Knowledge management in Latin America: Analysis of research trends from Scopus
Year: 2025
Type: article
Abstract: Objective. This study analyzed research on knowledge management produced by Latin American authors. Design/Methodology/Approach. To visualize research trends, a bibliometric indicator set was applied to data extracted from Scopus. The indicators calculated were productivity and collaboration by country, affiliation, and author. Results/Discussion. We observed that a few authors concentrate a significant proportion of the total productivity, reflecting their central influence on developing and disseminating knowledge within the field. Analysis of the co-authorship map shows a complex collaborative network. Scientific productivity by country reveals significant differences between the number of publications and international connections. Brazil leads with 607 papers, a figure that far exceeds the number of its international connections. On the other hand, Peru, with 74 publications and 25 connections, presents a minor difference (49) between its productivity and its international links. This indicates a higher level of integration in Peru's international networks, reflecting its participation in specific collaborations of high relevance. The Universidad Distrital Francisco José de Caldas, located in cluster 3, leads productivity with 22 published documents. The density analysis of the map of institutions reveals a value of 0.0123, which indicates that the network is highly dispersed. This density level is evidence that, although there are connected nodes, most institutions are not directly linked to each other. Conclusions. The analysis of scientific productivity on knowledge management in Latin America shows an apparent concentration of publications in a few authors and institutions. Co-authorship patterns reveal the existence of well-defined clusters, where some act as central nuclei with high internal cohesion, while others serve as bridges connecting different scientific communities.
DOI: 10.47909/ijsmc.1634
Language: English
Subfield: Statistics, Probability and Uncertainty
Field: Decision Sciences
Domain: Social Sciences
Open Access status: diamond
OpenAlex ID: W4407854953