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Principles of forecasting Featured

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Conjoint analysis can be used to understand how consumers develop preferences for product using a combination of different attributes.  Conjoint analysis is a multivariate method developed particularly to understand how consumers develop preferences for various products or services. The technique is widely used in marketing research because it allow researchers to estimate consumer’s preference of a product by combining part worth utilities for each attribute.

It is a decomposition approach for the measurement of preferences. Whereas incompositional preference measurement parameters are elicited directly from the decision make, in  decompositional method those parameters are derived from the decision makers’ holistic evaluative responses (in terms of liking, preferences, likelihood of purchasing, stated choices, etc) to profile descriptions designed by the researcher.  The researcher asks members of a target market to indicate their preferences or choices for objects under a range of hypothetical situations described in terms of product or services features, including features not available in existing products or services. The researcher uses these judgments to estimate preference functions, often a unique one for each respondent participating in a conjoint study. Steps involved in conjoint analysis include the selection of attributes and levels, the stimulus set and stimulus presentation method, collection of data and the measurement scale, the preference mode and the choice of simulator.


Armostrong J.S (2010). Principles of forecasting: Handbook of researchers and practitioners. Springer publishers, USA.

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