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. (C) 2011 Elsevier Ltd. All rights reserved.