Scientometric Approach Research Articles

The landscape of Industry 4.0 and business model innovation: A scientometric analysis of research trends and emerging patterns

In Industry 4.0, the business model innovation plays a crucial role in enabling organizations to stay competitive and capitalize on the opportunities presented by digital transformation. Industry 4.0 is driven by digitalization and characterized by integrating various emerging technologies. These technologies can potentially change traditional business models and create new value propositions for customers. This paper aims to analyze and review the research papers through a bibliometric approach scientifically. The data were extracted from reputable Clarivate Web of Science (WoS) Core Collection sources from 2010 to 2023 (June). However, the publication started in 2018 for the research fields. The results show that scientific publications on research domains have increased significantly from 2020. VOSviewer, R Language, and Microsoft Excel were utilized for analysis. Bibliometric and Scientometric approaches conducted to determine and explore the publication patterns with significant keywords, topical trends, and content clustering better discussions of the publication period. The visualization of the data set related to research trends of Industry 4.0 in relation to Business Model Innovation resulted in several co-occurrence clusters namely: 1) Business Model Innovation; 2) Industry 4.0; 3) Digital transformation; and 4) Technology implementation and analysis. The study results would identify worldwide research trends related to the research domains and recommendations for future research areas.

Reexamining metaverse with quantative scientometric approach

Reexamining metaverse with quantative scientometric approach

A Scientometrics Analysis of Global Research on Social Media: Trends, Influential Works, And Future Directions Explored

This research aims to study regulations on the use of social media around the world. This study uses a qualitative scientometric approach. The data source for this study was taken from the Scopus Database with the keywords "Social Media Use" and "Policies." There were 173 documents analyzed, and the data was filtered using bibliometrics based on keyword relevance, author country, and year of publication, which was limited to 2018-2022. Citespace software was used to process the data stored in RIS format. The study found that, firstly, 173 publications were addressing social media use and policy from 2018 to 2022. Second, the most published publications in the United States are 73; third, ten authors have collaborated in research on social media use and policy. The study also found that the social media use and policies of governments and countries worldwide continue to evolve as technology advances and people's behavior changes. Governments should make appropriate regulations and make good use of social media to communicate with the public and achieve their goals.

Scientometrics Analysis of Global Researches on Anemia

Background: Anemia is a condition in which the number of red blood cells or the hemoglobin concentration within them is lower than normal. This study aims to show the intellectual structure of knowledge regarding anemia and gives a comprehensive and up-to-date image of research in this area. Materials and Methods: This is a descriptive-analytical study with a scientometric approach. The PubMed database was searched for research publications indexed under "anemia" including 8484 records between 2011 and 2020. Data were analyzed using Co-word analysis, clustering methods, and strategic diagrams with the help of SPSS and Ucinet 6 software. Results: The keyword “Anemia Sickle Cell” and two pairs of frequently used keywords, namely “Anemia, Iron *Iron” were the most frequent in the research area. The results shaped the concepts of anemia in 9 clusters. The clusters "Hydroxyurea and sickle cell anemia", "Fetus transfusion", "Management of Thalassemia Major", "Hemolytic Uremic Syndrome", "Management and Control of Anemia", "Chronic Kidney Failure and Anemia", "Hematopoietic Stem Cell Transplantation" are topics that may be emerging or disappearing. The “Thalassemia and blood transfusion" are immature clusters. Conclusion: This study uses co-word networks that indicate important links between keywords of the research areas. Most research approaches are in the therapeutic aspects. Despite the importance of the effect of anemia on all levels of society, including economics, education, and other types of anemia, as well as its impact on learning and mental disorders, these subjects have not been given sufficient consideration.

The coverage of basic and applied research in press releases on EurekAlert!

