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This study investigates whether there are relationships between the characteristics of the boards of trustees of universities in the Arab region, higher education quality assurance and the output of scientific research.

The descriptive analytical approach was used in this study. The study was conducted on the universities of the Arab region that are included in the classification of the British Institution for the Arab Region: QS Arab Region University.

The findings show that there is an effect of the characteristics of the trustees combined in the universities of the Arab region on ensuring the quality of higher education, other than the output of scientific research. The findings also indicate when measuring the characteristics individually that the trustee system is not effective in the Arab region and it is only formal for nominal purposes.

Most universities in the Arab region do not disclose the data of boards of trustees, their roles, committees, rules of procedure and the nature of their work. A large number of universities also do not operate under the trustee system because the regulations and instructions do not allow this in the country.

This study seeks to improve practitioners knowledge, including boards of trustees, in ensuring the quality of higher education and the output of scientific research.

The research projected the governance model through the characteristics of the boards of directors of for-profit companies on the boards of trustees of universities in the Arab region. The study examines the nature of the characteristics of the boards of trustees that are compatible with its responsibilities, the most important of which is the supervision of the strategy to ensure the quality of higher education research.

Microteaching is a teacher training method based on microclasses (groups of four or five students) and microlessons lasting no more than 5–20 min. Since it was first explored in the late 20th century in experiments at Stanford University, microteaching has evolved at the interdisciplinary level. The purpose of this paper is to examine the networks found via an analytical bibliometric study of the scientific output related with microteaching in teacher training, through a study and examination of the Web of Science database.

This research was conducted with the VOSviewer tool for content analysis through data mining and scientific network structure mapping by means of the normalisation technique. This technique is based on the association strength indicator, which is interpreted as a measurement of the similarity of the units of analysis.

Two hundred and nine articles were thus obtained from the Web of Science database. The networks generated and the connections among the various items, co-authorship and co-citation are presented in the results, which clearly indicates that there are significant authors and institutions in the field of microteaching. The largest cluster is made up of institutions such as Australian Catholic University. The most often-cited document is by Rich and Hannafin. Allen (1968), who defines microteaching as a technique based on microclasses and microlessons, is the author most often cited and has the largest number of connections.

This research’s limitations concern either aspects that lie beyond the study’s possibilities or goals that have proved unattainable. The second perspective, which focuses on skill transfer, contains a lower percentage of documents and therefore has a weaker central documentary structure. Lastly, the authors have also had to bear in mind the fact that the scientific output hinges upon a highly specific realm, the appearance and/or liberalisation of digital technologies and access to those technologies in the late 20th century.

This research shows that microteaching is a promising area of research that opens up vast possibilities in higher education teacher training for application in the realm of technologies. This paper could lead to several lines of future research, such as access to and the universal design of learning from the standpoint of different communication and pedagogical models based on microteaching.

Artificial Intelligence (AI) is an emerging technology and turned into a field of knowledge that has been consistently displacing technologies for a change in human life. It is applied in all spheres of life as reflected in the review of the literature section here. As applicable in the field of libraries too, this study scientifically mapped the papers on AAIL and analyze its growth, collaboration network, trending topics, or research hot spots to highlight the challenges and opportunities in adopting AI-based advancements in library systems and processes.

The study was developed with a bibliometric approach, considering a decade, 2012 to 2021 for data extraction from a premier database, Scopus. The steps followed are (1) identification, selection of keywords, and forming the search strategy with the approval of a panel of computer scientists and librarians and (2) design and development of a perfect algorithm to verify these selected keywords in title-abstract-keywords of Scopus (3) Performing data processing in some state-of-the-art bibliometric visualization tools, Biblioshiny R and VOSviewer (4) discussing the findings for practical implications of the study and limitations.

As evident from several papers, not much research has been conducted on AI applications in libraries in comparison to topics like AI applications in cancer, health, medicine, education, and agriculture. As per the Price law, the growth pattern is exponential. The total number of papers relevant to the subject is 1462 (single and multi-authored) contributed by 5400 authors with 0.271 documents per author and around 4 authors per document. Papers occurred mostly in open-access journals. The productive journal is the Journal of Chemical Information and Modelling (NP = 63) while the highly consistent and impactful is the Journal of Machine Learning Research (z-index=63.58 and CPP = 56.17). In the case of authors, J Chen (z-index=28.86 and CPP = 43.75) is the most consistent and impactful author. At the country level, the USA has recorded the highest number of papers positioned at the center of the co-authorship network but at the institutional level, China takes the 1st position. The trending topics of research are machine learning, large dataset, deep learning, high-level languages, etc. The present information system has a high potential to improve if integrated with AI technologies.

The number of scientific papers has increased over time. The evolution of themes like machine learning implicates AI as a broad field of knowledge that converges with other disciplines. The themes like large datasets imply that AI may be applied to analyze and interpret these data and support decision-making in public sector enterprises. Theme named high-level language emerged as a research hotspot which indicated that extensive research has been going on in this area to improve computer systems for facilitating the processing of data with high momentum. These implications are of high strategic worth for policymakers, library stakeholders, researchers and the government as a whole for decision-making.

