Resumo

MATUTE CASTRO, Kelly Gardenia  e  MUNOZ MUNOZ, Emanuel Guillermo. Multivariate analysis of socioeconomic factors in SMEs: regression models machine learning. uct [online]. 2024, vol.28, n.125, pp.142-152.  Epub 05-Fev-2025. ISSN 1316-4821.  https://doi.org/10.47460/uct.v28i125.864.

The application of multivariate analysis in various social and economic sectors allows the implementation and denoting of the virtues that this statistical method has and the relevance that is generated in the presentation of results for the decision-making necessary in the development of SMEs, allowing to indicate the various factors that lead to their growth and consolidation in the market. The factors that have a significant impact on these types of companies are analyzed, through the application of multivariate techniques such as Factor Analysis, Principal Components, Cluster, and Classification Models that in turn have allowed a reduction from 211 variables to 32 latent variables that focus the initial information, obtaining that the opportunities and capabilities, physical environment and health and job satisfaction that constitute SMEs are the factors that have the greatest influence have in their consolidation.

Palavras-chave : SMEs; factor analysis; principal components; cluster; classification models.

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