Research organisations routinely reach out to the media via press releases to announce research news and promote advances in science. This paper explores the presence of basic and applied research in press releases issued through EurekAlert!. Using a scientometric approach to classify research papers featured in press releases into basic and applied research, we found that more than half of the press releases in our dataset were related to basic research. This trend was particularly notable in life and earth sciences, physical sciences, and engineering fields. In contrast, press releases in the biomedical and health sciences, as well as in social sciences and humanities, were more frequently associated with applied research. Additionally, we present findings on the similarity and readability of press releases compared to their corresponding research papers, which confirm the role of institutional press officers in making research papers more accessible to the public and media. This adaptation appears to be more pronounced for basic research.

Comparative analysis of the leprosy detection rate regarding its clinical spectrum through PCR using the 16S rRNA gene: a scientometrics and meta-analysis.

Leprosy is a chronic and disabling infectious disease caused by Mycobacterium leprae. It has a wide clinical spectrum and is operationally classified into paucibacillary (PB) and multibacillary (MB) cases. There is evidence that the 16S rRNA gene can be used in Polymerase Chain Reaction (PCR) for complementary detection with high sensitivity and specificity. However, there is no literature convention on its diagnostic correspondence regarding the particular operational classification of the disease. This study aimed to correlate, through a meta-analysis, the detection rate of leprosy between the PCR method with the 16S rRNA gene in the clinical forms PB and MB in relation to confirmed cases. This is a systematic review and meta-analysis study conducted according to the PRISMA 2020 guidelines, using the search descriptors with "AND": "Leprosy"; "Polymerase Chain Reaction"; "16S rRNA" in the PUBMED, SciELO, LILACS, and Science Direct databases. The search was limited to original observational articles in Portuguese, English, or Spanish, with no defined time frame. The methodological quality assessment of the selected articles was performed using the JBI checklists. A scientometric approach to the article using used the VOS Viewer and Scimago Graphica software. The meta-analysis was conducted using Comprehensive Meta-Analyses software, under Pearson's Correlation effect test and fixed effect model and subgroup analysis concerning the type of sample analyzed. The study was significant from the perspective of the paucibacillary group (Clinical biopsy: -0.45 [95% CI= -0.63 - -0.22], p < 0.001/ Slit smear skin: -0.52 [95% CI= -0.65 - -0.36], p < 0.001 / Overall: -0.50 [95% CI= -0.61 - -0.37], p < 0.001). The PCR diagnostic method for the16S rRNAgene ofM. lepraehas low viability and diagnostic sensitivity in both clinical biopsy samples and leprosy skin smears. This implies little validation of it as a PCR target gene for diagnosing the disease, highlighting limitations in the actual technique. https://www.crd.york.ac.uk/prospero/, identifier CRD42024588790.

Mapping Open Access Publishing Trends in Central Universities of North East India: A Scientometric Approach

ABSTRACT The study analyses open access publications across the 10 central universities of North East India, focusing on publication trends, disciplinary distribution, citation impact, collaboration patterns, and open access licensing patterns. It compiles scholarly outputs from the OpenAlex API, integrating various data sources such as Microsoft Academic Graph, ORCID, Crossref, and Unpaywall. A total of 28,832 publications from 2004–2023 were collected and analyzed using statistical methods. The findings reveal a positive trend in research output across the represented universities, with an increasing emphasis on OA publications. However, the proportion of OA publications remains relatively low compared to closed access. Citation impact varies among universities, reflecting differences in research quality and visibility. Open repositories such as SSRN, Research Square, and Zenodo are crucial in promoting OA publishing. The study also reveals common usage of licenses such as CC-BY and CC-BY-NC-ND, with variations across universities. The impact on libraries is also discussed, emphasizing the role of libraries in promoting OA, supporting researchers, and contributing to scholarly communication advancement. This study provides valuable insights for policymakers, academic administrators, and researchers seeking to promote a culture of openness, collaboration, and innovation in scholarly communication within the region, country, and at the global level.

