The difference between 'less bad' and 'much better'
Conjoint analysis is one of the most important tools in market research, yet it neglects fundamental insights from 'Behavioural Economics' Hence, all conjoint results are subject to two inherent distortions: firstly, linear interpolation fails to depict the typically 'step-like' utility functions of quantitative attributes. Secondly, the effects of differing levels of product involvement are artificially evened out. An 'open source' correction algorithm that efficiently eliminates both problems and bridges the gap between the rationalistic conjoint analysis and the realistic insights from 'Behavioural Economics' has been developed. The algorithm sensitively captures these behavioural effects whilst simultaneously preserving the strengths of conjoint, namely its diverse simulation options.
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