Farm household typology and adoption of climate-smart agriculture practices in smallholder farming systems of southern Africa

Abstract

Enhancing adoption rates of climate-smart agriculture practices and their impact on livelihoods requires promotional persistence, complemented by a thorough socioeconomic analysis that recognizes the heterogeneity of smallholder farmers. Farm typologies are a useful tool to assist in understanding and unpacking the wide diversity amongst smallholder farmers to improve both up- and out-scaling of climate-smart agriculture practices. Our study typifies farm households in southern Africa based on socioeconomic factors prompting adoption of climate-smart agriculture practices. We use a combination of principal component analysis for necessary data reduction and cluster analysis to identify typical farm households and their socioeconomic characteristics. It is evident from our results that various socioeconomic factors define clusters and can be associated with adoption and use of climate-smart agriculture practices in smallholder farming. We conclude that farm typology identification is an important step towards the promotion of climate-smart agriculture practices in smallholder agriculture. These typologies provide essential ammunition to support efforts and policies aimed at improving adoption by recognizing heterogeneities in the targeted populations. In addition, we conclude that the multivariate analysis provides useful tools suitable for identifying the important socioeconomic characteristics of households influential in determining adoption of climate-smart agriculture practices.

Keywords:

• climate-smart agriculture
• farm household typology
• multivariate analysis
• adoption
• southern Africa

Acknowledgements

The authors would like to acknowledge the financial assistance received from the Dryland Systems Consultative Research Programme (CRP1.1), International Fund for Agricultural Development and International Centre for Tropical Agriculture (CIAT) that was used in carrying out these studies. We thank all the enumerators for good work in data collection and most importantly the farmers who patiently gave us their time and responded to our questions.

Disclosure statement

No potential conflict of interest was reported by the authors.

ORCID

Clifton Makate http://orcid.org/0000-0002-6061-6638

Marshall Makate http://orcid.org/0000-0002-2005-2970

Nelson Mango http://orcid.org/0000-0003-4436-0449