[HTML][HTML] The Good, the Better and the Challenging: Insights into Predicting High-Growth Firms using Machine Learning

S Pekin, A Şengül - Borsa Istanbul Review, 2024 - Elsevier
This study aims to classify high-growth firms using several machine learning algorithms,
including K-Nearest Neighbors, Logistic Regression with L1 (Lasso) and L2 (Ridge) …

In search of gazelles: machine learning prediction for Korean high-growth firms

HC Chae - Small Business Economics, 2024 - Springer
Abstract High-growth firms (HGFs), also known as gazelle firms, have attracted considerable
attention due to their outstanding contributions to job creation and additional spillover …

Uncovering key predictors of high-growth firms via explainable machine learning

Y Huang, S Xu, L Lü, A Zaccaria, MS Mariani - arXiv preprint arXiv …, 2024 - arxiv.org
Predicting high-growth firms has attracted increasing interest from the technological
forecasting and machine learning communities. Most existing studies primarily utilize …

Logistic regression modelling: procedures and pitfalls in developing and interpreting prediction models

N Šarlija, A Bilandžić, M Stanic - Croatian operational research review, 2017 - hrcak.srce.hr
This study sheds light on the most common issues related to applying logistic regression in
prediction models for company growth. The purpose of the paper is 1) to provide a detailed …

Predicting high-growth firms with machine learning methods

J Virtanen - 2019 - jyx.jyu.fi
Motivated by the recently grown political and commercial interest in high-growth firms (HGF)—
in this master's thesis—I study whether common machine learning (ML) techniques are …

Predicting Growth of SMEs–A Multilevel Approach

A Bilandžić - 2022 - repozitorij.efos.hr
Sažetak Small and medium-sized enterprises are more efficient, more adaptable, contribute
more to employment and are more resistant to the economic crisis compared to large …

[引用][C] MODELLING GROWTH OF SMES IN CROATIA USING PANEL ANALYSIS

ANA BILANDŽIĆ - Small