Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
4943685 | Expert Systems with Applications | 2016 | 14 Pages |
Abstract
Working on the top 100 Interbrand world corporate brands dataset over the 10-years period 2001-10, we analyze the relative positioning of country brands as derived from the structural characteristics of the corresponding portfolios of top corporate brands. We find that the structural complexity of both sector and country variables are not correlated with brand equity. Moreover, we apply an innovative ANN methodology, AutoCM, to build the Minimum Spanning Tree (MST) of the multi-dimensional similarities among the top corporate brands structures at country level, and carry out a further related analysis in terms of the so called Maximum Regular Graph (MRG). We find that while the USA dominates the ranking of top brands at a global level, it does not have a central positioning in the MST and MRG, whereas Germany and other European and Far-Eastern countries do. We show how these results may have significant implications for the strategic intelligence analysis of country and corporate brands, and of their inter-relatedness. Moreover, we illustrate how AutoCM qualifies as a new computational approach that usefully expands the toolbox of scholars and analysts in corporate and country branding in a relevant, as yet unexplored direction.
Keywords
Related Topics
Physical Sciences and Engineering
Computer Science
Artificial Intelligence
Authors
Guido Ferilli, Pier Luigi Sacco, Emanuele Teti, Massimo Buscema,