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The continuous development of technology increases the number of new inventions and thus the number of patents. Each new technology is assigned to one of the existing patent classes, otherwise, a new technology must be added to the patent classes. These processes support the development of automated patent classification methods and articles on this subject. For decades, studies have been conducted in the field of automatic patent classification. In this paper, the studies and pat ents published in this field have been evaluated using a bibliometric approach. The most referenced important studies on this subject are examined in detail, the analysis is detailed by making the pioneering authors of the field, journals, countries, assignees, etc., the focal point. The most recent developments in the field have been examined and evaluations have been presented regarding topics that are likely to be studied in the future.

Since the International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems published its first issue in 1993, it has made important contributions to the research field of computer science. In this study, based on the dataset of the publications published in this journal between 1993 and 2016 retrieved from Web of Science, a general overview of this journal is performed using bibliometric methods and visualized networks. First, the productive and influential publications, authors, institutions, countries/territories, and supraregions are analysed based on the total number of citations, publications, and different citation thresholds. Second, network visualization analysis is applied to illustrate the links and connections between terms by using the VOSviewer software. Moreover, the most cited journals and common author keywords of three continents, including North America, Europe, and Asia, are also presented. This paper will hopefully help researchers understand the research patterns of this journal.

The International Journal of Information Technology and Decision Making (IJITDM) was launched in 2002 to study how the information technology and decision-making technique affect each other. To summarize the progress of the journal in the latest 11 years, a bibliometric overview of the IJITDM publications from 2012 to 2022 is provided to identify the conceptual evolution and development situation of the journal during this time slot. To do this, first, the publication and citation structures of the publications in this journal is presented. Then, the scientific network map analysis, including keywords analysis, co-authorship analysis and co-citation analysis, is performed in details. Furthermore, the development trends of information technologies and decision-making methods are discussed to dig out factors that influence the evolution of topics in IJITDM publications. Finally, conclusions of this study are offered. It is found that the IJITDM grew significantly from 2012 to 2022. The work presented in this paper will help scholars to obtain systematic knowledge and structured understanding of the research hotspots and development trends of the journal.

The Journal of Information and Knowledge Management (JIKM) published its first issue in 2002 and celebrated its 19th birthday in 2020. This study aims to assess JIKM performance over its lifetime between 2002 and 2020 by extracting data from the Scopus database and using a combined approach of bibliometric and content analysis. More specifically, we evaluate JIKM’s productivity and stature, discuss its performance compared to other journals, and identify key contributing (authors, institutions, and countries), citation pattern, and conceptual structure. The results highlight JIKM’s growing presence, which is reflected in the dual rise of publication activity and accumulated citation. JIKM becomes one of the preeminent journals in the area of knowledge management, with a broad range of scientific actors’ contributions (authors, institutions and countries) from all over the world. Furthermore, using a bibliographic coupling, keywords’ analysis, and co-authorship analysis, we analyse JIKM’s content and identify the most frequent themes discussed. The analysis reveals that JIKM has expanded its scope from knowledge management to a new array of emerging technologies’ topics such as artificial intelligence and data mining. Graphical visualization of similarities (VOSviewer and Rstudio) shows that the major themes published are clustered into four groups, mainly (i) sustainable knowledge, (ii) emerging technologies, (iii) information management, and (iv) organization culture and knowledge sharing.

This study uses bibliometric analysis to integrate, synthesise, and expand the knowledge regarding the relationship between automation and the labour market. In this paper, the authors examined the Web of Science (WoS) core collection database for articles published between 2002 and 2022. The co-citation, co-occurrence, and publication patterns were analysed using VOSviewer 1.6.19. The study comprised 287 papers, with the United States having the highest percentage of research publications, followed by Germany, China, and the United Kingdom. The institutional study shows that the Massachusetts Institute of Technology, Boston University, National Bureau of Economic Research, Harvard University, and the University of London are all leading institutions in this field of study and have more than 100 links. The co-occurrence of keywords revealed “automation”, “employment”, “growth”, and “jobs” as the most discussed terms. The paper concludes by identifying gaps in the literature and proposing possibilities for future studies.

