In the field of marketing, perceptual mapping is used to reflect how customers visualize different brands onto the two-dimensional plane. One of the most important techniques used in perceptual mapping is Multidimensional Scaling (MDS for short). Multidimensional scaling, in its simplest definition, takes as input the perceived differences between brands (or other objects in other scientific disciplines) and maps this dissimilarity information in different dimensionalities (but less than the number of objects/brands). Although there are tens of different scaling techniques, one of the oldest is Torgerson’s Scaling, also known as “Classical MDS” (Torgerson, 1958). The main aim of this paper is to show the mathematical principles behind this scaling technique and explain the similarities and differences with Principle Components Analysis (PCA). In addition to this, a secondary aim is to illustrate the techniques with some examples and demonstrate the application of the techniques in the paper by the open source statistical software “R”
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