Utilizing conjoint analysis to design modern crop varieties: Empirical example for groundnut in Niger

Preferences for monetary and non-monetary plant traits influence modern crop variety adoption decisions of farmers. To enhance adoption probability of modern crop varieties, it is necessary to identify and focus research on traits that significantly contribute to utility while de-emphasizing insignificant plant attributes. This paper illustrates the potential for applying conjoint analysis to aid the design and targeting of client-responsive modern crop varieties. Farmers ranked eight orthogonally-derived plant trait combinations used in an illustrative example. Utilities were estimated using the choice-probability-based method of ordered probit. Results showed that conjoint analysis can differentiate significant and non-significant traits of modern crop varieties. The usefulness of applying conjoint analysis over identifiable disaggregated groups of a sample was also evident. Future application of conjoint analysis to the design and targeting of modern crop varieties should carefully consider sample composition and size to permit the estimation of relevant sub-models for desired farmer segment

A variable-selection heuristic for K-means clustering

cluster analysis, K-means partitioning, variable selection, heuristics,