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<p>Determining consumer preferences is still one of the most important topics in marketing research. Not surprisingly, numerous approaches have been developed for this task. Conjoint measurement techniques are among the most prominent and different forms have emerged over the years. Depending on the specific research setting, all of them have their advantages and drawbacks. The authors discuss the nature and applicability of recent conjoint approaches and provide examples. Guidelines for selecting the optimal technique help to identify which approach works best in a given situation. </p>
</abstract>

Determining consumer preferences is still one of the most important topics in marketing research. Not surprisingly, numerous approaches have been developed for this task. Conjoint measurement techniques are among the most prominent and different forms have emerged over the years. Depending on the specific research setting, all of them have their advantages and drawbacks. The authors discuss the nature and applicability of recent conjoint approaches and provide examples. Guidelines for selecting the optimal technique help to identify which approach works best in a given situation.

Preference Measurement with Conjoint Analysis. Overview of State-of-the-Art Approaches and Recent Developments

Postdoctoral Research Associate, Institute of Marketing & Media, University of Hamburg, Germany

Professor of Marketing and Branding, Head of the Institute of Marketing & Media, University of Hamburg, Germany

NIM Marketing Intelligence Review

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Determining consumer preferences is still one of the most important topics in marketing research. Not surprisingly, numerous approaches have been developed for...

Preference Measurement with Conjoint Analysis. Overview of State-of-the-Art Approaches and Recent Developments

Published Online: Jul 19, 2014

Page range: 36 - 47

DOI: https://doi.org/10.2478/gfkmir-2014-0054

© 2014

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.