Katalóg evidencie publikačnej činnosti PU

ID záznamu:	187610
Kategória:	ADM
Autor:	Horváthová Jarmila (50%)
Autor:	Mokrišová Martina (50%)
Názov:	Comparison of the results of a data envelopment analysis model and logit model in assessing business financial health [elektronický dokument]
Zdroj:	Information [elektronický dokument]
Lokácia:	Roč. 11, č. 3. - Bazilej : Multidisciplinary Digital Publishing Institute, (2020), s. 1-20
ISSN:	2078-2489
URL:	https://www.mdpi.com/2078-2489/11/3/160/pdf
Ohlas:	[1] 2021. ŠTEFKO, Róbert, VAŠANIČOVÁ, Petra, JENČOVÁ, Sylvia et al. Management and economic sustainability of the Slovak industrial companies with medium energy intensity [elektronický dokument]. In Energies : elektronický dokument, ISSN 1996-1073. Bazilej, 2021, Roč. 14, č. 2, s. 1-15. CCC; WOS CC; SCO. Dostupný na internete <https://www.mdpi.com/1996-1073/14/2/267>
Ohlas:	[1] 2020. NAULA-SIGUA, Freddy Benjamín, ARÉVALO-QUISHPI, Diana Jackeline, CAMPOVERDE-PICÓN, Jorge Andrés et al. Financial distress in the Ecuadorian manufacturing sector [elektronický dokument]. In Revista Finanzas y Politica Economica, ISSN 22486046; 20117663. 2020, Roč. 12, č. 2, 461-490.
Ohlas:	[1] 2022. NINAMANGO ORIGUELA, N.A., SOVERO RIVERA, L.E. Efficiency of Peruvian regions in the management of hospital resources against COVID-19 in 2020: A two stage DEA model. In ACM international conference proceedings series. New York : Association for Computing Machinery, 2022. ISBN 978-145039569-4. SCOPUS.
Ohlas:	[1] 2022. KALINA, Jan. Model choice for regression models with a categorical response. In Journal of applied mathematics statistics and informatics, ISSN 1336-9180. 2022, roč. 18, č. 1, s. 59-71. WOS:000820112700005.
Ohlas:	[1] 2022. ĎURICA, M., MAZANEC, J. Modeling the financial distress of Slovak companies using various decision trees. In Business and management '2022. Vilnius : Vilnius Gediminas Technical University Press, 2022, s. 845-851. ISBN 978-609-476-288-8. WOS:000887405800100.
Ohlas:	[1] 2022. GAVUROVÁ, B., JENČOVÁ, S., BAČIK, R. et al. Artificial intelligence in predicting the bankruptcy of non-financial corporations. In Oeconomia Copernicana, ISSN 2083-1277. 2022, roč. 13, č. 4, s. 1215-1251. WOS:000907675800008; SCOPUS.
Ohlas:	[4] 2023. VRAVEC, J., KOREČKO, J. Economic aspects of bankruptcies of the business entities in Slovakia in the post-covid period. In Economics, management & business 2023 : contemporary issues, insights and new challenges : 8. international scientific conference. Prešov : Prešovská univerzita v Prešove. Vydavateľstvo Prešovskej univerzity, 2023, s. 684, 691. ISBN 978-80-555-3215-8.
Ohlas:	[4] 2023. MIŠKUFOVÁ, M., JUSKOVÁ, M., MATIJOVÁ, M. et al. Application of the bankruptcy models in the teaching of financial subjects. In Economics, management & business 2023 : contemporary issues, insights and new challenges : 8. international scientific conference. 1. vyd. Prešov : Prešovská univerzita v Prešove. Vydavateľstvo Prešovskej univerzity, 2023, s. 730, 732. ISBN 978-80-555-3215-8.
Ohlas:	[1] 2024. PRUSAK, B., KARAS, M. Bankruptcy prediction in Visegrad Group countries. In Polish journal of management studies, ISSN 2081-7452. 2024, roč. 30, č. 1, s. 283. WOS:001410206000016; SCOPUS.
Ohlas:	[1] 2024. MUSA, H., RECH, F., MUSOVA, Z. et al. Bankruptcy prediction using machine learning: the case of Slovakia. In Applied economic research and trends : 2023 International Conference on Applied Economics (ICOAE), Brno, Czech Republic, June 29-July 1, 2023, ISSN 2198-7246. 1. vyd. Cham (Švajčiarsko) : Springer, 2024, s. 590. ISBN 978-3-031-49104-7. SCOPUS.
Ohlas:	[1] 2024. NAYAN, A.B., ILIAS, M.R., ISHAK, S.S. et al. Evaluating the efficacy of financial distress prediction models in Malaysian public listed companies. In International journal of advanced and applied sciences, ISSN 2313-626X. 2024, roč. 11, č. 2, s. 7. WOS:001228354000002; SCOPUS.
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