Artículos

This article analyzes the scientific production on public administration in Latin America. The search was conducted in three databases: Scopus, Web of Science and Dimensions, covering only the period between 2012 and 2022. An exploratory-descriptive bibliometric approach was used to identify the main theoretical innovations, debates, and trends in the field. The information collecting process was supported by the Luis Echavarría Villegas Cultural Center Library at EAFIT University and was carried out in three stages: definition parameters and search criteria, selection of databases and systematization of information. The category most studied in documents is e-government, and there is evidence of an increase in the number of documents produced during the COVID-19 pandemic. The most productive authors are affiliated with institutions in Spain, and the journals with the highest production are associated with institutions in Spain, Brazil and Venezuela. Additionally, it was found that the predominant language of publication is English and gender issues have limited presence in the current literature.

Purpose: To identify how Business Administration has evolved in the context of global business through a bibliometric analysis. Methodology: The Scopus database was utilized to examine 1515 documents focused on the fields of Business, Administration, Economics, Econometrics, Finance, Social Sciences, and Multidisciplinary Studies, employing techniques such as citation network analysis, bibliographic coupling, and conceptual structure analysis of the selected documents. Findings: Thematic clusters proposed include: Economic dynamics and the global market; management and sustainable business development; digital transformation and efficiency in global business; comprehensive risk management and assessment; integrated business management and innovation; global marketing and strategic management, and human-centered approaches in international cooperation. Practical implications: Globalization has significantly influenced the production and dissemination of knowledge in Business Administration. Originality: Each thematic cluster presented serves as foundation for research lines in business schools as well as strategic alternatives for companies seeking to expand their business models to global markets.

Researchers, organizations, and policymakers have underlined the necessity of innovation for sustained economic growth. Few studies have applied bibliometric analysis to the term innovative culture”. This bibliometric study aims to evaluate the global trend in “innovative culture” by analyzing related publications in the Scopus database. The bibliometric map was analyzed utilizing VOS Viewer 1.6.19. The research employed Scopus as the primary database to extract relevant articles. Nevertheless, relevant literature from other databases has not been included. Scopus assessed 1,224 academic articles from 1972 to 2023. The United States and China lead “innovat* culture” research. The co-authorship analysis discovered that the United States had the most international collaboration. The analysis of author’s keywords indicated that “developing countries” and “product innovation” were important directions for studying innovative culture. Further studies are recommended to address this potential limitation. This paper offers implications and insights for the related field, guiding future research toward effectively investigating innovative culture.

Research is a mandatory and essential function of the university. The study analyses the behaviour of some bibliometric indicators of the scientific production Scopus 2019–2023 of the 19 Peruvian Non-Institutionalised Universities with Organising Commission. For 2023, 1746 documents indexed in Scopus were found. There is evidence of an increase in publications in social sciences, agricultural and biological sciences, engineering, informatics and computing, and environmental sciences. The variety of documents published, the level of publication in English, the H indexes of scientific journals and publication by quartiles, the number of qualified research professors in the Peruvian national science and technology system and the areas of publication are identified. Between 2022–2023, the level of publication in Scopus and the number of qualified teachers has increased significantly in this group of universities; however, the level of publication is well below that of institutionalized universities.

The emergence of COVID-19 has boosted internal communication as a central axis in the corporate environment, establishing itself as a key trend in 2024. This article examines the evolution and impact of internal communication in the business world since the appearance of the mentioned virus, with an analysis of selected publications in the months following the pandemic until the present in Scopus and the Web of Science. Through this study, the importance of internal communication in promoting well-being and effective leadership is highlighted, as well as its impact on transforming work practices and corporate culture, offering a detailed understanding of its benefits and added value for both organizations and employees.

The global transition to sustainable energy systems has placed the use of electric vehicles (EVs) among the areas that might contribute to reducing carbon emissions and optimizing energy usage. This paper presents a bibliometric analysis of the interconnected domains of EVs, artificial intelligence (AI), machine learning (ML), and deep learning (DL), revealing a significant annual growth rate of 56.4% in research activity. Key findings include the identification of influential journals, authors, countries, and collaborative networks that have driven advancements in this domain. This study highlights emerging trends, such as the integration of renewable energy sources, vehicle-to-grid (V2G) schemes, and the application of AI in EV battery optimization, charging infrastructure, and energy consumption prediction. The analysis also uncovers challenges in addressing information security concerns. By reviewing the top-cited papers, this research underlines the transformative potential of AI-driven solutions in enhancing EV performance and scalability. The results of this study can be useful for practitioners, academics, and policymakers.

