Emotional intelligence, leadership, and work teams: A hybrid literature review.

Emotional intelligence (EI) has been widely researched in different fields of knowledge. This paper reviews the literature on emotional intelligence, leadership, and teams in 104 peer-reviewed articles and reviews provided by the Web of Science and Scopus databases from 1998 to 2022. It is a hybrid or mixed review as it uses both quantitative and qualitative analysis techniques. The aims of this study are a performance analysis of the selected documents (years of publication, country, sectors, techniques used, most cited authors, authors with more publications, journals, journal quartiles, and scope of publication), as well as a co-word analysis using Atlas. ti v8. The results of the quantitative analysis indicate that the majority are empirical works. The qualitative analysis is a co-word analysis providing the following results: (i) classification of authors by major themes-categories (EI, leadership, team), (ii) classification of themes within each major theme: three subcategories in EI, 17 subcategories in leadership, and 19 subcategories in team and, lastly, (iii) classification according to the chronological development of main objectives from the most cited authors' articles we analyzed. Leadership (transformational, emergence, virtual, effective, health, effectiveness) is the major theme we studied. Our in-depth review of the articles has shown that emotionally intelligent leaders improve both behaviors and business results and have an impact on work team performance. It also highlighted a positive relationship between emotional competence and team members' attitudes about work. The new trends focus on the impacts of COVID19, the global crisis due to the Ukraine War, working in VUCA and BANI environments, comparative studies between generations, the application of artificial intelligence and the influence of mindfulness on organizations.

An alternative index to the global competitiveness index.

This paper reviews the methodology used by the World Economic Forum (WEF) to create the Global Competitiveness Index (WEF-GCI). We propose an alternative competitiveness index that only includes the objective data (hard data) from the WEF-GCI and is created by applying a multivariate statistical procedure (Exploratory Factor Analysis) that allows us to determine the weights from the implicit data structure. The rankings obtained from this index have a high degree of association with those provided by the WEF. The main benefit of this index over the WEF index is that it does not include valuations from opinion surveys given to business executives and/or entrepreneurs of the countries included in the index (soft data). Consequently, the rankings from this alternative index are not affected by political biases or individual interests as it is elaborated only including officially published objective data.