Publications

Motivational factors influencing farming practices in northern Ghana

Mellon-Bedi, S.; Descheemaeker, K.; Hundie-Kotu, B.; Frimpong, S.; Groot, J.C.J.

Summary

Socio-economic factors that influence the adoption of management practices and technologies by farmers have received wide attention in the adoption literature, but the effects of socio-psychological farmer features such as perceptions and motivations have been analysed to a lesser extent. Using farm household survey data from three regions in northern Ghana, this study explores farmers’ motivations and perceived adoption impediments for three sustainable intensification practices (SIPs): improved maize varieties, cropping system strategies, and combined SIPs (i.e. improved maize and cropping system strategies), and the effect of motivational factors on decisions to adopt SIPs. First, explorative factor analysis (EFA) was used in identifying factors of motivations and impediments for adoption of SIPs. Then, a multinomial logit model was used to analyze the effect of socio-economic farm characteristics and motivational factors on farmers’ decisions to adopt SIPs. EFA identified three motivational factors: personal satisfaction, eco-diversity and eco-efficiency, which differed in importance between the three regions. Across these regions, higher scores for aspects of personal satisfaction were associated with lower interest in improved maize varieties compared to cropping system strategies, while the opposite was true for eco-efficiency which was related to a stronger preference for improved maize varieties. Uncertainty, absence of social support, and resource constraints were identified as impediment factors. The logit model demonstrated that extension services seemed to support the use of improved maize varieties more than the implementation of cropping system strategies. We conclude that motivational factors significantly influence farmer adoption decisions regarding sustainable intensification practices and should be considered systematically in combination with socio-economic farm features and external drivers to inform on-farm innovation processes and supporting policies.