Cross-national logo evaluation analysis: an individual-level approach

van der Lans, Ralf, Cote, Joseph A., Cole, Catherine A., Leong, Siew Meng, Smidts, Ale, Henderson, Pamela W., Bluemelhuber, Christian, Bottomley, Paul Andrew ORCID: https://orcid.org/0000-0001-8131-6768, Doyle, John R., Fedorikhin, Alexander, Moorthy, Janakiraman, Ramaseshan, B. and Schmitt, Bernd H. 2009. Cross-national logo evaluation analysis: an individual-level approach. Marketing Science 28 (5) , pp. 968-985. 10.1287/mksc.1080.0462

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Abstract

The universality of design perception and response is tested using data collected from 10 countries: Argentina, Australia, China, Germany, Great Britain, India, The Netherlands, Russia, Singapore, and the United States. A Bayesian, finite-mixture, structural equation model is developed that identifies latent logo clusters while accounting for heterogeneity in evaluations. The concomitant variable approach allows cluster probabilities to be country specific. Rather than a priori defined clusters, our procedure provides a posteriori cross-national logo clusters based on consumer response similarity. Our model reduces the 10 countries to three cross-national clusters that respond differently to logo design dimensions: the West, Asia, and Russia. The dimensions underlying design are found to be similar across countries, suggesting that elaborateness, naturalness, and harmony are universal design dimensions. Responses (affect, shared meaning, subjective familiarity, and true and false recognition) to logo design dimensions (elaborateness, naturalness, and harmony) and elements (repetition, proportion, and parallelism) are also relatively consistent, although we find minor differences across clusters. Our results suggest that managers can implement a global logo strategy, but they also can optimize logos for specific countries if desired.

Item Type:	Article
Date Type:	Publication
Status:	Published
Schools:	Business (Including Economics)
Subjects:	H Social Sciences > H Social Sciences (General) H Social Sciences > HD Industries. Land use. Labor H Social Sciences > HD Industries. Land use. Labor > HD28 Management. Industrial Management H Social Sciences > HF Commerce H Social Sciences > HG Finance
Uncontrolled Keywords:	Design ; Logos ; International marketing; Standardization ; Adaptation ; Structural equation models ; Gibbs sampling ; Concomitant variable ; Bayesian ; Mixture models
Publisher:	inForms
ISSN:	0732-2399
Last Modified:	19 Oct 2022 09:56
URI:	https://orca.cardiff.ac.uk/id/eprint/22693

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