Dimension reduction approaches to modelling many attribute choice

I have previously applied evidence accumulation models to discriminate between which decision strategies are used by participants making multi-attribute choices about products. One limitation of this work is that it has currently been applied only to choices with 2 attributes. A natural extension of this work is to move towards a higher number of attributes or options, however model complexity increases exponentially with attributes x options when assessing strategies. I will present an approach currently being undertaken that asks participants to assess pairs of options (phones) differing across 5 attributes. The participants are asked to make two different judgements of each pair of phones, a preference judgement and a similarity judgement. The preference component of the experiment simply asks participants which phone of each pair they would choose. The similarity judgements are over the same set of phone pairs and participants rate each pair on a 7 point scale from low to high similarity. An initial analysis using multi-dimensional scaling on the similarity data (both average similarity and individual ratings) shows the phones are well represented by two dimensions. The plan will be to take each individuals multi-dimensional scaling solution and use that as input to a cognitive model of the preferences. This model will be contrasted to approaches where option utilities are derived from multi-attribute utility theory to see which better explains preferences.