The increasing complexity of many products makes high demands on methods used for measuring consumer preferences. In such cases, practitioners frequently use Adaptive Conjoint Analysis (ACA). However, compositional approaches also proved to be efficient. Recently, Srinivasan and Netzer (2011) suggested a promising compositional technique called the Adaptive Self-Explicated Approach (ASE), which significantly outperformed ACA regarding its predictive validity. Another advantageous approach, called Pairwise Comparison-based Preference Measurement (PCPM), was introduced by Scholz et al. (2010). This paper contrasts the popular ACA with these two new compositional approaches and discusses the validity results of an empirical study in the leisure industry. For two out of three criteria PCPM partly leads to a significantly higher predictive validity and a halving of the survey time.
Zeitschrift Für Betriebswirtschaft, 2011, Vol 81, Issue 4, p. 423-466