Using clustering of rankings to explain brand preferences with personality and socio-demographic variables

DOI10.1080/02664763.2017.1339025OpenAlexW2605609088WikidataQ60471512 ScholiaQ60471512MaRDI QIDQ5035747

Daniel Müllensiefen, Hedie Howells, Christian Hennig

Publication date: 22 February 2022

Published in: Journal of Applied Statistics (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1704.00959

zbMATH Keywords

distancelogistic regressioncluster analysispersonalityrandom forestsmarket segmentationranking datademographics

Mathematics Subject Classification ID

Classification and discrimination; cluster analysis (statistical aspects) (62H30) Clustering in the social and behavioral sciences (91C20) Consumer behavior, demand theory (91B42) Applications of statistics (62Pxx)

Related Items (3)

Comparing boosting and bagging for decision trees of rankings ⋮ A Kemeny distance-based robust fuzzy clustering for preference data ⋮ Estimating the number of clusters in a ranking data context

Uses Software

• R
• SPSS
• MASS (R)

Cites Work

• Mixtures of distance-based models for ranking data
• A mixture of experts model for rank data with applications in election studies
• Model-based clustering for multivariate partial ranking data
• Statistical Analysis of Financial Data in S-Plus
• Finding Groups in Data
• Some properties of clasical multi-dimesional scaling
• Clustering ranking data in market segmentation: a case study on the Italian McDonald's customers’ preferences
• Multistage Ranking Models
• Random forests
• A grade of membership model for rank data
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