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Bayesian Network Analysis of Brand Concept Maps


Abstract We apply a Bayesian network-based approach for determining the structure of consumers' brand concept maps, and we further extend this approach in order to provide a precise delineation of the set of cognitive variations of that brand concept map structure which can simultaneously coexist within the data. This methodology can operate with nonlinear as well as linear relationships between the variables, and utilizes simple Likert-style marketing survey data as input. In addition, the method can operate without any a priori hypothesized structures or relations among the brand associations in the model. The resulting brand concept map structures delineate directional (as opposed to simply correlational) relations among the brand association... (more)
Created Date 2013
Contributor Brownstein, Steven (Author) / Reingen, Peter (Advisor) / Kumar, Ajith (Committee member) / Mokwa, Michael (Committee member) / Arizona State University (Publisher)
Subject Marketing
Type Doctoral Dissertation
Extent 229 pages
Language English
Copyright
Reuse Permissions All Rights Reserved
Note Ph.D. Business Administration 2013
Collaborating Institutions Graduate College / ASU Library
Additional Formats MODS / OAI Dublin Core / RIS


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Description Dissertation/Thesis