Multivariate Total Quality Control pp 221-236 | Cite as
The Non-Symmetrical Analysis of Multiattribute Preference Data
Abstract
Multiattribute preference data refer to judgements collected with respect to a set of stimuli described by relevant attributes. The elements involved in the analysis are a group of judges, a collection of stimuli and a set of attributes characterising the stimuli. In particular, this data structure is used in order to apply the full profile approach to Conjoint Analysis (Green and Rao (1971), Green and Srinivasan (1978), Green and Srinivasan (1978), Green and Srinivasan (1990)). A multidimensional approach to Conjoint Analysis by means of non-symmetrical factorial analysis will be discussed. In this framework, we show how to deal with the complexity of multiattribute data structure. The aim is to characterise, on a two-dimensional subspace, the relationships among the judges, the attribute levels and the stimuli. Each factorial axis is interpreted as a synthesis of the original judgements. For example, the results obtained can be useful in marketing for describing consumer preference towards new product features. A case study showing the results of Conjoint Analysis, carried out both at individual and aggregated level, allows to compare the different approaches.
Key words and phrase
Conjoint analysis design of experiments preference scenario principal component analysis.Preview
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