Higher education institutions (HEIs) offer educational methods inspired by their mission, vision, and philosophy. Graduate attributes are the resulting skills and competencies that students develop during their learning process and then apply in their professional work. This study analyzes whether a HEI’s humanistic philosophy informs graduate attributes and then influences Senior Management alumni’s leadership style and social responsibility. The results of this study suggest that HEIs with strong humanistic components favor the development of a person-centered leadership. And, when graduates occupy management positions, this leadership style correlates with the development of socially responsible companies as well as positive organizational performance. Moreover, the longer graduates occupy leadership positions, the greater the positive effect on the organization.

Digitalization is a catalyst for the development of an information society, transforming how individuals interact with the world. However, its implementation across countries and regions has been uneven, contributing to social polarization and declining social trust. Among the most pressing concerns related to digitalization and inequality are the conditions of marginalized communities and persistent gender disparities. This study examines whether digitalization is associated with quality of life in marginalized areas and whether these effects differ between men and women. Using a quantitative approach, this study applies an ordinal regression model to data from two surveys conducted in 2021 and 2024 in a marginalized community in Mexico City. The results indicate that digitalization is significantly associated with quality of life: households possessing technological assets were 4.17 times more likely to report improvements in quality of life. Moreover, notable gender differences emerged. Although men’s quality of life increased by a factor of 35.7 in relation to digitalization, no statistically significant association was observed for women. The findings suggest a growing and statistically significant association between digitalization and quality of life in marginalized communities, but its benefits are distributed unevenly across genders.

Research on how corporate social responsibility (CSR) practices linked to sustainable operations (SO) affect corporate financial performance (FP) is still limited. This study presents a novel methodological proposal to measure the individual impact of such practices on the profitability of companies listed on the Mexican Stock Exchange. The method employed consists of a Random Forest (RF) model complemented by Explainable Machine Learning (XML) techniques, namely Individual Conditional Expectation (ICE), Partial Dependence Plots (PDPs) and SHapley Additive exPlanations (SHAP), to calculate the individualized marginal effect in the return on assets (RoA), return on equity (RoE) and return on investment capital (ROIC) for each company, explained by the environmental, social, and governance scores provided by Bloomberg (Bloomberg Finance, L.P., New York, NY, USA), such as the market capitalization, debt-to-equity ratio, sales growth, and years since listing. The novelty of this model lies in the application of RF and XML, which offers a comprehensive and interpretable perspective on the CSR–FP relationship and the use of lagged explanatory variables to avoid endogeneity problems, overcoming the limitations of traditional analyses. The results indicate that environmental scores exhibit the most consistent contribution to FP, whereas social and governance effects are highly metric-dependent. The SHAP analysis reveals substantial heterogeneity in the drivers of firm FP, highlighting the relevance of XML methods.