Investigating paired differences for data sets with special structures after principal component analysis

John Castura/ September 18, 2023/ Oral Presentation/ 0 comments

Principal component analysis (PCA) is a popular technique for summarizing and exploring multivariate data sets. We propose how to conduct PCA of results from sensory studies that have a special structure, where only a subset of the product paired comparisons are of interest. We illustrate the proposed approach with two data sets, both from trained sensory panels. In the first

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Evaluation of complementary numerical and visual approaches for investigating pairwise comparisons after principal component analysis

John Castura/ November 16, 2022/ Oral Presentation/ 0 comments

We propose and evaluate numerical and visual methods for investigating paired comparisons after principal component analysis (PCA). PCA results can be visualized to facilitate an understanding of the relationships between the products and the sensory attributes. But identifying and visualizing significant product differences in multiple PCs simultaneously is not straightforward. A benefit of the proposed methods is that they provide

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Clustering consumers based on their hedonic responses

John Castura/ November 9, 2022/ Oral Presentation/ 0 comments

Consumers are diverse in their product perceptions. But within the consumer population there are often consumer segments whose product perceptions are relatively homogeneous. To discover these consumer segments, consumers’ product-related responses are submitted to a cluster analysis. The particular cluster analysis is chosen by the researcher. But the choice of clustering algorithm can have profound consequences on the clustering solution

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Analyzing data from sensory discrimination tests: Parameter estimates and confidence regions

John Castura/ June 30, 2019/ Oral Presentation/ 0 comments

The sensory profile of a food product is an important contributor to its identity, and is linked to brand value. Sensory testing provide an objective way to ensure that the product’s target sensory profile is achieved, e.g., after making production changes. Historical data, including business outcomes, can provide context to assist decision making. Unreplicated sensory discrimination tests without response bias

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Is less always more?

John Castura/ June 5, 2019/ Oral Presentation, Symposium/ 0 comments

Here is a question to be answered in mythbusters style: “Do the number of available choices create a choice overload effect in consumers?” As a starting point, consider a well-known study in which consumers receive a coupon in a grocery store after tasting two jams. Consumers who were limited to choosing from only 6 jams followed through with purchase more

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Or is less just less?

John Castura/ June 5, 2019/ Oral Presentation, Symposium/ 0 comments

The authors of the meta-analysis suggest that the difficulties associated with making choices might be more related to the complexity of the choice task and the cognitive decision-making factors than simply to the number of choices. Other authors have suggested particular underlying factors. The claim of choice overload based strictly on the number of choices seems both capture and oversimplify

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Consumer perceptions of beer: The role of individual differences

John Castura/ June 3, 2019/ Oral Presentation/ 0 comments

Taste plays a key role in a consumer’s attitude towards food products and can influence the consumption of that product. One factor, thermal taster status, is determined when the tongue is warmed or cooled, whereby thermal tasters experience phantom taste sensations, while thermal non-tasters do not. Using temporal-check-all-that-apply sensory methodology, we simultaneously investigated the impact of thermal taster status and

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