The analysis of collaboration, prolific authors/journals using consistency factor and CPP, testing the relationship between consistency (z-index) and impact (h-index), using state-of-the-art network visualization and cluster analysis techniques make this study novel and differentiates it from the traditional bibliometric analysis. To the best of the author's knowledge, this work is the first attempt to comprehend the research streams and provide a holistic view of research on the application of AI in libraries. The insights obtained from this analysis are instrumental for both academics and practitioners.

This study aims to provide insight into Library and Information Science (LIS) research in India using scientometric approaches. Web of Science (WoS) and SCOPUS databases were used for data retrieval. The study examines productivity in terms of source types, gender distribution, document formats, authorship and other factors. In addition, this study sought to identify trends or patterns in the research preferences of LIS scientists through text analysis.

Data were downloaded from the WoS and Scopus databases over 22 years and analysed using VOSviewer, Orange, Biblioshiny and CRExplorer softwares.

The findings reveal that 5,692 out of the 9,384 documents in both databases underwent the final examination. In total, 466 different sources produced all of those papers. Author analysis revealed that 6,603 different authors authored 5,692 documents. There were 4,209 male and 1,063 female authors. Furthermore, India shares maximum collaborations with the USA and England. The spectrogram features nine significant peaks corresponding to Lotka’s, Bradford’s and similar laws. Text analysis revealed that Indian LIS researchers have consistently investigated open access and digital or open libraries.

The findings of this study will provide readers with a better understanding of India’s contribution to LIS. In addition, the study will help academics identify research gaps and undiscovered areas in the Indian context that require further investigation.

Not many studies highlight Indian research trends and international collaboration in LIS. This study highlights research trends, collaboration and gender productivity in LIS. The most cited references and trending topics were also identified using reference publication year spectroscopy and text analysis techniques.

The outcomes of public research institutions (PRIs), also known as research and development (R&D) institutions, in developing countries, including Indonesia, are still dubious. This study aims to measure the efficiency of R&D institutions using the case of the Indonesian Institute of Sciences, with and without an assessment of the role of scientific publication.

A panel data envelopment analysis (DEA) model is used to estimate the research efficiency of Indonesian R&D institutions during the period 2016–2019 based on the relationship between intellectual property (IP), research budgets and number of active researchers. The Tobit model is subsequently applied to analyze the factors that affect efficiency.

The DEA analysis shows an average efficiency value of 0.361, implying that 42% of the decision-making units (DMUs) have above-average efficiency scores. When scientific publication is added as an output variable, the efficiency increases to an average of 0.545, resulting in 53% of the DMUs with above-average efficiency.

The main implication is that scientific publications can increase the output of R&D institutions in Indonesia. This study recommends strengthening the research group establishment led by research professors along with setting acceptable high output targets. Researcher competence must be improved together with support for research collaboration among the different fields of science. Scientific publications should be considered part of IP measurement along with the type of mandate of each PRI.

This study offers a method of evaluation of research efficiency that can be applied to institutions outside Indonesia, thus furthering the dialogue on science and technology policy management.

This paper contributes to the literature by using a new and comprehensive method to measure research output – that of IP measurement, including new scientific publication. The implications provide action points for the governments to support R&D institutions and for research practitioners to augment research output.

This study aims to measure the global research landscape of the National Institute of Pharmaceutical Education and Research (NIPER) of India on a set of quantitative and qualitative metrics in terms of research output toward exploring research trends and give an overview of collaborative practices by researchers of NIPERs.

The present study has selected the Scopus database as a tool to retrieve potential publications of studied NIPERs during the last 12 years (2010–2021). NIPER-Mohali, NIPER-Hyderabad, NIPER-Ahmedabad, NIPER-Guwahati and NIPER-Kolkata have been selected for the study. The study has adopted a comprehensive search strategy to extract 3,926 publications data. VOS viewer 1.6.17, BibExcel and Microsoft Excel were used for data analysis and visualization.

The global scientific research output of NIPERs accrued 3,926 publications with an average of 327 publications per year. The retrieved publications fetched a total of 67,772 citations with an average citation impact of 17.26. There observed a steady growth of publications from 168 to 509 registered with an average growth rate of 18.44%. The mean relative growth rate and doubling time of research output are 0.26 and 2.94. The authorship patterns explore collaborative trends as most of the publications were published by multiple authors (99.39%). NIPERs have expanded their outreach to collaborate with the USA, Malaysia, Saudi Arabia, Australia and the UK to collaborate on research and regulatory reforms exhibits in the USA as a major contributor.

The present study is the first effort to evaluate the global research productivity of NIPERs and assess the current research trends on a set of quantitative and qualitative metrics to provide some insights into the complex dynamics of research productivity. The study’s outcome may help to identify the current research progress of NIPERs at the global level.

Genetics, a discipline of biology, is one of the most recent and rapidly advancing disciplines in science. This study aims to present a bibliometric analysis of the genetics research output of Iranian authors, map the intellectual structure of these studies and investigate the development path of this literature and the interrelationships among the main topics.

