The Difficulties in Measuring Individual Utilities of Product Attributes: A Choice Based Experiment
Abstract
The study combines different theoretical approaches in the field of conjoint analysis to estimate the im-portance of product related attributes. This is of major importance in food marketing, where we still try to find a valid answer, in particular, how to measure the real willingness to pay (WTP) for specific product specifica-tions. Based on a comprehensive literature analysis, a common method was used to approximate the im-portance of several product attributes. As usually suggested in literature, we used discrete choice modeling and developed a choice based experimental design considering selected product attributes. The study object was frozen pizza, a convenience good frequently bought by most households.
Up to this point, there is nothing special about the choice based experiment in comparison to direct measure-ment of the importance of product attributes. However, one of the core problems of discrete choice modeling – the approximation of individual utility functions – was then addressed by transforming the choices of con-sumers into scores. With these scores traditional conjoint measurement can be used to approximate individual utilities even in choice based experiments. The individual part-worth utilities will be compared with a usual but very complex approach to approximate individual part-worth utilities, the hierarchical Bayes method. Our ap-proach addresses methodological considerations concerning the restrictions of discrete choice modeling, namely the complexity of approximating individual utilities which is of huge importance in particular for market segmentation.
Up to this point, there is nothing special about the choice based experiment in comparison to direct measure-ment of the importance of product attributes. However, one of the core problems of discrete choice modeling – the approximation of individual utility functions – was then addressed by transforming the choices of con-sumers into scores. With these scores traditional conjoint measurement can be used to approximate individual utilities even in choice based experiments. The individual part-worth utilities will be compared with a usual but very complex approach to approximate individual part-worth utilities, the hierarchical Bayes method. Our ap-proach addresses methodological considerations concerning the restrictions of discrete choice modeling, namely the complexity of approximating individual utilities which is of huge importance in particular for market segmentation.
Full Text:
PDFDOI: https://doi.org/10.18461/pfsd.2017.1703
ISSN 2194-511X
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