One of the design elements in conducting Conjoint analyses is the use of orthogonal experiments to maximize our understandings from the variable parameters. I noticed that the design of the experiments, e.g. how the variable parameters are grouped together per line, looked very similar to the design of experiments done in Industrial Engineering, such as in line manufacturing.
One method of experiment design used in Industrial Engineering is called the Taguchi method. (http://controls.engin.umich.edu/wiki/index.php/Design_of_experiments_via_taguchi_methods:_orthogonal_arrays). In line manufacturing, there could be various inputs, such as temperature, type of chemicals, and processing time. These would be our variables. The possible values would be "hot, cold", "acidic, basic", "5 min, 10 min." Then, using the Taguchi method, one can design a few experiments to see which combination of values optimizes the output.
When we studied Conjoint in class, it seems we used the same method but with an application to marketing.
The link above provides details into how we might design our own (Taguchi) experiments so that we can conduct simple Conjoint analyses.
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Thanks for the link! Indeed, the method for designing the experiment is exactly the same. Conjoint however refers also to the data analysis, which is different than the standard way one would evaluate experiments.
ReplyDeleteExperimental design is also a standard feature in most statistical software packages these days.
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