Multidimensional Scaling

TAMMO H.A. BIJMOLT and MICHEL WEDEU two-dimensional marking has been applied to a replete(p) figure of merchandise problems, in particular to perceptual mapping base on dissimilitude judgments. The introduction of methods based on the maximal likeliness principle is one of the most important developments. In this article, the authors compargon the triad available Maximum Likelihood Multidimensional Scaling (MLMDS) methods, namely, MULTISCALE, MAXSCAL, and PROSCAL, and the traditionalistic multidimensional scaling (MDS) method KYST in a four-card monte Carlo study with 243 synthetic data sets. The MLMDS methods exceed KYST with respect to find the perceptual maps. MAXSCAL recovers the true distances between brands jolly better than MULTISCALE, which is fair better than PROSCAL. With regard to distance recovery, the MLMDS methods atomic number 18 quite robust to violations of distributional assumptions. The decision criteria for selecting the number of dimensions be l ess robust to distributional violations. The results support the use of gentle Akaike Information Criterion for the selection of the number ot dimensions. The authors recommend that disagreement judgments be collected on interval scales or on ordinal scales with a substantial number of scale values.

The authors distinguish implications of the results for the design and analysis of perceptual mapping studies. A equivalence of Multidimensional Scaling Methods for Perceptual Mapping Multidimensional scaling (MDS) is otie of the hot tools of marketing research (Naumann, Jackson, and Wolfe !994; Wind, Rao. and Green 1991). It is applied to a wide range of marketing problems (Cooper 1 983), in particular in the demesne of perce! ptual mapping, for which the purpose Is to derive a spatial represetitation of the market. In the vast majority of these studies, traditional MDS methcxls are employed, such as KYST (Kruskal, Young, and Seery 1977) and INDSCAL (Carroll and Chang 1970), Although the introduction of methods based on the...If you want to descend a full essay, order it on our website: OrderEssay.net

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