tailieunhanh - Lecture Marketing research (12th edition) - Chapter 21: Multidimensional scaling and conjoint analysis

Chapter 21 - Multidimensional scaling and conjoint analysis. In this chapter, the following content will be discussed: Multidimensional scaling, approaches to creating perceptual maps, attribute based approaches, comparison of factor and discriminant analysis,. | Marketing Research Aaker, Kumar, Leone and Day Twelfth Edition Instructor’s Presentation Slides 1 Chapter Twenty-One 2 Multidimensional Scaling and Conjoint Analysis Marketing Research 12th Edition Multidimensional Scaling Used to: Identify dimensions by which objects are perceived or evaluated Position the objects with respect to those dimensions Make positioning decisions for new and old products 3 Marketing Research 12th Edition 4 Perceptual map Attribute data Nonattribute data Similarity Preference Correspondence analysis MDS Discriminant analysis Factor analysis Approaches To Creating Perceptual Maps Marketing Research 12th Edition Attribute Based Approaches Attribute based MDS - MDS used on attribute data Assumption The attributes on which the individuals' perceptions of objects are based can be identified Methods used to reduce the attributes to a small number of dimensions Factor Analysis Discriminant Analysis Limitations Ignore the relative importance of particular attributes | Marketing Research Aaker, Kumar, Leone and Day Twelfth Edition Instructor’s Presentation Slides 1 Chapter Twenty-One 2 Multidimensional Scaling and Conjoint Analysis Marketing Research 12th Edition Multidimensional Scaling Used to: Identify dimensions by which objects are perceived or evaluated Position the objects with respect to those dimensions Make positioning decisions for new and old products 3 Marketing Research 12th Edition 4 Perceptual map Attribute data Nonattribute data Similarity Preference Correspondence analysis MDS Discriminant analysis Factor analysis Approaches To Creating Perceptual Maps Marketing Research 12th Edition Attribute Based Approaches Attribute based MDS - MDS used on attribute data Assumption The attributes on which the individuals' perceptions of objects are based can be identified Methods used to reduce the attributes to a small number of dimensions Factor Analysis Discriminant Analysis Limitations Ignore the relative importance of particular attributes to customers Variables are assumed to be intervally scaled and continuous 5 Marketing Research 12th Edition Comparison of Factor and Discriminant Analysis Identifies clusters of attributes on which objects differ Identifies a perceptual dimension even if it is represented by a single attribute Statistical test with null hypothesis that two objects are perceived identically Groups attributes that are similar Based on both perceived differences between objects and differences between people's perceptions of objects Dimensions provide more interpretive value than discriminant analysis 6 Factor Analysis Discriminant Analysis Marketing Research 12th Edition Perceptual Map of a Beverage Market 7 Marketing Research 12th Edition Basic Concepts of Multidimensional Scaling (MDS) MDS uses proximities (value which denotes how similar or how different two objects are perceived to be) among different objects as input Proximities data is used to produce a geometric configuration of points (objects)

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