Bibliometric Analysis of Research Between Deep Brain Stimulation and Alzheimer’s Disease

Objective: To examine the thematic evolution and scientific productivity of the relationship between deep brain stimulation (DBS) and Alzheimer’s disease (AD). Materials and methods: A descriptive study using a scientometric approach was conducted using the Scopus database between 2019 and July 2024. Data were exported to the SciVal bibliometric analysis tool, and bibliometric indicators, such as number of publications per country/region, citations per publication, and h-index, were used. Results: A total of 150 publications were obtained, mostly of high quality (Q1) and coming from the USA and China. Lozano was the most productive author, and the University of Toronto in Canada had the highest number of publications. The journal with the highest impact was Frontiers in Neuroscience with 21.3 citations/paper, and most authors only published one article. Conclusions: The bibliometric study revealed decreasing research trends but mostly highlighted large international collaborations, especially in high-impact journals. The findings can serve as a basis for future research and policies evaluating the impact of DBS in the management of patients with AD.

Quantitative Process of Retrieving Documents on Specific Technology Using an Academic Database and the Sentence Transformer

ABSTRACTAs competition in technologies such as semiconductors and AI intensifies, the importance of technology analysis in establishing R&amp;D strategies is increasing. Although frequently used, technological document searches by domain experts often suffer from limitations in qualitative judgment and inconsistency. This study proposes a process for quantitatively assembling a collection of documents on specific technologies using an academic database and a language model. Using approximately 92 million records from the Web of Science, we identified related keywords from author keywords and used scientometric approaches to determine a core set of technology‐related literature. Then, a deep learning‐based Sentence Transformer model was employed to extract technology literature with high similarity to the documents, ultimately forming a set of documents for technology analysis. This study aims to overcome cognitive limitations and introduce quantitative criteria for technology analysis, which is particularly significant for data‐driven science and technology policy.

Exploring Innovation Capabilities in Organizations through a Scientometric Approach in the Context of Manufacturing Industry

Over the last four decades, innovation capability has been studied to examine the innovation phenomenon based on the specific characteristics of organizations and systems under the theory of resources and capabilities. However, "capability" has diverse applications, and its correlation with innovation remains unclear. This study aims to clarify the definition of "innovation capability" in the context of the manufacturing industry and to comprehend how researchers presently investigate this concept. In order to meet this, an exhaustive search was conducted in the Scopus and Web of Science (WoS) databases, covering the period from 2018 to 2023. The selection of documents for analysis was determined by applying the scientometric method. The authors of this research identified 462 documents, and the bibliometric analysis, conducted using VOS viewer and Bibliometrix tools, revealed four main thematic areas within the research domain: sustainability, business performance, technology transfer, and knowledge management. As a result, this study identified the seminal authors of the concept. It provided a precise definition of "innovation capability", highlighting the significant interest that this research topic arouses in current academic literature.

Developing a Conceptual Model for Promoting Risk Management for Public–Private Partnerships Projects

Over the past decade, there has been significant growth in the literature addressing risk issues associated with Public–Private Partnerships (PPPs). However, few studies have attempted to comprehensively map and visualize research in this domain. This study aims to fill this gap through a systematic literature review conducted in four stages, utilizing knowledge mapping analysis. More than 400 peer-reviewed articles published between 1990 and September 2023 were examined, making this study the first to analyze such a substantial sample of papers in this field. The research identifies three distinct phases of growth trends in PPP risk management studies. To minimize arbitrariness and subjectivity in analyzing research focuses, this study employed a scientometric approach using VOSviewer software (version 1.6.19), which provides insights into the current state and trends of research on PPP risk management, including high-frequency keywords, contributions of core authors, and distribution across countries, regions, institutions, and journals. In addition to the scientometric analysis, a qualitative review identified six primary research interests, various research perspectives, and diverse methodologies present within the literature. Based on these findings, this study culminates in the development of a conceptual model for risk management in PPPs, offering a structured framework for future research and practical application. This study contributes to the literature by providing the first large-scale, comprehensive mapping and analysis of PPP risk management research, presenting a novel conceptual model that connects theoretical insights with practical implications, and highlighting key areas for future exploration.

