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In parallel with the rising importance of innovation and digital technologies, research on platform ecosystems is rapidly accumulating. This study aims to summarize the current research published in leading technical and innovation management (TIM) journals and provide recommendation for future research.

In this paper, the authors combine multiple quantitative literature review methods (social network analysis, citation analysis and co-citation analysis) with a systematic literature review of articles published in the 13 most influential TIM journals over a 15-year period.

The citation network of 168 selected papers is sparse, with low network density indicating the emerging nature of the field. Using network centrality values, the authors identified the 33 most influential articles. The review of methodologies in these articles found that conceptual and case study research dominate, suggesting the need for additional confirmatory and quantitative analysis. Co-citation analysis of the references identified six research clusters: foundation, network-centric innovation, complementor management, platform competition, ecosystemsand product platforms.

This analysis is among the first to examine the knowledge structure of platform ecosystem research in the TIM domain by using multiple evidence-based analysis methods. The authors also apply the theory, context, characteristics and methodology framework to suggest areas for future research.

The metaverse offers great potential for creating a new educational environment with unique experiences. Currently, it has been integrated into many stages of education, including classroom study aids, clinical skill interaction and image training simulators, thanks to a new generation of Internet applications. This paper aims to provide a comprehensive systematic review using bibliometric analysis on the metaverse in health education and analyze the trends and patterns of research output within the field.

The paper conducts bibliometric analysis and follows the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines to ensure a rigorous and transparent review process. Specifically, this article identifies research questions, develops a data-collection strategy and establishes a screening approach that includes determining relevant keywords and applying inclusion and exclusion criteria.

A bibliometric analysis is conducted comprising 231 studies from 145 scientific journals to assess the trends, patterns and collaboration networks in research on the use of metaverse technology in health education. This paper provides insights into the research themes, publication trends and countries leading in this field, which can guide future research in this field.

The use of metaverse technology in health education has gained momentum in recent years. Despite this interest, comprehensive studies to review and analyze the existing literature on this topic systematically are lacking. In response, this paper provides a systematic review that explores the potential role of the metaverse in health education. By considering the current research, key trends, research hotspots and opportunities for future investigations are identified. The findings not only shed light on the current state of research but also offer guidance for advancing this exciting field.

Predicting highly cited papers can enable an evaluation of the potential of papers and the early detection and determination of academic achievement value. However, most highly cited paper prediction studies consider early citation information, so predicting highly cited papers by publication is challenging. Therefore, the authors propose a method for predicting early highly cited papers based on their own features.

This research analyzed academic papers published in the Journal of the Association for Computing Machinery (ACM) from 2000 to 2013. Five types of features were extracted: paper features, journal features, author features, reference features and semantic features. Subsequently, the authors applied a deep neural network (DNN), support vector machine (SVM), decision tree (DT) and logistic regression (LGR), and they predicted highly cited papers 1–3 years after publication.

Experimental results showed that early highly cited academic papers are predictable when they are first published. The authors’ prediction models showed considerable performance. This study further confirmed that the features of references and authors play an important role in predicting early highly cited papers. In addition, the proportion of high-quality journal references has a more significant impact on prediction.

Based on the available information at the time of publication, this study proposed an effective early highly cited paper prediction model. This study facilitates the early discovery and realization of the value of scientific and technological achievements.

This research conducts bibliometric analyses and network mapping on smart libraries worldwide. It examines publication profiles, identifies the most cited publications and preferred sources and considers the cooperation of the authors, organizations and countries worldwide. The research also highlights keyword trends and clusters and finds new developments and emerging trends from the co-cited references network.

A total of 264 records with 1,200 citations were extracted from the Web of Science database from 2003 to 2021. The trends in the smart library were analyzed and visualized using BibExcel, VOSviewer, Biblioshiny and CiteSpace.

The People’s Republic of China had the most publications (119), the most citations (374), the highest H-index (12) and the highest total link strength (TLS = 25). Wuhan University had the highest H-index (6). Chiu, Dickson K. W. (H-index = 4, TLS = 22) and Lo, Patrick (H-index = 4, TLS = 21) from the University of Hong Kong had the highest H-indices and were the most cooperative authors. Library Hi Tech was the most preferred journal. “Mobile library” was the most frequently used keyword. “Mobile context” was the largest cluster on the research front.

This study helps librarians, scientists and funders understand smart library trends.

There are several studies and solid background research on smart libraries. However, to the best of the author’s knowledge, this study is the first to conduct bibliometric analyses and network mapping on smart libraries around the globe.

This study aims to investigate the impact of ResearchGate (RG) scores on the scientific indicators of Qur’anic productions in Scopus.

This research is fundamental in method, created in a descriptive method and a scientometric approach. The statistical society includes 4,105 records produced by writers in the field of Qur’an during the time period of 2011–2020 indexed in the Scopus database. In this study, Pearson correlation coefficient test is used with aid of Excel and SPSS software.

