Combining extrinsic and intrinsic information in consumer acceptance studies

This paper proposes a methodology for combining extrinsic and intrinsic attributes in consumer testing of food products. The paper attempts to focalize on the main sensory drivers of liking or choice probability and their interaction with additional information, and to investigate effects related to the population as well as how consumers differ in their assessments. Two different data analysis approaches are considered and compared on choice probability data from a consumer study of orange juice. One of the methods is based on mixed model ANOVA of individual differences, the other approach is based on fuzzy clustering related to regression residuals. The main results show that extrinsic consumer attributes are easily and efficiently related to the sensory properties of products, allowing for interactions. The methodology estimates population or segment means and gives an overview of individual differences in choice intent or liking.

► Methodology for joint studies of intrinsic and extrinsic attributes, in order to discover interactions between the two types of information.
► Emphasis not only on the differences among products, but also on the whole sensory profile and the main drivers of liking or choice probability.
► Methodology best suited for estimating population or segment means, but also for an indication of individual differences in choice intent or liking.
► Important for understanding human perception and liking, but also for product development in industry.
► Combinations of established methods, available in standard software packages.