The Societal Impact of the Papers Published in Blended Learning in Medicine on Social Network Sites: An Altmetrics Study.

Nowadays, blended learning in medicine (BLM) has gained the attention of most experts as an invaluable approach to improving the quality of medical education. The level of attention to articles in this field on social networks is substantial. This study aimed to study the effectiveness of published articles in blended learning, indexed in Scopus and Web of Science databases between 2013 and 2022, from an altmetrics perspective. The research is descriptive-analytical, with a scientometrics approach (using the Altmetrics index). The population includes all the articles on blended learning in medicine, indexed in Scopus and Web of Science databases, two well-known citation databases worldwide. Data were extracted using the Altmetrics bookmarklet tool and analyzed with descriptive statistics methods in Excel software. Out of 1327 articles, 136 articles (10.25%) did not have a digital object identifier (DOI) or PMID number. Mendeley, X (previously Twitter), and Dimensions were the most widely used social networks in blended learning. The United States, the United Kingdom, and Australia had the highest number of tweets in blended learning in medicine. The number of articles with altmetrics indicators, categorized by publication year, demonstrates an improvement in the familiarity and use of social media by blended learning researchers in medicine. Blended learning researchers are advised to carefully select reputable journals - preferably with DOI - to increase the visibility and attention to their articles on social media.

The synergy of artificial intelligence and nanotechnology towards advancing innovation and sustainability - A mini-review

The convergence of Artificial Intelligence (AI) and nanotechnology is a transformative frontier, holding vast potential for scientific and technological advancements. This review explores the integration of AI and nanotechnology, aiming to uncover current trends, challenges, and future directions across various domains. A scientometric approach was employed, gathering and analyzing existing literature and research in the fields of AI and nanotechnology. Through a systematic examination of recent studies and developments, we identified key trends, challenges, and potential pathways for future research and applications. Findings from this review highlight the significant impact of AI-driven nanotechnology in materials discovery and design, healthcare, environmental monitoring, energy conversion, and quantum computing. These areas have witnessed remarkable advancements, such as the development of novel nanomaterials, precise drug delivery systems, advanced nanosensors, and efficient energy storage solutions. However, challenges persist, including insufficient interdisciplinary collaboration, data quality, ethical concerns, and regulatory frameworks. While challenges require careful consideration and mitigation, the potential for innovation and progress in diverse domains is undeniable. This review underscores the importance of responsible AI use and ongoing research to unlock the full potential of this convergence, ultimately shaping the future of science and technology.

Scientometric mapping of the trends, impact, and thematic evolution of scientific production on ehrlichiosis in veterinary medicine.

This study focuses on the scientific output of ehrlichiosis, a tick-borne disease that affects a variety of animal species, including dogs, cats, and livestock. Therefore, this study aimed to perform a scientometric mapping of the trends, impact, and thematic evolution of scientific production on ehrlichiosis in veterinary medicine. The study design was descriptive and observational, with a quantitative scientometric approach. This study was based on Scopus data collection and analysis from 2018 to 2023. A literature search was conducted on February 12, 2024, and a total of 200 documents were found, of which 177 were articles, 15 book chapters, and eight reviews. A specific search formula was used to obtain documents. The documents were analyzed using SciVal and Bibliometrix in R Studio, focusing on four key metrics: Scholarly Output, View Count, Field-Weighted Citation Impact, and Citation Count. This bibliometric study covered the period from 2018 to 2023 and analyzed 200 papers from 84 different sources. The average number of citations was 3595 and the mean age was 3.17 years. A total of 1874 keywords and 1085 authors were identified, with an average of 6.25 co-authors per paper. International co-authorship was present in 23% of the papers. The papers were distributed as articles (177), book chapters (15), and reviews (8). The combination of these metrics enabled a more complete and accurate assessment of research performance. A total of 1874 keywords and 1085 authors were identified. The thematic evolution from "canine ehrlichiosis" and "Ehrlichia canis" to "dog" and "canine" was observed. Bradford's and Lotka's laws were confirmed, with some sources and authors generating most publications.

