VALUE GENERATORS OF ENTERPRISES IN THE PROCESSING INDUSTRY

被引:0
|
作者
Machova, Veronika [1 ]
Rowland, Zuzana [2 ]
机构
[1] Univ Econ, Fac Business Adm, Nam W Churchilla 4, Prague 13067, Czech Republic
[2] Univ Zilina, Fac Operat & Econ Transport & Commun, Univ 8215-1, Zilina 01026, Slovakia
关键词
Value generators; artificial neural networks; economic value added; processing industry; NEURAL-NETWORKS; FIRM VALUE; MANAGEMENT;
D O I
暂无
中图分类号
F [经济];
学科分类号
02 ;
摘要
Purpose: The purpose of this article is to find out value generators of industrial enterprises having operated on the Czech market in 2015. Design/methodology/approach: The analysed data come from Albertina database. The dataset (data of their complete financial statements) contains records of 500 enterprises altogether. We calculate EVA value for shareholders (owners) of each enterprise of its operation on the market. Data mining and automated neural networks (radial basic function and multilayer perceptron networks) will be used as major tools. Findings: A reliable method was developed, and value generators of industrial enterprises having operated in the Czech Republic in 2015 were identified. The most important variables were defined. They are long-term receivables, material and energy consumption, power consumption, equity and basic capital. Research/practical implications: Enterprises of the processing industry should mainly focus on suggested value generators, their management and optimization. Thus, they get a higher EVA Equity and reach their major goal value growth for shareholders (owners). Originality/value: As a result, verifying the method for identifying value generators and appreciating their importance in the model should be considered as the most important part. At the same time, four central problems, which need to be dealt with within the further research, have been identified. They are wise choice of variables, dependence (or independence) of variables, size of the data file and stationarity of the data.
引用
收藏
页码:624 / 634
页数:11
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