Designing Conjoint Choice Experiment Using Partially Confounded Factorial Design

摘要

Conjoint choice experiments help researchers understand how people make complex judgments such as purchase decisions and product valuation by posing a series of choices, about products or services. A respondent is asked to evaluate a series of choice sets, where the task is to choose the most preferred alternative from a series of choice sets. Conjoint choice designs are frequently based on single fractions of full factorial designs that generally do not allow estimation of interaction effects, have complex aliasing and produce biased estimates of main effects when interactions are not negligible. As an alternative to fractional factorials, we developed partially confounded factorial designs for conjoint choice experiments with the purpose of estimating main effects and first order interactions.