Alternative methods for combining information about products, consumers and consumers’ acceptance based on path modelling

• The methodology relates consumer characteristics to each other and to the acceptance.
• Path modelling is here used for linking data about consumers, products and acceptance.
• Ways of pre-processing and combining data sets with different dimensions are explained.
• The study can be applied to preference mapping, conjoint analysis and their combination.

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.