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CONSUMER PREFERENCES FOR VISUALLY PRESENTED MEALS
Author(s) -
REISFELT HANS HENRIK,
GABRIELSEN GORM,
AASLYNG MARGIT DALL,
BJERRE MARIA SCHMIDT,
MØLLER PER
Publication year - 2009
Publication title -
journal of sensory studies
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.61
H-Index - 53
eISSN - 1745-459X
pISSN - 0887-8250
DOI - 10.1111/j.1745-459x.2008.00202.x
Subject(s) - meal , product (mathematics) , portion size , computer science , selection (genetic algorithm) , similarity (geometry) , marketing , information retrieval , psychology , mathematics , food science , artificial intelligence , business , image (mathematics) , chemistry , geometry
The aim of the study was to investigate consumers' preferences for variations of a visually presented meal. The study was conducted in three middle‐sized Danish towns, including 768 respondents who were presented with a computerized questionnaire that initially displayed four consecutive series of photos. The series each consisted of eight unique photos of randomized food dishes arranged around the center square in a 3 × 3 array. Five meal components, each with two levels, were investigated. One level of each component was used for each photo, in total 2 5 = 32 combinations.The respondents were asked to select the meal they preferred the most, the second most and the least, respectively. Significant interactions were found between meal components and background variables such as, gender, age, geographic variables, purchase store and level of education. The current procedure can be applied to help solve a number of problems involving consumer choices.PRACTICAL APPLICATIONS This study outlines an approach to use visual images for investigations of food. Our results suggest that rather complex food stimuli of great similarity can be used to subdivide consumers based on sociodemographic background variables. We present an efficient and cheap quick method that provides and captures more information than an ordinary survey that focuses merely on the most preferred option. As a prerequisite for success, stimuli should be well known and appropriately selected. Hence, the present quick method can easily be applied for several practical purposes, such as pretesting, labeling, product flop prevention, and for specific optimization and selection tasks, e.g., convenience meals and institutional meal services in various contexts. The conjoint layout used allows for late‐based segmentation. It further allows for estimation on aggregate as well as individual level. The current approach is useful for database and/or online implementation.