Prediction of institutional sector development and analysis of enterprises active in agriculture

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dc.contributor.authorStehel, Vojtěch
dc.contributor.authorHorák, Jakub
dc.contributor.authorVochozka, Marek
dc.contributor.otherEkonomická fakultacs
dc.date.accessioned2019-11-28T10:20:13Z
dc.date.available2019-11-28T10:20:13Z
dc.description.abstractThe overall EU agricultural productivity growth has slowed down in recent years and has lagged behind leading global competitors, which is mainly due to decreasing number of employees in agriculture. Technical inefficiency is then an important phenomenon of the Czech agriculture and its individual sectors. Agriculture development should be established on scientific bases. One of the basic principles of sustainable agriculture is therefore forecasting its future development. In recent years, several agricultural economists have been engaged in comparing forecasts with various other methods and their conclusions generally correspond to commonly accepted beliefs. At present, artificial intelligence can be definitely recognized as a useful tool for business analyses and forecasting. The objective of the contribution is an analysis of companies active in agriculture of the Czech Republic using Kohonen network and the subsequent prediction of their development. A data set is created, which includes complete data from financial statements of 4,201 companies active in agriculture of the Czech Republic in 2016. The set of companies is generated from the Bisnode Albertina database. The data set is subsequently subjected to cluster analysis using Kohonen network. For cluster analysis, Dell´s Statistica software, version 12 is used. The set is divided into three parts: training data set, testing data set, validation data set. Topological length and width of Kohonen network are set at 10. The number of iterations is set at 10 000. Subsequently, the individual clusters are subjected to analysis of absolute and selected indicators (or more precisely, their mean values – arithmetic average) and the results are interpreted. It can be stated that the agriculture companies show very favorable values – optimal assets level, acceptable financing structure and adequate economic result. It can be even stated that the indicators show above-average values compared to other investment options.en
dc.formattext
dc.identifier.doi10.15240/tul/001/2019-4-007
dc.identifier.eissn2336-5604
dc.identifier.issn1212-3609
dc.identifier.urihttps://dspace.tul.cz/handle/15240/154266
dc.language.isoen
dc.publisherTechnická Univerzita v Libercics
dc.publisherTechnical university of Liberec, Czech Republicen
dc.publisher.abbreviationTUL
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dc.relation.ispartofEkonomie a Managementcs
dc.relation.ispartofEconomics and Managementen
dc.relation.isrefereedtrue
dc.rightsCC BY-NC
dc.subjectagriculture enterprisesen
dc.subjectinstitutional sector developmenten
dc.subjectpredictionen
dc.subjectartificial neural networksen
dc.subjectvalue of the businessen
dc.subject.classificationC45
dc.subject.classificationO13
dc.titlePrediction of institutional sector development and analysis of enterprises active in agricultureen
dc.typeArticleen
local.accessopen
local.citation.epage118
local.citation.spage103
local.facultyFaculty of Economics
local.filenameEM_4_2019_07
local.fulltextyes
local.relation.abbreviationE+Mcs
local.relation.abbreviationE&Men
local.relation.issue4
local.relation.volume22
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