ČÁSTEK, Ondřej, Ladislav BLAŽEK, Pavel PUDIL and Petr SOMOL. Comparison of the multivariate and bivariate analysis of corporate competitiveness factors synergy. Ekonomická revue. Ostrava: VŠB - Technická univerzita Ostrava, 2013, XVI, No 2, p. 67 - 77. ISSN 1212-3951. doi:10.7327/cerei.2013.06.02.
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Basic information
Original name Comparison of the multivariate and bivariate analysis of corporate competitiveness factors synergy
Name (in English) Comparison of the multivariate and bivariate analysis of corporate competitiveness factors synergy
Authors ČÁSTEK, Ondřej (203 Czech Republic, guarantor, belonging to the institution), Ladislav BLAŽEK (203 Czech Republic, belonging to the institution), Pavel PUDIL (203 Czech Republic) and Petr SOMOL (203 Czech Republic).
Edition Ekonomická revue, Ostrava, VŠB - Technická univerzita Ostrava, 2013, 1212-3951.
Other information
Original language Czech
Type of outcome Article in a journal
Field of Study 50600 5.6 Political science
Country of publisher Czech Republic
Confidentiality degree is not subject to a state or trade secret
WWW Plný text výsledku
RIV identification code RIV/00216224:14560/13:00066244
Organization unit Faculty of Economics and Administration
Doi http://dx.doi.org/10.7327/cerei.2013.06.02
Keywords (in Czech) Konkurenceschopnost; faktory konkurenceschopnosti; finanční výkonnost; vícerozměrné statistické metody; sekvenční dopředný plovoucí výběr; synergie; k-nejbližších sousedů
Keywords in English Competitiveness; competitiveness factors; corporate financial performance; multidimensional statistical methods; Sequential Forward Floating Search; synergy; k-Nearest Neighbours
Tags International impact, Reviewed
Changed by Changed by: doc. Ing. Ondřej Částek, Ph.D., učo 4209. Changed: 10. 7. 2013 08:52.
Abstract
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.
Abstract (in English)
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.
Links
GAP403/12/1557, research and development projectName: Přístupy k identifikaci faktorů výkonnosti podniků s důrazem na metody výběru příznaků ve statistickém rozpoznávání.
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