Analyzing the Profitability Performance of SMEs Using a Neural Model

Dumitru-Iulian Nastac (), Alexandru Isaic-Maniu () and Irina Dragan ()
Additional contact information
Dumitru-Iulian Nastac: Politehnica University of Bucharest
Alexandru Isaic-Maniu: Centre for Industrial and Service Economics, Romanian Academy

ECONOMIC COMPUTATION AND ECONOMIC CYBERNETICS STUDIES AND RESEARCH, 2017, vol. 51, issue 4, 55-71

Abstract: Special models of artificial neural networks (ANNs) have proven their worth in various and sometime unexpected domains. In this paper, our focus was to develop an ANN application in order to analyze the financial performance of the SMEs in Romania. For historical reasons, this sector seems to be still weakly developed in that country, both quantitative (being situated on one of the last places in the EU's entrepreneurial intensity) and qualitative, having a weak economic performance with a modest contribution to GDP. Literature shows the importance of this sector for the economies of different countries, and diverse scientific methods used for its description and analysis. One of our research purposes was the identification of those factors that condition the profitability of companies, thus providing useful directions and possible strategies for developing the SME sector. The selected information source was represented by the annual balance sheets, from about 8000 of medium-sized companies in Romania. As a means of verifying the obtained results, econometric methods were used, such as regression analysis, which could identify and validate the models that emphasize the dynamics with different influence factors. The conclusions obtained could prove their utility in both the investigation of the combining quantitative methods (ANN and regression), and in the SME sector management plan.

Keywords: SMEs; neural networks; classification; econometric models. (search for similar items in EconPapers)
JEL-codes: C10 C38 C52 M11 P12 (search for similar items in EconPapers)
Date: 2017
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
ftp://www.eadr.ro/RePEc/cys/ecocyb_pdf/ecocyb4_2017p55-71.pdf

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:cys:ecocyb:v:50:y:2017:i:4:p:55-71

Access Statistics for this article

ECONOMIC COMPUTATION AND ECONOMIC CYBERNETICS STUDIES AND RESEARCH is currently edited by Gheorghe RUXANDA

More articles in ECONOMIC COMPUTATION AND ECONOMIC CYBERNETICS STUDIES AND RESEARCH from Faculty of Economic Cybernetics, Statistics and Informatics Contact information at EDIRC.
Bibliographic data for series maintained by Corina Saman ().