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A COMPARISON OF CONJOINT ANALYSIS AND INTERACTIVE GENETIC ALGORITHMS FOR THE STUDY OF PRODUCT SEMANTICS
Petiot, Jean-François; Francisco, Cervantes Chavez; Ludivine, Boivin
Type:
Year:
2015
Editor:
Christian Weber, Stephan Husung, Gaetano Cascini, Marco Cantamessa, Dorian Marjanovic, Frederico Rotini
Author:
Series:
ICED
Institution:
1: Ecole Centrale de Nantes, France; 2: Technocentre RENAULT, France
Section:
Design Methods and Tools - part 1
Page(s):
011-020
ISBN:
978-1-904670-68-1
ISSN:
2220-4334
Abstract:
An active research field in product design concerns the analysis of end-users evaluations on virtual products, in order to understand the product semantics. This study compares two methods for eliciting user s perceptions of a product: a classical model-based method, based on conjoint analysis, and a more innovative non model-based test, using interactive genetic algorithms. The product proposed to illustrate the study is a digital instrument panel integrated in a car dashboard, and the semantic dimension considered is the sportiness . After the definition of the variables of the instrument panel, the two users assessment tests are conducted with a panel of 30 participants. For both tests, the most influent variables on the sportiness of the instrument panel are selected, and representative designs of the sportiness are defined (the most or the least sporty). A comparison of the results of the tests is proposed, by examining the differences and agreements between them. The results show that the agreement between the two tests is important and that interactive genetic algorithms can be an interesting alternative to classical rating tests to study product semantics.
Keywords:
