The use of neural networks to determine value based drivers for SMEs operating in the rural areas of the Czech Republic
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F75081431%3A_____%2F20%3A00001797" target="_blank" >RIV/75081431:_____/20:00001797 - isvavai.cz</a>
Result on the web
<a href="http://economic-research.pl/Journals/index.php/oc/article/view/1788" target="_blank" >http://economic-research.pl/Journals/index.php/oc/article/view/1788</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.24136/OC.2020.014" target="_blank" >10.24136/OC.2020.014</a>
Alternative languages
Result language
angličtina
Original language name
The use of neural networks to determine value based drivers for SMEs operating in the rural areas of the Czech Republic
Original language description
The objective of the contribution is to determine through the use of artificial neural networks the relationship between business value drivers, or value based drivers (VBD), and EVA Equity, which is economic value added (EVA), of small and medium-sized enterprises operating in the rural areas of the Czech Republic.
Czech name
—
Czech description
—
Classification
Type
J<sub>SC</sub> - Article in a specialist periodical, which is included in the SCOPUS database
CEP classification
—
OECD FORD branch
50200 - Economics and Business
Result continuities
Project
—
Continuities
N - Vyzkumna aktivita podporovana z neverejnych zdroju
Others
Publication year
2020
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
Oeconomia Copernicana
ISSN
2083-1277
e-ISSN
—
Volume of the periodical
11
Issue of the periodical within the volume
2
Country of publishing house
PL - POLAND
Number of pages
22
Pages from-to
325-346
UT code for WoS article
000542035500005
EID of the result in the Scopus database
2-s2.0-85089102083