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Item type:Publication, The Association Between Human–AI Interaction and Leadership: A Structural Equation Modeling Analysis in Colombian Organizations(Multidisciplinary Digital Publishing Institute (MDPI), 2026-07-27)Artificial Intelligence (AI) has evolved from a tool for automation into a strategic component of organizational decision-making. However, the extent to which the dimensions of Human–AI Interaction are associated with leadership remains underexplored, particularly in emerging economies. This study examines how interaction quality, productivity enhancement, user experience, organizational impact, ethical governance, and innovation are associated with Leadership Effectiveness and Organizational Sustainability in Colombian organizations. We applied Structural Equation Modeling (SEM) to data collected from 170 participants using a purpose-built 30-item instrument designed to measure eight dimensions of the human–AI relationship through a five-point Likert scale. Six dimensions assessed Human–AI Interaction (Interaction Quality, Productivity and Efficiency, User Experience and Acceptance, Organizational Impact, Ethical Governance, and Innovation and Transformation), while two dimensions assessed leadership (Leadership Effectiveness and Organizational Sustainability). Estimation used maximum likelihood (ML/FIML) as the primary method, with robust ML (MLR) and an item-level WLSMV estimator as sensitivity checks. Correlation analysis (Pearson, with Spearman as a robustness check) revealed consistent positive and significant associations among all construct indicators. Confirmatory Factor Analysis (CFA) confirmed convergent validity, with innovation (λ=0.88) emerging as the highest-loading dimension. The structural model demonstrated a significant association between Human–AI Interaction and leadership (two-parcel model: β=0.95, R2=0.91). Under a more conservative six-item leadership specification, the association attenuates to β=0.87 (R2=0.75), which we treat as the substantive estimate. Common-method-variance diagnostics (Harman’s first factor =48.8%; a common latent factor accounting for ≈41% of variance) and an elevated RMSEA (= 0.13) signal the need for expanded measurement models and longitudinal designs to address causality. The findings suggest that ethical governance and innovation-oriented AI interaction are primary correlates of leadership effectiveness in digital organizations operating in emerging economies. - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Social impact of happiness on transformational leadership in students from Colombian universities(Frontiers Media, 2025-01-01)In the literature, it has been described that affective commitment and transformational leadership are directly related to occupational happiness. In this sense, the present study begins with the premise that subjective happiness may enhance the effectiveness of transformational leadership. For this purpose, the Leadership Practices Inventory (LPI) and the Subjective Happiness Scale (SHS) were applied to a non-probabilistic sample of 215 business administration students in Colombian universities. Bivariate correlation analysis, confirmatory factor analysis, and structural equation modeling were used to examine the relationship between the dimensions of happiness and the five leadership practices. The findings indicate that three happiness items correlate positively with transformational leadership practices, suggesting that happier individuals exhibit more effective leadership behaviors. The proposed theoretical model showed a good fit with the empirical data. In conclusion, promoting happiness in leaders not only improves their performance but also positively impacts organizational productivity.1 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Leadership and Human–AI Collaboration: A Measurement Scale(Multidisciplinary Digital Publishing Institute (MDPI), 2026-07-17)This paper aims to develop and provide the validity and reliability of a measurement scale that establishes the relationship between Leadership and Human–AI Collaboration. An instrumental study was conducted to inform the design and revision of a scale's psychometric properties. The techniques used for statistical analysis were carried out in three sequences, namely, the first consisted of collecting validity evidence based on test content; the second consisted of an exploratory and confirmatory factor analysis to gather validity evidence based on internal structure; and the third consisted of estimating the test reliability of internal consistency through the omega coefficient. The results show that the proposed measurement scale meets the psychometric properties required of a social-science instrument.