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Exploring consumer knowledge structures using associative network analysis
Author(s) -
Teichert Thorsten A.,
Schöntag Katja
Publication year - 2010
Publication title -
psychology and marketing
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.035
H-Index - 116
eISSN - 1520-6793
pISSN - 0742-6046
DOI - 10.1002/mar.20332
Subject(s) - parallels , salient , associative property , perspective (graphical) , psychology , centrality , order (exchange) , cognition , computer science , artificial intelligence , mathematics , business , pure mathematics , mechanical engineering , finance , combinatorics , neuroscience , engineering
Abstract This paper offers a new perspective on consumer knowledge analysis that combines Human Associative Memory (HAM) models from cognitive psychology with network analytic approaches in order to gain deeper insights into consumers” mental representations, such as brand images. An illustrative case study compares the associative networks of a manufacturer brand with a retail brand and is used to demonstrate the application and interpretation of various network measures. Network analysis is conducted on three levels: Node‐level analysis yields insights about salient brand image components that can be affected through short‐term marketing activities. Group‐level analysis is concerned with brand image dimensions that characterize a brand and can be strategically influenced in the medium term. Finally, network‐level analysis examines the network structure as a whole, drawing parallels to brand imagery, which needs to be managed over the long term. Management implications are derived and suggestions for further research are provided. © 2010 Wiley Periodicals, Inc.