Blockchain technology has attracted a lot of attention due to its revolutionary potential to upend the established economic structures, leading to a deluge of literature on the topic. Academics and business leaders alike are eager to see this technology used in the financial industry, although its full potential and limitations are currently unknown. To bridge this knowledge gap, 3312 records from the Dimensions database were obtained between 2014 and 2022 and used for bibliometrics and network analysis on the subject of blockchain technology in the financial sector. This analysis articulates the various potentials of blockchain literature as well as its adoption by various countries and authors, collaboration patterns, and applications of blockchain in finance using the visual mapping technique provided by VOSviewer. The top two innovators in the field, China and the USA, have used blockchain more extensively in financial research. Furthermore, the results show that the coverage of blockchain in finance has exploded in the last three years. Although India ranks third in documentation, behind China and the USA, it is lacking in citations and networking opportunities. The results, which identify important journals and authors in this field, will aid future researchers in better understanding the literature and conducting a PRISMA-based systematic review. This research is unique because it is the first bibliometric study to use the Dimensions AI database to look into how blockchain technology can be used in the financial sector.

Objective: To understand the research status and hot topics of internal medicine teaching in traditional Chinese medicine (TCM) in recent 20 years.

Methods: The relevant literature on the teaching of Chinese Internal Medicine in the past 20 years (2004–2023) was searched in China National Knowledge Infrastructure (CNKI), and the authors, institutions, and keywords were co-occurred and/or cluster analysis by using CiteSpace6.2.R7 and VOSviewer1.6.20 software.

Results: A total of 1117 journal articles were included, showing an overall upward trend. The journal with the most published articles is “Chinese Medicine Modern Distance Education of China”, the author is Xiao Yonghua of Dongzhimen Hospital of Beijing University of Chinese Medicine, and the research institution is Henan University of Chinese Medicine, with few cross-team and cross-institutional studies. Keywords “teaching method”, “teaching reform”, “problem-based learning”, “case teaching”, and “clinical teaching” are the research hotspots. “Flipped classroom” and “presentation assimilation discussion” in teaching methods, as well as “curriculum ideology and politics” and “talent cultivation” are possible research directions.

Conclusion: Teaching method and teaching reform are the research hotspots of internal medicine teaching in TCM, and the research frontier is the refinement of teaching method, that is, flipped classroom and presentation assimilation discussion, as well as curriculum ideology and politics. However, there is a lack of large sample and multi-center studies.

The Sustainable Development Goals (SDGs) serve as a common aim that brings many nations together, led by the United Nations with the purpose to achieve a set of 17 targets by 2030. One very important factor in achieving these aims is finance. The advancement in financial development all around the world will be able to speed up achieving SDGs where governments, policymakers, and people will be able to grow the economic development and infrastructure of the country, provide adequate job opportunities for many people, reduce poverty, as well as improve sustainability around the world. In opposition to that, some researchers see the advancement in financial development as an activity that will jeopardize achieving SDGs as financial development might lead to the production of carbon footprints at a faster rate. Using bibliometric analysis, this paper was able to discover that there is an increase in attention and interest in the field with the rise in publications in recent years, especially in 2022. Furthermore, this paper also identifies research hotspots within the field while also finding and analyzing the most impactful authors and publications on the topic. Ultimately, this paper hopes to provide a better definition for the relationship between financial development and SDGs with the use of bibliometric analysis, where data is collected from the Scopus database and analyzed using VOSviewer.

Numerous studies in the microfinance context have been observed to employ the data envelopment analysis (DEA) technique for the estimation of efficiency and/or productivity at the organizational level. This chapter aims to synthesize the existing DEA literature in the microfinance context to provide an overview of the methodological development over the past two decades and identify future research directions. To this end, literature data spanning the period 2006–2022 have been gathered from the Scopus database, and after filtering them based on inclusion and exclusion criteria, a total of 70 research articles relevant to this topic were considered for the study. With respect to methodological development, although most of the studies relied on the classical DEA, a recent trend revealed that studies are also employing various forms of network DEA (NDEA) techniques that integrate complex and multiple stages of the production process to help capture the diverse objectives of microfinance institutions. Furthermore, most studies utilize either regional or global data in their analysis of efficiency/productivity, with only a few exceptions. Lastly, bibliometric processing software (e.g., VOSViewer) is utilized for the identification of influential authors, institutions, networking, and countries. The study identifies important prospects for future research.