Performance Factors of Czech Companies Identified Using Statistical Pattern Recognition: Interpretation of Results

ČÁSTEK, Ondřej. Performance Factors of Czech Companies Identified Using Statistical Pattern Recognition: Interpretation of Results. Prague economic papers. Praha: Oeconomica, 2018, vol. 27, No 4, p. 397-416. ISSN 1210-0455. Available from: https://dx.doi.org/10.18267/j.pep.659.

Basic information

• Original name: Performance Factors of Czech Companies Identified Using Statistical Pattern Recognition: Interpretation of Results
• Authors: ČÁSTEK, Ondřej (203 Czech Republic, guarantor, belonging to the institution).
• Edition: Prague economic papers, Praha, Oeconomica, 2018, 1210-0455.

Other information

• Original language: English
• Type of outcome: Article in a journal
• Field of Study: 50204 Business and management
• Country of publisher: Czech Republic
• Confidentiality degree: is not subject to a state or trade secret
• WWW: URL
• Impact factor: Impact factor: 0.629
• RIV identification code: RIV/00216224:14560/18:00101184
• Organization unit: Faculty of Economics and Administration
• Doi: http://dx.doi.org/10.18267/j.pep.659
• UT WoS: 000442975600002
• Keywords in English: corporate financial performance; statistical pattern recognition; dependency-aware feature selection; factors of corporate performance; strategy; FDI
• Tags: Reviewed

Abstract

The paper interprets factors of corporate performance identified by means of statistical pattern recognition techniques. A Dependency-Aware Feature algorithm with non-linear regression model ranked 74 potential factors of corporate performance according to their contribution to corporate performance prediction. This paper brings consecutive statistical analyses, which interpret the effects of Strategy, FDI, Share of Export, Top Management Performance Pay, and Workers’ Performance Pay on corporate performance. Furthermore, the analyses reveal strong mutual moderating interdependencies. On the national scale, the paper brings evidence that the companies from the industries researched can use the stational techniques to learn about corporate performance factors. On a global scale, the paper introduces the contribution of Dependency-Aware Feature selection in the field of management and confirms the need for a multidimensional contingency approach in researching corporate performance. The results are based on a sample of 432 private limited or joint stock companies located in the Czech Republic operating in the manufacturing and construction industries and employing 50 or more people.

Links

• GAP403/12/1557, research and development project: Name: Přístupy k identifikaci faktorů výkonnosti podniků s důrazem na metody výběru příznaků ve statistickém rozpoznávání.