Producción Científica

This study utilized mixed (qualitative and quantitative) methods to discover the current research trends for AI in sustainable Fintech and to validate a research model through empirical analysis. The primary purpose of this research is to explore the factors influencing the acceptance of AI tools within the sustainable Fintech industry through a cross-national perspective, identifying key benefit and sacrifice dimensions, along with sustainability considerations, that affect users’ intentions to adopt AI tools. Drawing on a bibliometric keywords approach, we first conducted an overall review of academic literature using Web of Science and VOSviewer (version 1.6.17), covering areas related to AI applications in Fintech and sustainable Fintech practices. Additionally, for a cross-national study, this study built and validated a conceptual framework on the intention to use AI tools by selecting subjects from Republic of Korea and China. As core theoretical premises of the conceptual framework, the study drew on the Value-Based Adoption Model (VAM) and the Technology Acceptance Model (TAM). Furthermore, we extended the TAM to embrace sustainable dimensions (perceived responsibility and perceived transparency). Overall, the study concludes that AI not only improves Fintech efficiency but also significantly contributes to sustainable development, suggesting collaboration between experts in AI, finance, sustainability, and other relevant fields for more research on AI integration with sustainable Fintech management. This research contributes to existing literature by highlighting the synergistic benefits of combining AI and sustainable Fintech and offers practical insights for industry practitioners and policymakers.

In this paper, a bibliometric review is conducted on brain–computer interfaces (BCI) in non-invasive paradigms like motor imagery (MI) and steady-state visually evoked potentials (SSVEP) for applications in rehabilitation and robotics. An exploratory and descriptive approach is used in the analysis. Computational tools such as the biblioshiny application for R-Bibliometrix and VOSViewer are employed to generate data on years, sources, authors, affiliation, country, documents, co-author, co-citation, and co-occurrence. This article allows for the identification of different bibliometric indicators such as the research process, evolution, visibility, volume, influence, impact, and production in the field of brain–computer interfaces for MI and SSVEP paradigms in rehabilitation and robotics applications from 2000 to August 2024.

Background: Highly cited papers in critical care nursing can offer valuable insights for all stakeholders engaged in the research process by highlighting key research trends, guiding resource allocation and shaping future research priorities. Aim: To gain insights from the top-cited papers in the top critical care nursing journals. Study Design: This was a bibliometric analysis of the top-cited papers in the top critical care nursing journals as reported by the Journal Citation Report 2023—released in June 2024. Data were tabulated and visualized using Microsoft Excel and the VOSviewer software. Results: Forty papers from the top four critical care nursing journals (Intensive and Critical Care Nursing [ICCN], Nursing in Critical Care [NICC], Australian Critical Care [ACC] and American Journal of Critical Care [AJCC]) were analysed. Half of the analysed papers were related to the COVID-19 pandemic, and mental health was the most addressed theme (n = 11 papers). Papers from the ICCN featured contributions from 17 countries, the highest among the journals analysed, followed by NICC, with contributions from 11 countries. Articles received more citations than reviews (median [interquartile range]: 18 [9–23] vs. 8 [8–11.5]), and open-access papers were cited about twice those published under a subscription model (19 [16–31] vs. 9 [8–15]). In ICCN, 9 of the 10 analysed papers were published open access compared with 3 in NICC and ACC and 2 in AJCC. Conclusions: The identified themes in this paper underscore the dynamic nature of the field of critical care nursing and the ongoing efforts to address key challenges in critical care nursing practice and health care delivery. Publishing open-access articles on trending topics and collaborating internationally seem to be effective approaches for gaining more citations. Relevance to Research: Understanding these prevalent themes has significant implications for guiding research priorities, informing clinical practice, shaping policy and improving patient outcomes. Academic journals need to encourage increasing the representation of researchers from the Global South in both journals’ editorial boards and submissions to the journals.

Circular Manufacturing (CM) is a manufacturing process that employs strategies such as remanufacturing and closed-loop supply chains to improve sustainability (Delpla, Kenné, & Hof, 2022). This process employs circular economic principles. The adoption of CM has been impeded by a lack of financial support, inadequate consumer awareness, and insufficient government support. This review aims to facilitate a broader understanding of the adoption of government policies in implementing circular manufacturing strategies, which will help in advancing our knowledge about how nations compete to create and capture value. To provide a comprehensive and global perspective, the review included 524 studies from the Scopus Database, covering studies between 1990 and May 2024. The review contributes to (a) outlining three thematic clusters of shared scholarly interest, (b) the conceptual framework, and (c) highlighting several areas for future research. Ineffective management and sharing of information are significant challenges that impede organisational knowledge and decision-making administration. The transition to CM is facilitated by identifying essential data and technologies through an integrative review (bibliometric analysis and conceptual framework).