Predicting Entrepreneurial Intentions among the Youth in Serbia with a Classification Decision Tree Model with the QUEST Algorithm

Dejan Djordjevic, Dragan Ćoćkalo, Srdjan Bogetic and Mihalj Bakator
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Dejan Djordjevic: Technical Faculty “Mihajlo Pupin”, University of Novi Sad, 23101 Zrenjanin, Serbia
Srdjan Bogetic: Belgrade Business and Arts Academy of Applied Studies, 11120 Belgrad, Serbia
Mihalj Bakator: Technical Faculty “Mihajlo Pupin”, University of Novi Sad, 23101 Zrenjanin, Serbia

Mathematics, 2021, vol. 9, issue 13, 1-27

Abstract: Youth unemployment rates present an issue both in developing and developed countries. The importance of analyzing entrepreneurial activities comes from their significant role in economic development and economic growth. In this study, a 10-year research was conducted. The dataset included 5670 participants—students from Serbia. The main goal of the study is to attempt to predict entrepreneurial intentions among the Serbian youth by analyzing demographics characteristics, close social environment, attitudes, awareness of incentive means, and environment assessment as potential influencing factors. The data analysis included Chi-square, Welch’s t-test, z-test, linear regression, binary logistic regression, ARIMA (Autoregressive Integrated Moving Average) regression, and a QUEST (Quick, Unbiased, Efficient, Statistical Tree) classification tree algorithm. The results are interesting and indicate that entrepreneurial intentions can be partially predicted using the dataset in this current study. Further, most likely due to the robust dataset, the results are not complementary with similar studies in this domain; therefore, these findings expand the current literature and invite future research.

Keywords: decision tree; classification; prediction; QUEST algorithm; entrepreneurial intentions; youth (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

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