SCIENTOMETRIC APPROACH IN DETERMINING THE ROLE OF SCIENCE IN SOCIOECONOMIC DEVELOPMENT OF SOCIETY

This study investigates the relationship between scientific advancement and socioeconomic progress using a scientometric methodology. The research examines publication activity and the Science Development Index (SDI) in different countries, utilizing statistical methods to evaluate the reciprocal impact of science and socioeconomic metrics, namely the Human Development Index (HDI). The results demonstrate a significant, nonlinear association between SDI and HDI, emphasizing the essential role of international cooperation and funding in fostering scientific development. The study emphasizes the importance of scientometric indicators in informing policy-making and fostering sustainable socioeconomic progress.

Textile Sustainable Development Related to Culture: A Scientometric Approach

The sustainable development of textiles has been a notable concern for the textile industry and society in recent years. From green textiles and circular textiles to cultural textiles, academia has conducted many explorations. The problem of the connection between the cultural needs of increasingly educated consumers and the development of textiles has become increasingly prominent, which has also triggered many new social problems. This study aims to explore how culture promotes sustainability in textiles and can meet consumer demands. This study uses scientometric methods to conduct a thematic analysis of cultural factors in the development of textiles. From 2013 to 2023, the Web of Science and Scopus databases included a total of 306 articles related to the cultural factors in textiles. The results of this study are as follows: 40 main research keyword clusters appeared in the knowledge base, 6 research themes were identified, and a conceptual framework of culture in the development of textiles was constructed. At the same time, this study provides suggestions on how to better establish communication between textiles and culture. The results of this study will help textile practitioners better understand the current status, hot spots, and research trends of cultural sustainability in the textile industry while establishing closer connections with consumers.

Formation of Approaches to Determining the Social Effectiveness of Scientific Activity of Libraries

The problem of evaluating the effectiveness of scientific activity as applied to the humanitarian and library sphere is analyzed. Research conducted in libraries contributes to the development of libraries themselves, as well as to the study and disclosure of cultural heritage. The question of the effectiveness of the conducted research is of fundamental importance. An analysis of the evolution of approaches to the evaluation of effectiveness is presented. In the last quarter of the 20th century, the fundamental principle of scientific policy was the position “science is the direct productive force of society”, which focused on the implementation of the findings of research activities and the formation of ideas about the mandatory material form of the results. This attitude is not applicable in the social sciences and humanities. In the Soviet period, the task of practical connection of science with production for a long time established the position that any scientific result should be practically tangible and economically effective, and every research should end with a document containing certain conclusions and a list of measures, or with an act on the implementation of research results.Currently, to assess not only the performance of individual scientists and organizations, but also in the formation of public science policy, the use of scientometric methods — quantitative measurements of information characteristics of published results of scientific work — is widely used. However, the scientometric approach continues to be debated.In the last decade the theoretical problem of social effectiveness of science, which, unlike economic, is not direct and specific and difficult to measure, has been increasingly discussed. Research conducted in the field of scientific support of library development has been proven to have a pronounced impact on library work (e. g., in the form of developed concepts, strategies, programs, etc.). Research of historical and cultural character influences the formation of public and individual consciousness, value system and contributes to the solution of the most important strategic state tasks.Determining the social effectiveness of research activities of libraries is becoming increasingly important.

Emergent Patterns, Collaborative Networks and Thematic Evolution on Black Stain and Dental Caries: A Scientometric Study.

