Cluster Analysis for classification of farm households based on socio-economic characteristics for technology adoption in agriculture: A case study of West Java Province, Indonesia

Abstract

Blind drive of intensifying vegetable production to combat issues of low productivity, low quality of product and ensuring off season availability of vegetables, pose serious challenges for smallholder farmers to adopt efficient and appropriate technologies. Technology adoption is a complex process depending on several factors mainly including the socio-economic status of individual farmers. The differentiation on adopting technology could be explained by farm typology. The aim of this research is to classify groups of farm households in the West Java Province of Indonesia based on identification of factors influencing new technology adoption. A survey of farmers was carried out during January-December 2010 in Sukabumi (medium and highland) and West Bandung regency (highland). The information obtained through the survey was analysed using multivariate analysis, which was carried out through Principle Component Analysis (PCA) and Cluster Analysis (CA) to classify the farm households based on socio-economic characteristics. Selected variables derived from questionnaires were used to describe the components that influence the adoption of agricultural technology and to identify the group of potential farmers. The results indicate that the farmers could be classified into three, four, and two groups of typical farm households in medium land Sukabumi Regency, highland Sukabumi Regency and West Bandung Regency of West Java Province, respectively.