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Profiling nascent entrepreneurs in Croatia - neural network approach

Petra Mezulić Juric   ORCID icon orcid.org/0000-0003-3660-5215 ; Josip Juraj Strossmayer University of Osijek, Faculty of Economics in Osijek, Osijek, Croatia
Adela Has   ORCID icon orcid.org/0000-0002-3583-6970 ; Josip Juraj Strossmayer University of Osijek, Faculty of Economics in Osijek, Osijek, Croatia
Tihana Koprivnjak   ORCID icon orcid.org/0000-0001-9881-6419 ; Josip Juraj Strossmayer University of Osijek, Faculty of Economics in Osijek, Osijek, Croatia

Puni tekst: engleski, pdf (502 KB) str. 335-346 preuzimanja: 56* citiraj
APA 6th Edition
Mezulić Juric, P., Has, A. i Koprivnjak, T. (2019). Profiling nascent entrepreneurs in Croatia - neural network approach. Ekonomski vjesnik, 32 (2), 335-346. Preuzeto s https://hrcak.srce.hr/231431
MLA 8th Edition
Mezulić Juric, Petra, et al. "Profiling nascent entrepreneurs in Croatia - neural network approach." Ekonomski vjesnik, vol. 32, br. 2, 2019, str. 335-346. https://hrcak.srce.hr/231431. Citirano 24.09.2020.
Chicago 17th Edition
Mezulić Juric, Petra, Adela Has i Tihana Koprivnjak. "Profiling nascent entrepreneurs in Croatia - neural network approach." Ekonomski vjesnik 32, br. 2 (2019): 335-346. https://hrcak.srce.hr/231431
Harvard
Mezulić Juric, P., Has, A., i Koprivnjak, T. (2019). 'Profiling nascent entrepreneurs in Croatia - neural network approach', Ekonomski vjesnik, 32(2), str. 335-346. Preuzeto s: https://hrcak.srce.hr/231431 (Datum pristupa: 24.09.2020.)
Vancouver
Mezulić Juric P, Has A, Koprivnjak T. Profiling nascent entrepreneurs in Croatia - neural network approach. Ekonomski vjesnik [Internet]. 2019 [pristupljeno 24.09.2020.];32(2):335-346. Dostupno na: https://hrcak.srce.hr/231431
IEEE
P. Mezulić Juric, A. Has i T. Koprivnjak, "Profiling nascent entrepreneurs in Croatia - neural network approach", Ekonomski vjesnik, vol.32, br. 2, str. 335-346, 2019. [Online]. Dostupno na: https://hrcak.srce.hr/231431. [Citirano: 24.09.2020.]

Sažetak
A significant body of research has been conducted to identify the most important characteristics of nascent entrepreneurs. The aim of this paper is to create a model for recognizing nascent entrepreneurs in Croatia, using the Global Entrepreneurship Monitor (GEM) data for 2014. In this research, the artificial neural networks were used as a machine learning method which enabled the recognition of nascent entrepreneurs, as well as the selection of most important variables and profiling. The suggested model includes variables that describe examinees’ attitudes, skills and demographic characteristics, while the binary output variable identifies a nascent entrepreneur. In addition to testing the accuracy of the suggested model, the contribution of this paper lies in the profiling of nascent entrepreneurs in Croatia. This model could be a valuable tool for the government and entrepreneurship support institutions in creating policies and programmes based on recognizing the most important features of nascent entrepreneurs in order to improve entrepreneurial ecosystems.

Ključne riječi
nascent entrepreneurs; GEM; neural network; modelling

Hrčak ID: 231431

URI
https://hrcak.srce.hr/231431

Posjeta: 101 *