Discrete choice experiments are an increasingly popular form of marketing research due to the accessibility of on-line respondents. While statistically optimal experimental designs have been developed for use in discrete choice experiments, recent research has suggested that efficient designs often fatigue or burden the respondent to the point that decreased response rates and/or decreased response precision are observed. Our study was motivated by high early-termination rates for one such optimally-designed study.
In this talk, we examine the design of discrete choice experiments in the presence of respondent fatigue and/or burden. To do so, we propose a model that links the respondent's utility error variance to a function that accommodates respondent fatigue and burden. Based on estimates of fatigue and burden effects from our own work and published studies, we study the impact of these factors on the realized efficiencies of commonly-used D-optimal choice designs. The trade-offs between the number of surveys, the number of choice sets per survey, and the number of profiles per choice set are delineated.
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