Adaptive Multidimensional Scaling: The Spatial Representation of Brand Consideration and Dissimilarity Judgments

T.H.A. Bijmolt, M. Wedel, W.S. DeSarbo

Research output: Working paperDiscussion paperOther research output

339 Downloads (Pure)


We propose Adaptive Multidimensional Scaling (AMDS) for simultaneously deriving a brand map and market segments using consumer data on cognitive decision sets and brand dissimilarities.In AMDS, the judgment task is adapted to the individual respondent: dissimilarity judgments are collected only for those brands within a consumers' awareness set.Thus, respondent fatigue and subjects' unfamiliarity with any subset of the brands are circumvented; thereby improving the validity of the dissimilarity data obtained, as well as the multidimensional spatial structure derived.Estimation of the AMDS model results in a spatial map in which the brands and derived segments of consumers are jointly represented as points.The closer a brand is positioned to a segment's ideal brand, the higher the probability that the brand is considered and chosen.An assumption underlying this model representation is that brands within a consumers' consideration set are relatively similar.In an experiment with 200 subjects and 4 product categories, this assumption is validated.We illustrate adaptive multidimensional scaling on commercial data for 20 midsize car brands evaluated by 212 members of a consumer panel.Potential applications of the method and future research opportunities are discussed.
Original languageEnglish
Place of PublicationTilburg
Number of pages38
Publication statusPublished - 2002

Publication series

NameCentER Discussion Paper


  • scaling
  • brands
  • market segmentation


Dive into the research topics of 'Adaptive Multidimensional Scaling: The Spatial Representation of Brand Consideration and Dissimilarity Judgments'. Together they form a unique fingerprint.

Cite this