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Digital financial inclusion as a catalyst for innovation, economic growth, and sustainability: A bibliometric analysis (2014-2024)
(Pro-Metrics, 2025)
Salazar-Uribe, Mayra Yvette
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Salgado-García, Jorge Arturo
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Hernández-Lara, Ana Beatriz
Objective. This study aimed to conduct a bibliometric analysis of keywords to identify strategic topics in digital financial inclusion (DFI) and their relationship with sustainability and economic growth between 2014 and 2024. Design/Methodology/Approach. A bibliometric analysis was conducted on a sample of 1,234 academic articles indexed in Scopus using the Bibliometrix tool in R. Keyword co-occurrence was examined using multiple correspondence analysis and K-means clustering to reveal thematic structures. Results/Discussion. A total of six thematic clusters were identified: (1) threshold effect, (2) digital transformation, (3) central bank digital currencies (CBDCs), (4) sustainable development, (5) financial and digital literacy, and (6) fintech. These clusters demonstrated the evolution of DFI from its initial role as a technological enabler, such as fintech and blockchain, to its current impact on economic development, growth, and sustainability. This analysis proposed a conceptual model of DFI. In this model, digital literacy and fintech functioned as enablers. Meanwhile, CBDCs and blockchain technology served as structural tools. Digital financial inclusion was defined as a mechanism for inclusive economic development. Conclusion. The findings contributed to an understanding of how financial digitization is linked to sustainability strategies and long-term economic growth. ©The authors ©Iberoamerican Journal of Science Measurement and Communication ©Pro-Metrics
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Mapping international research in Cinema, Audiovisual, and Animation: A metric study in Scopus
(Escuela de Comunicación - CampCM, 2025-08-06)
Dias Medeiros, Thaís
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Souza Vanz, Samile Andréa de
This article maps out the international scientific output in Cinema, Audiovisual, and Animation in the Scopus database. It uses bibliometrics as its methodological approach. Our research identified a diversity of publication languages, with English being the most commonly used language. The article was the dominant documentary typology, followed by the review, which may indicate a publication trend in the area. Among the publication vehicles, journals from the United Kingdom and Spain stand out. The countries with the highest number of publications in Cinema, Audiovisual, and Animation differ from the general ranking, and Brazil and Spain stand out when it comes to publications on the topic. It is concluded that production in the area, which began in 1980, has been growing slowly but steadily, especially since the 2000s, predominantly in the areas of Arts and Humanities, and Human Sciences. This research presents a broad and international view of the topic and suggests new studies in other databases as well as in specific countries.
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Contra la bibliometría “rápida y sucia”: aspectos para valorar la complejidad en los análisis bibliométricos
(Escuela de Comunicación - CampCM, 2025-06-30)
Rafael Repiso
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Álvaro Cabezas-Clavijo
El presente trabajo denuncia el auge indiscriminado de estudios bibliométricos de baja calidad que, aprovechando la accesibilidad de bases de datos como Web of Science o Scopus y el uso de herramientas automatizadas, proliferan en revistas científicas de diversas disciplinas. Esta tendencia, facilitada por la ausencia de conocimientos especializados de los revisores de revista y por el interés en incrementar rápidamente la productividad académica, ha derivado en la publicación de investigaciones metodológicamente pobres, con escasa elaboración conceptual y valor analítico limitado. Frente a este panorama, los autores reivindican la bibliometría como un campo de alta especialización que exige comprensión teórica, competencia metodológica e interpretación crítica de los datos. Con base en estos principios, se propone una aproximación metodológica para valorar la complejidad de los estudios bibliométricos a partir de seis dimensiones: tamaño de la población, origen y fuente de los datos, forma de recolección, grado de normalización, tipos de análisis empleados y herramientas utilizadas. Esta perspectiva metodológica pretende ofrecer a editores e investigadores un marco para identificar investigaciones sustantivas y distinguirlas de aquellas realizadas con poco esfuerzo, criterio y contexto teórico.
