Comparison of the multivariate and bivariate analysis of corporate competitiveness factors synergy
| Authors | |
|---|---|
| Year of publication | 2013 |
| Type | Article in Periodical |
| Magazine / Source | Ekonomická revue |
| MU Faculty or unit | |
| Citation | |
| web | Plný text výsledku |
| Doi | http://dx.doi.org/10.7327/cerei.2013.06.02 |
| Field | Management and administrative |
| Keywords | Competitiveness; competitiveness factors; corporate financial performance; multidimensional statistical methods; Sequential Forward Floating Search; synergy; k-Nearest Neighbours |
| Attached files | |
| Description | Corporate competitiveness is influenced by a number of factors. Their impact is not partial, but synergistic. It is necessary to respect the phenomenon of synergy consistently when examining which of these potential competitiveness attributes can really function as these factors. Consequently, feature selection and classification methods of statistical pattern recognition have been used for the multivariate statistical analysis of and search for competitiveness factors. The calculations conducted herein show that the Sequential Forward Floating Search method in combination with k-Nearest Neighbours classification is capable of capturing the synergistic effect of the whole set of factors, providing much better results than simple bivariate analysis methods that test only the partial effects of individual factors. |
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