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A. MUNOZ, Consultant, 234 Robin Hood Rd., Mountainside, NJ 07092 and D. S. Lundahl, CAMO Inc., P.O. Box 1628, Corvallis, OR 97339.

The understanding of the acceptability of foods and beverages is mission critical to the food industry. Researchers developing products for international markets must understand the intrinsic product characteristics that drive acceptance. However, extrinsic cultural factors influence consumer preference by shaping attitudes, behaviors, wants, needs, and exposure to various sensory experiences. It is the knowledge of the complex relationships between these extrinsic cultural factors and intrinsic product characteristics that can separate the product success from failure.

Many researchers agree on the importance of extrinsic cultural factors. However, there are difficulties in their measurement limiting study depth. There has also been a large amount of effort made to model the processes for food preference and acceptances among consumers. However, models used by product developers often are limited in scope to acceptance and quantitative food quality measurements. Further, models used by marketing researchers often are limited to acceptance and consumer segmentation. More inclusive models are needed which identify the relationships between consumer segments, acceptance and product qualities.

Traditional statistical methods used for modeling these complex relationships often fail due to issues in model instability (e.g. multi-collinearity issues from highly co-varying input variables) and the need to estimate more data (observations) than model parameters. Principal component regression and partial least squares regression techniques have provided new modeling tools to model the sensory, compositional, and structural qualities of products to acceptance. However, these new models do not incorporate extrinsic cultural factors. Classification methods such as factor analysis and hierarchical cluster analysis provide a means to segment consumers into groups with similar preferences. In this presentation, these classification methods in conjunction with PLS modeling methods will be used to demonstrate their applications in gaining understanding into how cultural extrinsic factors and intrinsic product qualities drive consumer acceptance.