New PDF release: Analyzing decision making: metric conjoint analysis

By Jordan J. Louviere

ISBN-10: 0803927576

ISBN-13: 9780803927575

This quantity introduces the idea, process, and purposes of 1 kind of conjoint research process. those strategies are used to check person judgement and choice procedures. established upon info Integration concept, metric conjoint research permits evaluate of multi-attribute possible choices in line with period point info. The version, which justifies use of metric conjoint tools and the statistical ideas drawn from it, are the middle of this monograph. additionally defined are functions of the version in advertising and marketing, psychology, economics, sociology, making plans, and different disciplines, all of which relate to forecasting the decision-making habit of people.

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Extra resources for Analyzing decision making: metric conjoint analysis

Sample text

Guilford, 1954; Lavidge and Steiner, 1961; McClelland, 1979). 1. After acquiring information and learning about alternatives, consumers define a set of determinant attributes (Alpert, 1971) to use to compare and evaluate brands in a particular product class. After comparing available brands with respect to each of the attributes, consumers eliminate some alternatives and develop final ''choice sets" of brands from which to choose (including the choice to delay or not purchase at all). The process by which consumers compare brands on sets of determinant attributes, form final choice sets, and make choices is complicated.

We adhere to the previous notation established in Chapter 1, recalling that interest centers on responses made by consumers on category-rating scales. The problem, therefore, is to diagnose (if we lack an a priori hypothesis) or test (if we have an a priori hypothesis) an appropriate decision model for a consumer who evaluates combinations of levels of two determinant attributes on a category-rating scale. Let us consider three possible models for this problem (although there are other possibilities): Page 29 where all terms are as defined in Chapter 1.

We also assume elementary knowledge of experimental design, and we emphasize the design and analysis of fractional factorial experiments because of their value in practical work. Some reference to basic design theory, however, is necessary, and where such reference is made we shall note textbooks in which further information can be found. 1 Two-Attribute (Factor) Designs The two-factor case serves as an introduction to the problem and as a basis for a discussion of important concepts and issues that arise in larger problems.

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Analyzing decision making: metric conjoint analysis by Jordan J. Louviere


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