Abstract
In abstract terms conjoint analysis can be seen as fitting a model to preference information elicited from a group of respondents. That is, conjoint analysis comprises two tasks,
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(1)
preference data elicitation, and
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(2)
model fitting to the elicited data.
The model fitting phase is necessary since in general the elicited data tends to be very sparse and can be interpreted meaningfully only in the context of some model, which already encodes general assumptions on the structure of the preferences.
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References
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Giesen, J., Schuberth, E. (2007). The Combinatorial Structure of Polyhedral Choice Based Conjoint Analysis. In: Gustafsson, A., Herrmann, A., Huber, F. (eds) Conjoint Measurement. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-71404-0_13
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DOI: https://doi.org/10.1007/978-3-540-71404-0_13
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