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dc.contributor.authorSuchánek, Petr
dc.contributor.authorŠterba, Martin
dc.date.accessioned2018-02-06T07:00:58Z
dc.date.available2018-02-06T07:00:58Z
dc.date.issued2017
dc.identifier.citationTrendy v podnikání = Business trends : vědecký časopis Fakulty ekonomické ZČU v Plzni. 2017, č. 3, s. 3-15.cs
dc.identifier.issn1805-0603
dc.identifier.urihttp://hdl.handle.net/11025/29160
dc.format13 s.cs
dc.format.mimetypeapplication/pdf
dc.language.isoenen
dc.publisherZápadočeská univerzita v Plznics
dc.relation.ispartofseriesTrendy v podnikánícs
dc.rights© Západočeská univerzita v Plznics
dc.subjecttvorba cenycs
dc.subjectvýkoncs
dc.subjectkoeficient EVAcs
dc.subjectfinanční analýzacs
dc.subjectpotravinářské společnostics
dc.titleAn analysis of value creation in Czech food companiesen
dc.typečlánekcs
dc.typearticleen
dc.rights.accessopenAccessen
dc.type.versionpublishedVersionen
dc.description.abstract-translatedThe subject of this article is based on an analysis of food companies in the Czech Republic. The aim of the article is to identify differences in value creation (including causal ones) across the companies. We chose a basic sample of all 931 Czech companies in the food industry sector, in segments such as meat and fish processing, milk and dairy products and so on. Of this group, 707 companies had sufficient and available financial data for the year 2014. In the second step we calculated the EVA and ROE indicators for those companies. Subsequently, 382 successful companies (EVA indicator > 0) and 103 extremely unsuccessful companies (ROE < 0) were selected for further analysis. For these companies, a profile analysis, considering difference in averages, was done which allowed us to compare each of selected financial indicators in both groups of companies and to find the greatest differences between them. In the next step a logistic regression model was used (for indicators with a statistically significant difference) identifying which indicators would serve as the basis for a model for distinguishing high-performing companies from low-performing ones. Thus obtained indicators are evaluated on the basis of the food company model. We created a CVM model which is able to identify companies which create values in 97.1 % of cases and in 79.6 % of cases is able to recognize companies which destroy value. An advantage of the model is its ability to detect areas where the companies are strengthened or weakened due to used financial indicators.en
dc.subject.translatedvalue creationen
dc.subject.translatedperformanceen
dc.subject.translatedEVA ratioen
dc.subject.translatedfinancial analysisen
dc.subject.translatedfood companiesen
dc.type.statusPeer-revieweden
Vyskytuje se v kolekcích:Číslo 3 (2017)
Číslo 3 (2017)

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