Hybrid Approach to Choice-Based Conjoint Analysis

Adaptive Choice-Based Conjoint Analysis

Conjoint analysis (CA) has emerged as an important approach to the assessment of health service preferences. This article examines Adaptive Choice-Based Conjoint Analysis (ACBC) and reviews available evidence comparing ACBC with conventional approaches to CA. ACBC surveys more closely approximate the decision-making processes that influence real-world choices. Informants begin ACBC surveys by c...

Choice Based Conjoint Analysis: Discrete Choice Models vs. Direct Regression

Conjoint analysis is family of techniques that originated in psychology and later became popular in market research. The main objective of conjoint analysis is to measure an individual’s or a population’s preferences on a class options that can be described by parameters and their levels. We consider preference data obtained in choice based conjoint analysis studies, where one observes test per...

Adaptive Hybrid Methods for Choice-Based Conjoint Analysis: A Comparative Study

Adaptive choice-based conjoint analysis (ACBC) and hybrid individualized two-level choice-based conjoint analysis (HIT-CBC) were developed to improve standard choice-based conjoint analysis through additional interviewing techniques. Both methods have demonstrated their applicability in comparison to standard choice-based conjoint methods. The objective of our study was a direct comparison of t...

The CBC System for Choice-Based Conjoint Analysis

Ellipsoidal Methods for Adaptive Choice-Based Conjoint Analysis

Questionnaires for adaptive choice-based conjoint analysis aim at minimizing some measure of the uncertainty associated with preference parameters (e.g. partworths). Bayesian approaches to conjoint analysis quantify this uncertainty with a multivariate distribution that is updated after the respondent answers. Unfortunately, this update requires multidimensional integration, which effectively r...