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An Optimization framework for adaptive questionnaire design

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The authors propose a general approach for adaptively designing questionnaires for conjoint analysis customized at the individual level. At each step, the next question presented to an individual is designed on the fly and computationally fast based on the responses the individual has given to all previous choice questions. Their framework also encompasses recent polyhedral adaptive conjoint methods as a special case. Within their framework, they develop a novel conjoint analysis method that is in the spirit of recently proposed conjoint estimation methods. They test the proposed method on widely used simulation data and compare the effectiveness of the designed questionnaires with a standard orthogonal design, a random design, and a polyhedral adaptive conjoint questionnaire under varying conditions. The results show that the proposed method leads to individual-specific questionnaires and estimations of individual utilities that are significantly more accurate than what is estimated with the other methods and questionnaires when there is high response error. They finally show that further significant improvements are achieved when they use a hybrid individual-specific and aggregate customization method that they also develop within their general framework for conjoint analysis.

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