Conjoint analysis is used to measure the importance of attribute-level trade-offs. A methodological anomaly is the number-of-levels effect; that is, as the number of intervening attribute levels increases, the derived importance weight of an attribute increases. The authors use three studies to show that attentional processes contribute to the number-of-levels effect. When there is an inequalit…
An enduring issue in the development and use of conjoint analysis is consumer response to missing attributes in partial profiles. Academic research has failed to produce a consistent answer to this issue, and practitioners are more likely to view it as a nuisance factor. Bradlow, Hu, and Ho (2004) argue that inference making is common, follows a specified process, and when properly incorporated…