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    Psychometric Analysis of a Brief Measure of Emotional Intelligence (EQ-i-M20) in Teenagers from Lima
    (AIDEP, 2023-01-01)
    The research aimed to assess if the EQ-i-M20 presents evidence of validity regarding its internal structure, measurement invariance between men and women, and acceptable reliability. The sample consisted of 788 adolescents between 11 and 18 years old from an educational institution in Lima (Peru). The internal structure was evaluated by the Exploratory Structural Equation Modeling (ESEM), both the oblique model and the bifactor, the invariance of measurement with a multiple ESEM group, and its reliability using the α and ω. The results indicate that in men and women. the original factor structure of five oblique factors is replicated, that it has an acceptable degree of measurement invariance, and the reliability values are satisfactory. In conclusion, the EQ-i-M20 is an instrument with adequate psychometric properties.
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    Emotional intelligence and ethical behaviour in mining executives: the mediating effect of trust-building
    (Cogent OA, 2025-01-01)
    Executives in the mining industry are faced with complex ethical challenges involving the responsible management of resources, environmental impacts, and community relations. As such, it is crucial to understand and develop strategies to enhance ethical behaviour in the mining industry. However, empirical evidence on ethical behaviour among executives in this industry remains limited. This study attempts to address this research gap by analysing the mediating effect of trust-building on the relationship between emotional intelligence and ethical behaviour in mining executives. Partial least squares structural equation modelling (PLS-SEM) was used with a sample of 115 executives at Peru's largest mining projects, finding that trust-building has a partial mediating effect on the relationship between emotional intelligence and ethical behaviour. Besides adding to the existing academic literature, the results will be useful to mining executives, and possibly to executives in other extractive industries, to focus their efforts in enhancing trust-building to have a larger effect on ethical behaviour in their projects. Furthermore, these results may help when managing relations with different stakeholders, defining and implementing concrete strategies to reinforce ethical behaviour among executives in the mining industry, and probably in other extractive industries, by paying more attention to enhancing emotional intelligence and boosting trust-building in their top and middle-managers and in the workplace.
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    Influence of Leadership on Human–Artificial Intelligence Collaboration
    (Multidisciplinary Digital Publishing Institute (MDPI), 2025)
    This study proposes a conceptual model that explains the influence of leadership on the relationship between human intelligence (HI) and artificial intelligence (AI). A qualitative, non-systematic literature review was conducted in Scopus and Web of Science of the literature published in the last 5 years, using Boolean combinations of the terms “leadership,” “artificial intelligence,” and “human intelligence.” The thematic analysis allowed the identification of conceptual patterns and research gaps; the model elaborated from the review shows that leadership has an ethical and strategic mediation in the HI-AI relationship in a hybrid space of cooperation, in which automated decisions are put in real context through human judgment and reasoning; ethical governance mechanisms emerge for systems supported by artificial intelligence; and finally, a balancing mechanism to algorithmic efficiency is established through cognitive adaptability. The proposed framework offers organizations some guidelines for human supervision processes for AI-supported systems that integrate ethical evaluations into automated processes. It proposes elements—leadership tools that enhance the relationship between human intelligence and artificial intelligence. This article contributes to the management of organizations by proposing a model that recognizes leadership as a dynamic facilitator between HI and AI, integrating transdisciplinary knowledge of management, technological ethics, and cognitive science, and proposing an ethical interrelationship in the decision-making architectures between HI and AI. The proposed model establishes leadership mediation of human–AI interaction through four axes showing how leadership acts as the axis that brings together human and technological systems to work together. Hierarchical interaction creates a hybrid interaction that is highly flexible, efficient, and has ethical oversight. Finally, the proposed model is an open system that interacts with the environment and is understood as a flexible tool to support strategic decision-making in complex environments.
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