This study searched the Web of Science database for documentation of Iranian-published genetics research published up to 2020. Further, this study used HistCite software to profile and analyze the most cited articles and references and to draw their historiographies.

A database search revealed 21,329 documents that created the study population. The highest cited publications based on the Global Citation Score (GCS) and Local Citation Score (LCS) achieved scores of 602 and 47, respectively. The publication growth rate study demonstrated consistent expansion over time. The scientific maps based on LCS and GCS had five and four clusters, respectively. Furthermore, journal articles emerged as the predominant type of publication.

The significance of this study is in its contribution to understanding the genetics research position in Iran, informing policymakers and researchers, helping scientific collaboration and its impact on public attitudes and quality of life. The results of the present study, with benefits for various groups of communities, such as policymakers, academic groups and public society, can bridge the gap between theoretical research and practical implications.

The results of this study, by helping future advancement in health care, medical genetics and disease prevention, may have a direct and indirect positive influence on the quality of life. Furthermore, it may lead to more informed discussions on health care and biotechnology as well as influencing public attitudes and perceptions.

Ultimately, this study concludes that despite the proliferation of publications in terms of quantity and complexity, especially in areas such as disease diagnosis, prevention and treatment, there remains a need for more attention to other facets of genetics such as biology and biotechnology. Iranian publications are most related to population genetics, human genetics, molecular genetics, medical genetics, genomics, developmental genetics and evolutionary genetics out of 10 branches of genetics. This study reveals patterns in scientific outputs and authorship collaborations and plays an alternative and innovative role in revealing Iranian research trends in genetics.

The paper develops a model for enhancing R&D productivity for Indian public funded laboratories. The paper utilizes the productivity data of five Council of Scientific and Industrial Research (CSIR) laboratories for analysis and to form the constructs of the model.

The weighted average method was employed for analyzing the rankings of survey respondents pertaining to the significant measures enhancing R&D involvement of researchers and significant non-R&D jobs. The authors have proposed a model of productivity. Various individual, organizational and environmental constructs related to the researchers working in the CSIR laboratories have been outlined that can enhance R&D productivity of researchers in Indian R&D laboratories. Partial Least Squares-Structural Equation Modeling (PLS-SEM) was used to find the predictability of the productivity model.

The organizational factors have a crucial role in enhancing the R&D outputs of CSIR laboratories. The R&D productivity of researchers can be improved through implementing the constructs of the proposed model of productivity.

The R&D productivity model can be adapted by the R&D laboratories to enhance researchers’ R&D involvement, increased R&D outputs and achieving self-sustenance in long run.

The R&D laboratories can initiate exercises to explore the most relevant factors and measures to enhance R&D productivity of their researchers. The constructs of the model can function as a guideline to introduce the most preferable research policies in the laboratory for overall mutual growth of laboratory and the researchers.

Hardly any studies have been found that have focused on finding the measures of enhancing R&D involvement of researchers and the influence of significant time-intensive jobs on researchers’ productivity.

The current study aims to map the scientific output of grey literature (GL) through bibliometric approaches.

The source for data extraction is a comprehensive “indexing and abstracting” database, “Web of Science” (WOS). A lexical title search was applied to get the corpus of the study – a total of 4,599 articles were extracted for data analysis and visualisation. Further, the data were analysed by using the data analytical tools, R-studio and VOSViewer.

The findings showed that the “publications” have substantially grown up during the timeline. The most productive phase (2018–2021) resulted in 47% of articles. The prominent sources were PLOS One and NeuroImage. The highest number of papers were contributed by Haddaway and Kumar. The most relevant countries were the USA and UK.

The study is useful for researchers interested in the GL research domain. The study helps to understand the evolution of the GL to provide research support further in this area.

The present study provides a new orientation to the scholarly output of the GL. The study is rigorous and all-inclusive based on analytical operations like the research networks, collaboration and visualisation. To the best of the authors' knowledge, this manuscript is original, and no similar works have been found with the research objectives included here.

This study investigates the correlation between economic development and scientific knowledge production indicators in the BRICS countries from 2000 to 2020, highlighting the importance of human resources, natural resources, and innovation. Addressing a gap in the existing literature, this study aims to contribute significantly to understanding this relationship.

Employing a descriptive statistical approach, this study utilizes GDP and per capita income as economic indicators and scientific data from WoS and SCOPUS databases, focusing on scientific document production and citations per document.

The analysis reveals a strong correlation between economic development and scientific performance within the BRICS nations during the specified period. It emphasizes the interdependence of economic progress and scientific prowess, underscoring that they cannot be considered independently.

However, limitations exist, notably the reliance on specific databases that might not cover the entire scientific output and the inability to capture all factors influencing economic and scientific development.

Understanding this interdependence has crucial originality. Policymakers and stakeholders in BRICS countries can leverage these insights to prioritize investments in human capital development and scientific research. This approach can foster sustainable economic growth by reducing reliance on natural resources.