an online questionnaire from a sample of 450 Romanian business students, were examined using principal component analysis … (PCA) and logistic regression. Facilitating conditions indicated a direct effect (positive) on the dependent variables, and …

principal component analysis (PCA) on 40 variables already used in the bankruptcy failure literature, resulting in the formation …

-of-the-art machine-learning methods. In this study, we employed a novel approach that combines an extended version of principal component … analysis (PCA) and a reinforcement learning algorithm to achieve efficient clustering and data reduction. The primary …

formulated Green Logistics Performance Index (GLPI) derived through Principal Component Analysis (PCA), the research assesses how …

governance capacity and offer governance support. The research uses principal component analysis (PCA) for data preprocessing and …

on nonparametric dimensionality reduction are rather sparse. Principal component analysis (PCA) and multiple …

an online questionnaire from a sample of 450 Romanian business students, were examined using principal component analysis … (PCA) and logistic regression. Facilitating conditions indicated a direct effect (positive) on the dependent variables, and …

documents the similarities and differences in energy sector variability among OTS members using a principal component analysis … (PCA) of data between 1991 and 2021. Our study shows that all OTS countries are similar in terms of primary energy …