Combining hedonic information and CATA description for consumer segmentation
Published 2021 View Full Article
- Home
- Publications
- Publication Search
- Publication Details
Title
Combining hedonic information and CATA description for consumer segmentation
Authors
Keywords
Liking, CATA, Penalty-lift analysis, Consumer segmentation, Cluster stability, Sensometrics
Journal
FOOD QUALITY AND PREFERENCE
Volume 95, Issue -, Pages 104358
Publisher
Elsevier BV
Online
2021-08-12
DOI
10.1016/j.foodqual.2021.104358
References
Ask authors/readers for more resources
Related references
Note: Only part of the references are listed.- Check-all-that-apply (CATA) questions: Sensory term citation frequency reflects rated term intensity and applicability
- (2020) Sara R. Jaeger et al. FOOD QUALITY AND PREFERENCE
- The item-by-use (IBU) method for measuring perceived situational appropriateness: A methodological characterisation using CATA questions
- (2019) Sara R. Jaeger et al. FOOD QUALITY AND PREFERENCE
- Sensory drivers of product-elicited emotions are moderated by liking: Insights from consumer segmentation
- (2019) Sara Spinelli et al. FOOD QUALITY AND PREFERENCE
- An assessment of the CATA-variant of the EsSense Profile®
- (2018) Sara R. Jaeger et al. FOOD QUALITY AND PREFERENCE
- Consumer segmentation in multi-attribute product evaluation by means of non-negatively constrained CLV3W
- (2018) Véronique Cariou et al. FOOD QUALITY AND PREFERENCE
- A new approach for the analysis of data and the clustering of subjects in a CATA experiment
- (2018) Fabien Llobell et al. FOOD QUALITY AND PREFERENCE
- Segmentation of consumers in preference studies while setting aside atypical or irrelevant consumers
- (2016) E. Vigneau et al. FOOD QUALITY AND PREFERENCE
- CLV3W: A clustering around latent variables approach to detect panel disagreement in three-way conventional sensory profiling data
- (2016) Tom F. Wilderjans et al. FOOD QUALITY AND PREFERENCE
- Testing for differences between impact of attributes in penalty-lift analysis
- (2016) Michael Meyners FOOD QUALITY AND PREFERENCE
- Examination of sensory product characterization bias when check-all-that-apply (CATA) questions are used concurrently with hedonic assessments
- (2015) Gastón Ares et al. FOOD QUALITY AND PREFERENCE
- Check-all-that-apply data analysed by Partial Least Squares regression
- (2015) Åsmund Rinnan et al. FOOD QUALITY AND PREFERENCE
- Comparison of sensory product profiles generated by trained assessors and consumers using CATA questions: Four case studies with complex and/or similar samples
- (2015) Gastón Ares et al. FOOD QUALITY AND PREFERENCE
- On the Added Value of Bootstrap Analysis for K-Means Clustering
- (2015) Joeri Hofmans et al. JOURNAL OF CLASSIFICATION
- Lack of evidence that concurrent sensory product characterisation using CATA questions bias hedonic scores
- (2014) Sara R. Jaeger et al. FOOD QUALITY AND PREFERENCE
- Stability of market segmentation with cluster analysis – A methodological approach
- (2014) Henriette Müller et al. FOOD QUALITY AND PREFERENCE
- Existing and new approaches for the analysis of CATA data
- (2013) Michael Meyners et al. FOOD QUALITY AND PREFERENCE
- Penalty analysis based on CATA questions to identify drivers of liking and directions for product reformulation
- (2013) Gastón Ares et al. FOOD QUALITY AND PREFERENCE
- Finding and explaining clusters of consumers using the CLV approach
- (2011) Evelyne Vigneau et al. FOOD QUALITY AND PREFERENCE
- CATA penalty/reward
- (2011) Dave Plaehn FOOD QUALITY AND PREFERENCE
- Combining extrinsic and intrinsic information in consumer acceptance studies
- (2011) Elena Menichelli et al. FOOD QUALITY AND PREFERENCE
- A new approach to product set selection and segmentation in preference mapping
- (2009) Susanne Bølling Johansen et al. FOOD QUALITY AND PREFERENCE
- New modifications and applications of fuzzy -means methodology
- (2007) Ingunn Berget et al. COMPUTATIONAL STATISTICS & DATA ANALYSIS
Find Funding. Review Successful Grants.
Explore over 25,000 new funding opportunities and over 6,000,000 successful grants.
ExploreBecome a Peeref-certified reviewer
The Peeref Institute provides free reviewer training that teaches the core competencies of the academic peer review process.
Get Started