Abstract
In consumer studies the collected consumer data are often of different nature (demographic variables, attitudes and habits). Usually these data are considered all together when modelling consumer acceptance patterns, even though there may exist interesting relations between groups of consumer characteristics. The objective of this paper is thus to propose methodology for relating the different types of consumer characteristics data to each other and to the consumers' acceptance, when also product information is available. Focus is given to the possible approaches for pre-processing and combining data sets with different dimensions in a path modelling context. Considerations about advantages and limitations are given. The study is general in nature and can be applied to preference mapping, conjoint analysis and their combination. The different approaches are illustrated by data from a consumer test on chocolate, comprising several types of information about consumers.
Original language | English |
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Journal | Food Quality and Preference |
Volume | 31 |
Pages (from-to) | 142–155 |
Number of pages | 14 |
ISSN | 0950-3293 |
DOIs | |
Publication status | Published - Jan 2014 |