Data Mining Approaches in Predicting Entrepreneurial Intentions Based on Internet Marketing Applications DOI Creative Commons

Milan Krivokuća,

Mihalj Bakator, Dragan Ćoćkalo

et al.

Applied Sciences, Journal Year: 2024, Volume and Issue: 14(24), P. 11778 - 11778

Published: Dec. 17, 2024

Amidst the globalization of markets, there has been a continuous intensification competitiveness between enterprises. The modern business environment caused shift in how is conducted. Opportunities and challenges arise, which put tremendous pressure on enterprises regardless size industry. Entrepreneurship plays an important role obtaining competitive edge market. Thus, entrepreneurial intentions can often shape future survival enterprise. In this paper, prediction through Internet marketing predictors addressed. For this, several statistical methods data mining were used. First, simpler approaches such as linear regression, logistic regression Afterward, classifier decision trees QUEST (quick, unbiased, efficient, tree), CHAID (chi-squared automatic interaction detection) sample for analysis was 137 from Serbia. Furthermore, supervised machine learning algorithm, support vector (SVM) Finally, feed-forward neural network (FNN) applied. results varied across applied approach, thus providing significant insights into dynamics outcomes enterprise setting.

Language: Английский

Data Mining Approaches in Predicting Entrepreneurial Intentions Based on Internet Marketing Applications DOI Creative Commons

Milan Krivokuća,

Mihalj Bakator, Dragan Ćoćkalo

et al.

Applied Sciences, Journal Year: 2024, Volume and Issue: 14(24), P. 11778 - 11778

Published: Dec. 17, 2024

Amidst the globalization of markets, there has been a continuous intensification competitiveness between enterprises. The modern business environment caused shift in how is conducted. Opportunities and challenges arise, which put tremendous pressure on enterprises regardless size industry. Entrepreneurship plays an important role obtaining competitive edge market. Thus, entrepreneurial intentions can often shape future survival enterprise. In this paper, prediction through Internet marketing predictors addressed. For this, several statistical methods data mining were used. First, simpler approaches such as linear regression, logistic regression Afterward, classifier decision trees QUEST (quick, unbiased, efficient, tree), CHAID (chi-squared automatic interaction detection) sample for analysis was 137 from Serbia. Furthermore, supervised machine learning algorithm, support vector (SVM) Finally, feed-forward neural network (FNN) applied. results varied across applied approach, thus providing significant insights into dynamics outcomes enterprise setting.

Language: Английский

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