Increasingly, appliers of conjoint analysis are being faced with the need to reduce data collection demands on respondents while still obtaining enough data to estimate individual utility functions. The authors propose a model that combines the ease of self-explicated utility measurement with the greater generality of decompositional models to develop estimated utility functions that maintain individual differences. The model is applied to a conjoint study involving physicians’ evaluations of a new antibiotic drug. The paper concludes with suggestions for possible extensions of the approach.
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