Descriptive analysis of South African livestock Farmers Towards the Adoption of Smart Farming Technologies

Abstract

This study investigates the factors influencing the adoption of smart farming technologies (SFTs) among South African livestock farmers, recognizing that their technology adoption behaviour differs from crop farmers. Using a quantitative descriptive research design, data were collected from 110 livestock farmers through a structured questionnaire. Structural Equation Modelling (SEM) was employed to test hypothesised relationships between technological, behavioural, institutional, and perceptual factors. The results show that Perceived Usefulness and Technical Infrastructure are significant predictors of adoption, while Farmers’ Knowledge and Skills, External Support, and Regulatory Environment have weak or non-significant effects. These findings highlight the critical role of infrastructure and perceived benefits over institutional support in shaping adoption decisions. The study contributes to understanding livestock-specific adoption dynamics in a South African context, where infrastructural challenges and behavioural factors intersect. It recommends prioritizing infrastructure investment, emphasizing practical benefits in training programmes, and exploring context-specific business models for smallholder farmers. This research provides empirical evidence to guide policymakers, technology developers, and extension services in fostering digital transformation in the livestock sector.