PROFILING NASCENT ENTREPRENEURS IN CROATIA - NEURAL NETWORK APPROACH

Abstract

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.