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2016

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Please use this identifier to cite or link to this item: https://hdl.handle.net/2445/103305

A design strategy for improving adaptive conjoint analysis

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Abstract

Adaptive conjoint analysis (ACA) is a market research methodology for measuring utility in business-to-business and customer studies. Based on partial profiles, ACA tailors an experiment's design to each respondent depending on their previously stated preferences, ordered in a self-assessment questionnaire. The purpose of this paper is to describe advantages and disadvantages of using a partial-profile randomised experiment, the usual system, and to propose a new design strategy for arranging profiles in blocks that improve its performance.

Related resource

https://doi.org/10.1108/JBIM-02-2013-0043

Subject

Disseny d'experiments, Anàlisi conjunt (Màrqueting), Anàlisi factorial

Subject (English)

Experimental design, Conjoint analysis (Marketing), Factor analysis

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HUERTAS GARCÍA, Rubén, GÁZQUEZ-ABAD, Juan Carlos and FORGAS COLL, Santiago. A design strategy for improving adaptive conjoint analysis. Journal of Business & Industrial Marketing. 2016. Vol. 31, num. 3, pags. 328-338. ISSN 0885-8624. [consulted: 16 of October of 2026]. Available at: https://hdl.handle.net/2445/103305

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