Hybrid Models for Conjoint Analysis: An Expository Review

TLDR

Hybrid conjoint models have emerged to reduce data collection effort and time by blending self‑explicated utility measurement with traditional conjoint analysis, yet their untested assumptions warrant further theoretical and empirical scrutiny. The paper recommends future research to rigorously test the assumptions and performance of hybrid conjoint models before their practical role can be fully assessed. The authors classify hybrid models and evaluate their comparative performance using cross‑validation tests.

Abstract

Over the past few years hybrid models for conjoint analysis have been developed to reduce data collection effort and time. Hybrid models combine features of self-explicated utility measurement with more traditional conjoint analysis. A classification of hybrid models is presented, followed by a review of their comparative performance in cross-validation tests. Though hybrid models represent an attempt to cope with an important practical problem in industry applications of conjoint techniques, these models entail a number of untested assumptions requiring further theoretical analysis and empirical research. Suggestions are offered on future studies that are essential before the role of hybrid models in conjoint methods can be evaluated properly.