Silicon (Si) is a promising anode material for the next generation of lithium-ion batteries (LiBs) due to its high theoretical capacity. However, Si undergoes a significant volumetric expansion during lithiation, leading to cracking, pulverization, and poor long-term electrochemical performance. To tackle these challenges, numerous strategies have been proposed, resulting in a rapidly expanding and diverse field of research. Despite this surge in Si-related studies, a comprehensive quantitative analysis of the literature on Si anode applications in LiBs has not been thoroughly examined yet. This study aims to bridge this gap through a bibliometric analysis with the objective of providing insights into key research themes, trends over time, emerging topics, and future research directions. Furthermore, it highlights prolific authors, organizations, countries, and foundational works in this area, offering a valuable reference for inclined researchers. For this purpose, a dataset of 4508 publications from 1970 to 2024 was retrieved from the Web of Science and analyzed to identify trends in leading journals, publication outputs, disciplines, and collaborations. The analysis shows that 2005–2014 was a “golden period” of substantial innovation, while more recent work reflects incremental yet interdisciplinary advancements. Notably, the collaboration network among prolific authors was found to be relatively weak, with the majority of the authors having only two or fewer connections. In contrast, strong collaboration was observed among leading institutions in the field. A thorough keyword analysis revealed that the research focus over the years can be categorized into three main themes: (1) electrochemical performance, (2) nanostructures and composite electrodes, and (3) electrochemical processes and mechanisms. Additionally, recently emerging topics include understanding the mechanisms of Si anodes and improving their performance through novel binders, pre-lithiation strategies, and advanced electrolytes. This study quantitatively analyzes for the first time the development of Si anodes for LiBs, offering an invaluable reference for researchers looking to engage in and contribute to this field.

Mapping of innovation (MOI) emerges as an essential tool for visualizing internal and external innovation prospects in the current business environment. This study employs a bibliometric approach to analyze the development, significance, and evolution of mapping of innovation at the business level through 241 publications indexed in Web of Science between 1985 and 2023. The research identifies 61 MOI techniques, such as costumer journey map, stakeholder map, and cognitive map. These techniques were categorized into six groups, including network approaches, geographical approaches, strategic tools, statistical and mathematical models, diagramming techniques, and descriptive methods. Having a comprehensive framework of MOI techniques will enable the delivery of effective and tailored solutions to companies that wish to map their innovation. At the cluster level, the mapping of the improvement of business models, co-creation processes, and product design are the most embraced factors both scientifically and by businesses. This research links MOI scientific production with business needs and interests. At the individual theme level, artificial intelligence, business models, entrepreneurship, and sustainability are highlighted for their practical relevance to current business needs and interests. Although research on MOI primarily focuses on developed economies such as the United States and Western Europe, it plays a significant role in driving entrepreneurship, social innovation, frugal solutions, and reverse innovation in developing economies. To the best of our knowledge, this is one of the first comprehensive attempts to integrate mapping of innovation techniques, linking them to both business and academic enhancement, including developing countries, and highlighting emerging themes.

This study presents a bibliometric analysis of artificial intelligence (AI) in digital image processing (DIP), analyzing 1063 publications from the Scopus database from 1998 to 2023. The field has seen significant growth, with an average annual growth rate of 16.24%, accelerating sharply between 2020 and 2023. The analysis emphasizes AI’s growing influence in healthcare and real-time image processing. China leads in publication volume, while the USA dominates in citation impact, underscoring the global and collaborative nature of AI-DIP research. Key institutions like the University of California and Tsinghua University, along with authors such as U. Rajendra Acharya, have made significant contributions to AI-driven healthcare diagnostics, highlighting the importance of interdisciplinary collaboration. High-impact journals, including IEEE Transactions on Medical Imaging, play a crucial role in advancing the field. However, this study relied on a targeted keyword search in Scopus, which may not capture all relevant research, particularly those using alternative terminologies or broader AI classifications. Additionally, challenges related to data privacy, bias, and transparency persist. Addressing these issues will be critical for the responsible development and application of AI-DIP technologies. This study offers valuable insights for future research and highlights key areas for continued exploration.

Over the past decade, Deep Learning (DL) techniques have demonstrated remarkable advancements across various domains, driving their widespread adoption. Particularly in medical image analysis, DL received greater attention for tasks like image segmentation, object detection, and classification. This paper provides an overview of DL-based object recognition in medical images, exploring recent methods and emphasizing different imaging techniques and anatomical applications. Utilizing a meticulous quantitative and qualitative analysis following PRISMA guidelines, we examined publications based on citation rates to explore into the utilization of DL-based object detectors across imaging modalities and anatomical domains. Our findings reveal a consistent rise in the utilization of DL-based object detection models, indicating unexploited potential in medical image analysis. Predominantly within Medicine and Computer Science domains, research in this area is most active in the US, China, and Japan. Notably, DL-based object detection methods have gotten significant interest across diverse medical imaging modalities and anatomical domains. These methods have been applied to a range of techniques including CR scans, pathology images, and endoscopic imaging, showcasing their adaptability. Moreover, diverse anatomical applications, particularly in digital pathology and microscopy, have been explored. The analysis underscores the presence of varied datasets, often with significant discrepancies in size, with a notable percentage being labeled as private or internal, and with prospective studies in this field remaining scarce. Our review of existing trends in DL-based object detection in medical images offers insights for future research directions. The continuous evolution of DL algorithms highlighted in the literature underscores the dynamic nature of this field, emphasizing the need for ongoing research and fitted optimization for specific applications.