To conduct a scientometric analysis on black stains, and dental caries, with a focus on identifying emergent patterns, collaborative networks, and thematic evolution. A retrospective, descriptive, observational study was conducted using a scientometric approach. The Scopus database was utilized for literature search, selecting articles published between 1976 and 2023. The literature search was carried out on February 8, 2024, using AND and OR Boolean operators which were adapted to the search strategy. Finally, SciVal used different scientometric indicators such as "Scholarly Output", "Views Count", "Field-Weighted Citation Impact" and the "Citation Count". A total of 13 documents from 10 different sources were analyzed, covering a period from 1976 to 2023. Despite an annual growth rate of 0%, each document has an average of 21.08 citations, indicating their relevance in the field. The documents have an average age of 12.9 years and contain 336 references. A total of 143 additional keywords and 26 author keywords were identified. The documents were written by 62 different authors, with an average of 5 coauthors per document and 30.77% international coauthorships. The results indicate a significant relevance of the documents in the field, a notable collaboration among authors, and a significant thematic evolution in the research topics. The mentioned institutions and sources produced documents with notable results, indicating a significant interest and impact in the field. This study provides a detailed view of the trends and patterns in the research of dental caries and black stains. The findings can assist dental health professionals in better understanding the prevalence and impact of these conditions. Furthermore, it can guide future research and treatment strategies in this field. How to cite this article: Mayta-Tovalino F, Espinoza-Carhuancho F, Reyes-Carmona J, et al. Emergent Patterns, Collaborative Networks and Thematic Evolution on Black Stain and Dental Caries: A Scientometric Study. J Contemp Dent Pract 2024;25(4):326-330.

Insights into Industrial Efficiency: An Empirical Study of Blockchain Technology

Blockchain technology is expected to have a radical impact on most industries by boosting security, transparency, and efficiency. This work considers the potential benefits of blockchain-focused applications in industrial process monitoring. The research design facilitates a detailed bibliometric analysis and delivers insights into the intellectual structure of blockchain technology’s application in industry via scientometric approaches. The work also approaches numerous sources in various industrial sectors to identify the transformative role of blockchain in industrial processes. Aspects such as blockchain technology’s impact on industrial processes’ transparency are discussed, while the paper does not ignore that success stories in applying blockchain to industrial sectors are often exaggerated due to a highly competitive environment that the cryptocurrency domain has become. Finally, the work presents major research avenues and decision-making areas that should be tackled to maximize the disruptive potential of blockchain and create a secure, transparent, and inclusive future.

Research evolution of metal organic frameworks: A scientometric approach with human-in-the-loop

Abstract Purpose This paper reports on a scientometric analysis bolstered by human-in-the-loop, domain experts, to examine the field of metal-organic frameworks (MOFs) research. Scientometric analyses reveal the intellectual landscape of a field. The study engaged MOF scientists in the design and review of our research workflow. MOF materials are an essential component in next-generation renewable energy storage and biomedical technologies. The research approach demonstrates how engaging experts, via human-in-the-loop processes, can help develop a comprehensive view of a field’s research trends, influential works, and specialized topics. Design/methodology/approach A scientometric analysis was conducted, integrating natural language processing (NLP), topic modeling, and network analysis methods. The analytical approach was enhanced through a human-in-the-loop iterative process involving MOF research scientists at selected intervals. MOF researcher feedback was incorporated into our method. The data sample included 65,209 MOF research articles. Python3 and software tool VOSviewer were used to perform the analysis. Findings The findings demonstrate the value of including domain experts in research workflows, refinement, and interpretation of results. At each stage of the analysis, the MOF researchers contributed to interpreting the results and method refinements targeting our focus on MOF research. This study identified influential works and their themes. Our findings also underscore four main MOF research directions and applications. Research limitations This study is limited by the sample (articles identified and referenced by the Cambridge Structural Database) that informed our analysis. Practical implications Our findings contribute to addressing the current gap in fully mapping out the comprehensive landscape of MOF research. Additionally, the results will help domain scientists target future research directions. Originality/value To the best of our knowledge, the number of publications collected for analysis exceeds those of previous studies. This enabled us to explore a more extensive body of MOF research compared to previous studies. Another contribution of our work is the iterative engagement of domain scientists, who brought in-depth, expert interpretation to the data analysis, helping hone the study.