Emergent scenarios, synergies and suppressions uncovered within conjoint analysis

Abstract

The article introduces two approaches to identify the direction and magnitude of interaction between concept elements in a conjoint analysis task. Both approaches use main effects experimental designs, permuted to create hundreds of new designs isomorphic to the original design structure. In the first approach, the scenario analysis creates a distinct mutually exclusive and exhaustive set of subgroups from concepts with specific elements, runs a dummy variable regression within each subgroup and identifies the effect of one element on the utilities of the others. In the second approach, the interaction analysis of complete set of raw data forces in the linear terms for the single elements, and then allows significant pair-wise combinations to enter if they contribute significant additional predictability to the model. The two approaches identify the existence of and then measure the impact of one element on the performance of others (scenario), and the unexpected effect of mixing two concept elements (interaction analysis). The approach is illustrated by two case histories: communicating the sensory and refreshment benefits of an orange beverage, and identifying the features of a cookie. © 2006, Blackwell Publishing.