Classification of Farming Enterprises of Land Reform Beneficiaries in KwaZulu-Natal

Résumé

The establishment of farmer typologies in agriculture has gained popularity in recent years and is key to guiding planning, execution, and monitoring of intervention strategies and programmes that improve productivity. Using Principal Components Analysis, Hierarchical Clustering, and K-Means Clustering, this study sought to develop farmer typologies and characterise them among land reform farming enterprises. The data was collected from 262 land reform farmers in KwaZulu-Natal using a structured questionnaire. The data set was tested for reliability using the Kaiser-Meyer-Olkin Measure of Sampling Adequacy and Bartlett’s Test of Sphericity. The study found that land reform enterprises in KwaZulu-Natal can be classified into six clusters. The six farmer typologies are summarised as High value farms — driven by farm size, marketing costs and total asset value; Highly capitalised farms — driven by high income, high production costs and high labour costs; Family labour farms — driven by high number of family members and entity directors’ dependent on farm income; Resource-constrained farms — determined by high lease rental amount and reduced access to credit; Retention farms — driven by aging farmers with vast experience; and Non-farm based income farms — driven by high dependence on non-farm income, gender and farmer’s level education. The Principal Components Analysis explained 63,94% of the total variation in the sample. The remaining 36,06% can be explained by other methods not captured by the PCA model. The established clusters enabled the resolution of the main aim of this study, as the established typologies will be key to the planning and implementation of intervention programmes that increase profitability in land reform. Future policies assisting small-scale and land reform farmers should design support packages targeting the homogenous groups of farmers with similar characteristics for maximum impact.

Citer ce document

Accès au document

Texte intégral en lecture en ligne, réservé aux abonnés SPHAERO et aux membres de l'institution. Se connecter

Auteur(s)

Statistiques

Consultations : 1

Téléchargements : 0