Using HJ-Biplot and External Logistic Biplot as Machine Learning Methods for Corporate Social Responsibility Practices for Sustainable Development

• DOI: 10.3390/math9202572
• Publication Date: 2021-10-15T02:42:18Z
• Authors: Joel A. Martínez-...; Cinthia Leonora M...; Purificación Vice...; Mónica Jiménez-He...; José Luis Vicente...
• Keywords: Biplot; Sample (material)

In recent years, social responsibility has been revolutionizing sustainable development. After the development of new mathematical techniques, improvement computers’ processing capacity and greater availability possible explanatory variables, analysis these topics is moving towards use different machine learning techniques. However, within field learning, Biplot techniques little known for analyses. For this reason, in paper we explore performance two most popular multivariate statistics: External Logistic HJ-Biplot, to analyse data structure studies. The results obtained from sample companies representing Fortune Global 500 list indicate that frequently reported indicators are related aspects labour practices decent work society. On contrary, disclosure less human rights product responsibility. Additionally, have identified countries sectors with highest CSR matters. We discovered both algorithms extremely competitive practical apply since they simple implement well relatively big datasets.