Data mining and machine learning in the context of sustainable evaluation: a literature review

Measuring and evaluating the sustainable performance of an organization has become an important and challenging topic because it involves the economic, social and environmental dimensions, helping the development of policies and becoming strategic factors in the decision-making process. However, difficulties are still encountered by managers in adequately assessing sustainability at the corporate level. In this perspective, data mining and machine learning are presented as techniques for extracting potentially useful information for generation of knowledge. Therefore, the purpose of this article is to identify, by means of a literature review, different approaches used to assist in the evaluation of sustainable performance. The method called Methodi Ordinatio was used for the review and, for the analysis, the software tools: VOSviewer e RStudio. By means of the methodological procedure adopted, 33 significant articles were identified for analysis from the Web of Science, Scopus and Science Direct databases, in which mainly the applied techniques were addressed. In this sense, this study seeks to stimulate research on the use of DM and ML to help in the sustainable context, being essential to assist in the Sustainable Development Goals.

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