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Machine learning (ML) analytical tools are increasingly being considered as an alternative quantitative methodology in management research. This paper proposes a new approach for uncovering the antecedents behind product and product–service innovation (PSI).

The ML approach is novel in the field of innovation antecedents at the country level. A sample of the Equatorian National Survey on Technology and Innovation, consisting of more than 6,000 firms, is used to rank the antecedents of innovation.

The analysis reveals that the antecedents of product and PSI are distinct, yet rooted in the principles of open innovation and competitive priorities.

The analysis is based on a sample of Equatorian firms with the objective of showing how ML techniques are suitable for testing the antecedents of innovation in any other context.

The novel ML approach, in contrast to traditional quantitative analysis of the topic, can consider the full set of antecedent interactions to each of the innovations analyzed.

The objective of this study is to review the main studies of social entrepreneurship (SE) in Latin America, to categorize them into four categories. To accomplish this, a bibliometric literature review is carried out based on data from the Web of Science database, to locate the Latin American collection of studies. In this way, the main studies are described and grouped, following a qualitative scheme that allows to substantiate the main findings of the Latin authors. Consequently, the progress made in the literature of the SE for Latin America is corroborated, by visualizing that the SE turns out to be a forceful fact to manage well-being, but that it is faced with an inconsistent development.