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Thematic mapping of artificial intelligence in management: A bibliometric approach using co-word analysis (2015–2024)
(Pro-Metrics, 2025)
Salgado-García, Jorge Arturo
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Objective: The objective of this study was twofold: first, to map the main themes in the literature on artificial intelligence in management, and second, to explore the relationships between these themes. Design/Methodology/Approach: A co-word analysis was performed on 15,835 articles indexed in Scopus (2015–2024), with the author’s keywords in the field of administration constituting the unit of analysis. The semantic network under consideration was constructed using the 50 most frequent terms, applying normalization by association and the Walktrap algorithm for cluster detection. Results/Discussion: The results of the analysis indicated that the extant literature was organized around three thematic groups. The first of these focused on conversational interfaces, the second on digital transformation, and the third adopted a computational approach. The thematic structure identified reflected a field in the process of consolidation, with a predominance of technical approaches and limited functional specialization. Conclusion: Contemporary research endeavors prioritized methodological development over strategic implementation in particular organizational contexts. These findings underscored the necessity for more comprehensive approaches that articulated technology, management, and governance. Moreover, they called for a future agenda that was oriented toward its adoption from sociotechnical perspectives. ©The authors ©Iberoamerican Journal of Science Measurement and Communication (Revista Iberoamericana de Medición y Comunicación de la Ciencia) ©Pro Metrics.
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SECI model of knowledge management: A thematic analysis with emphasis on agricultural organizations
(Pro-Metrics, 2024)
López-Meza, Evelia
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Leyva-Hernández, Sandra Nelly
Objective. This research aimed to identify the thematic trends in knowledge management through Nonaka and Tekeuchi's socialization, externalization, combination, and internalization (SECI) model. First, an analysis of the application of the model in general and then in the field of agriculture was conducted. Design/Methodology/Approach. A bibliometric analysis was performed, and 2201 indexed papers from the Scopus database between the years 1994 and 2024 were considered. The study used the authors' keywords to identify thematic trends through word co-occurrences. Results/Discussion. Thematic cores related to innovation and open innovation were identified. This model has experienced a notable boom in recent years. In the agricultural sector, knowledge creation and transfer represent a part of the model that has experienced increasing use. The importance of understanding and effectively using the model to drive innovation and sustainable development in agriculture was stressed. Therefore, it was proposed that knowledge be transformed into a source of knowledge. Conclusions. Despite the criticisms received, this paper highlights the lack of research on using the SECI model in agriculture and its relevance in advancing knowledge management research. Furthermore, the results point out that, for the agricultural sector, future research on knowledge management should focus on organizational learning mechanisms, social innovation, critical success factors, business processes, and job satisfaction. ©The authors ©Iberoamerican Journal of Science Measurement and Communication ©Pro-Metrics.
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Machine learning models in health prevention and promotion and labor productivity: A co-word analysis
(Pro-Metrics, 2024)
Domínguez Miranda, Sergio Arturo
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Objective: The objective of this article is to carry out a co-word study on the application of machine learning models in health prevention and promotion, and its effect on labor productivity. Methodology: The analysis of the relevant literature on the proposed topic, identified in the last 15 years in Scopus, is considered. Articles, books, book chapters, editorials, conference papers and reviews refereed publications were considered. A thematic mapping analysis was performed using factor analysis and strategy diagrams to derive primary research approaches and identify frequent themes as well as thematic evolution. Results: The results of this study show the selection of 87 relevant publications with an average annual growth rate of 23.25% in related production. The main machine learning algorithms used, the main research approaches and key authors, derived from the analysis of thematic maps, were identified. Conclusions: This study emphasizes the importance of using co-word analysis to understand trends in research on the impact of health prevention and promotion on labor productivity. The potential benefits of using machine learning models to address this issue are highlighted and anticipated to guide future research focused on improvements in labor productivity through prevention and promotion of health. Originality: The identification of the relationship between work productivity and health prevention and promotion through machine learning models is a relevant topic but little analyzed in recent literature. The analysis of co-words allows us to establish the reference point of the state of the art in this regard and future trends.
Scopus© Citations 1 20
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Transformación digital en ciencias administrativas y contabilidad: tendencias de investigación en Scopus
(Pro-Metrics, 2024)
Salgado-García, Jorge Arturo
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González-Zelaya, Vladimiro
Objective. Identify thematic trends in digital transformation in administrative sciences and accounting. Design/Methodology/Approach. A bibliometric analysis was performed considering 7,519 documents indexed in the Scopus database between 1970 and 2023. The analysis was performed using the authors' keywords to identify thematic trends. Results/Discussion. Thematic cores related to Covid-19, digital marketing, emerging technologies, innovation, industry 4.0, and Fintech were identified. Conclusions. Covid-19 promoted digital transformation and research in this field applied to administrative sciences and accounting. However, the advancement of digital technologies has influenced scientific production. Likewise, other trends, such as sustainability, converged in the generation of knowledge. © Iberoamerican Journal of Science Measurement and Communication.
Scopus© Citations 6 42

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