Nalazite se na CroRIS probnoj okolini. Ovdje evidentirani podaci neće biti pohranjeni u Informacijskom sustavu znanosti RH. Ako je ovo greška, CroRIS produkcijskoj okolini moguće je pristupi putem poveznice www.croris.hr
izvor podataka: crosbi !

Financial Self-Organizing Map of Croatian small- sized enterprises (CROSBI ID 638454)

Prilog sa skupa u zborniku | izvorni znanstveni rad | međunarodna recenzija

Župan, Mario ; Letinić, Svjetlana ; Budimir, Verica Financial Self-Organizing Map of Croatian small- sized enterprises // Proceedings of the 2016 SAI Computing Conference / Cavoukian, Ann ; Makki, Kami ; Serbedzija, Nikola et al. (ur.). London : Delhi: Institute of Electrical and Electronics Engineers (IEEE), 2016. str. 139-147

Podaci o odgovornosti

Župan, Mario ; Letinić, Svjetlana ; Budimir, Verica

engleski

Financial Self-Organizing Map of Croatian small- sized enterprises

Abstract—For many years, the relevant analyses have indicated problems in the functioning of the Croatian small-sized enterprises sector. It has been marked by recession, changes in legislation, financing problems, poor cash flow, dependence on large and state-owned companies and the low rate of survival. At the same time, the small-sized enterprises sector has been referred to as a generator of economic development, because of its size, innovation and adaptability. The uncertainties of the business future are forcing small enterprises to adopt ad hoc decisions, which are based on unstructured information. The most common aims are to reduce the current tax base, increase current liquidity and find financing sources. The aims are not associated with future obligations or the core business development. Decisions are rarely based on financial analysis, which requires a high-quality accounting information system, financial information about other enterprises, and methods that will generate usable and transparent information about several aspects of the business. Entrepreneurs, macro analysts, bankers and investors need analytical systems that generate simple, understandable and usable information, based on a number of relevant financial ratios. The construction of such analytical systems is the subject of this work. Current global and domestic researches use unsupervised methods of data mining because they provide aggregated information in predicting financial distress and bankruptcy, fraud detection, credit risk assessment, measurement and comparison of financial performance. Data mining methods have advantage over traditional statistical methods for their classification and prediction capabilities, as well as the ability to work with non-linear relationships between features. Based on a sample of 2, 200 financial statements, which entities submitted in 2011 and 2012, self- organizing model created was built that successfully identify the current state of the small-sized enterprise sector. In total, 3 clusters have been identified, whose sustainability is proven by clustering quality indexes.

Small-sized enterprises sector ; Financial ratios ; Self-organizing maps ; Cluster analysis

nije evidentirano

nije evidentirano

nije evidentirano

nije evidentirano

nije evidentirano

nije evidentirano

Podaci o prilogu

139-147.

2016.

objavljeno

Podaci o matičnoj publikaciji

Proceedings of the 2016 SAI Computing Conference

Cavoukian, Ann ; Makki, Kami ; Serbedzija, Nikola ; Khaddaj Mallat, Nazih

London : Delhi: Institute of Electrical and Electronics Engineers (IEEE)

978-1-4673-8460-5

Podaci o skupu

Science and Information (SAI) Conference 2016

ostalo

13.06.2016-15.06.2016

London, Ujedinjeno Kraljevstvo

Povezanost rada

Ekonomija

Indeksiranost