We investigated how multivariate statistics can be used to determine the different patterns of preferences that may exist within a farmer population. As a case study, we used adaptive conjoint analysis to analyse farmers’ preferences for nine farm performance characteristics that may be related to tail docking practice decisions. As expected, at the whole population level, farmers’ preferences for these traits were found to be highly heterogeneous, with only the most important issues and least important issues being able to be statistically differentiated. Using Cluster Analysis and Principal Components Analysis we found some hidden relationships and identified the existence of four groups of farmers that had greater preferences for different characteristics; group one preferred having less dags and less costs associated with dagging and crutching, group two preferred to reduce euthanasia from uterine prolapse and rectal prolapse, group three preferred to avoid stressing lambs at the time of docking and group four preferred to have less fly-strike and greater weaning weights. We discuss how the use of multivariate statistics allowed a deeper interpretation of preference studies in a context of importance to NZ farmers.
Proceedings of the New Zealand Society of Animal Production, Volume 75, Dunedin, 205-209, 2015
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