labor, and productive assets enhance both adoption and usage intensity. • Male gender, large household size, and non-productive assets significantly increase dis-adoption likelihood. • Dis-adoption reflects rational coping with labor and cost constraints, underscoring the need for adaptive, farmer-centered innovation strategies.
Kehinde et al. (2026) studied this question.