Countries such as Malaysia, the USA and Indonesia, respectively, hold the highest number of scientific productions in the field of Qur’an. Iran holds the fourth place with a 544 record difference in comparison to Malaysia (866 documents). There is a positive and meaningful relation between measures of RG, readers, followers, citations and the H-index score regarding writers with received citations and the H-index score of scientific productions in the field of Qur’an in Scopus. However, no relation can be observed between the mentioned measures and indicators of the number of documents with cowriting.

Because of some authors not using the same name in their articles, it was not possible to access their profile in RG. For this reason, the information of these authors was not accessible in RG.

The activity of researchers in social networks will receive feedback from readers. This will result in more citations. Contrary to expectations, the research results showed that Iran does not have a good position in publishing Qur’anic works. Therefore, researchers should publish their findings in international journals.

Iranian writers should try to publish their scientific productions in international publications and also widely spread their content and research results across social networks to increase feedback and gain the attention of readers. This process leads to receiving reader feedback and publication of the Islamic teachings.

The relationship between the number of citations of Qur’anic works in Scopus and altmetric indicators in RG has not been investigated in previous researches. Therefore, this research is innovative in this field.

The purpose of this study is to present a comprehensive knowledge mapping and an in-depth analysis of pro-environmental travel behaviour research to better understand the global trend in this field that have emerged between 2000 and 2021.

In this study, a visual analysis of 187 scholarly articles between the year 2000 and 2021 related to pro-environmental travel behaviour (PETB) is presented. Using the knowledge mapping based on CiteSpace it presents the current research status, which contains the analysis of collaboration network, co-citation network, and emerging trends.

The results revealed that the PETB is an emerging topic, which has an increased number of publications in recent years. Though the collaboration network between scholars is dispersed, some countries exert stronger collaboration network. Researchers from England, USA and China have worked more on this topic comparatively. “Pro-environmental norm” is found to be the major concern in regard to PETB, and the theory of planned behaviour (TPB) is the most common theory used by the scholars around the world. Ten articles with the highest citations are found to be the most valuable articles. COVID-19, value orientation, negative spillover, carbon footprints, biospheric and adolescent are some of the latest keywords based on the past two years' literature review, all of which have huge research potential in the future.

This study is among the pioneers to shed some light on the current research progress of PETB by using a bibliometric analysis to provide research directions for scholars. Moreover, this study utilized latest data from 2000 to 2021. The studies which are published before and during the pandemic are also incorporated.

In recent years, instant messaging platforms like WhatsApp have gained substantial popularity in both academic and practical domains. However, despite this growth, there is a lack of a comprehensive overview of the literature in this field. The primary purpose of this study is to bridge this gap by analyzing a substantial dataset of 12,947 articles retrieved from the Dimensions.ai, database spanning from 2011 to March 2023.

To achieve the authors' objective, the authors employ bibliometric analysis techniques. The authors delve into various bibliometric networks, including citation networks, co-citation networks, collaboration networks, keywords and bibliographic couplings. These methods allow for the uncovering of the social and conceptual structures within the academic discourse surrounding WhatsApp.

The authors' analysis reveals several significant findings. Firstly, the authors observe a remarkable and continuous growth in the number of academic studies dedicated to WhatsApp over time. Notably, two prevalent themes emerge: the impact of coronavirus disease 2019 (COVID-19) and the role of WhatsApp in the realm of social media. Furthermore, the authors' study highlights diverse applications of WhatsApp, including its utilization in education and learning, as a communication tool, in medical education, cyberpsychology, security, psychology and behavioral learning.

This paper contributes to the field by offering a comprehensive overview of the scholarly research landscape related to WhatsApp. The findings not only illuminate the burgeoning interest in WhatsApp among researchers but also provide insights into the diverse domains where WhatsApp is making an impact. The analysis of bibliometric networks offers a unique perspective on the social and conceptual structures within this field, shedding light on emerging trends and influential research. This study thus serves as a valuable resource for scholars, practitioners and policymakers seeking to navigate the evolving landscape of WhatsApp research. The study will also be useful for researchers interested in conducting bibliometric analysis using Dimensions.ai, a free database.

This study aims to provide insights into different aspects of the extant literature on the effects of dividend announcements. Along with other outputs of a bibliometric study, this study provides deeper insights into the concentration of the extant literature and suggest future research agendas.

This study uses the bibliometric, network and content analysis of the dividend announcement literature indexed in Scopus. This study presents the temporal analysis, the network of authors, countries, author citations and the co-occurrence of author keywords. This study provides the concentration of the extant literature in three clusters and unearth some key future research areas. This study uses the latent Dirichlet allocation method for robustness.

A total of 54 documents examining the US sample have received 1,804 citations. Interestingly, the first article on emerging markets was published in 2002, when at least 34 articles on developed markets had already been published from 1982 to 2001. The content analysis of top-cited literature unveils diverse insights into dividend announcements’ effects on financial markets. Contagion effects negatively impact non-announcing banks, particularly larger ones. Dividend maintenance affects stock market momentum, influencing loser returns. While current dividend/earnings news may not predict future company performance, information content dominates bond market reactions to post-dividend announcements. Concomitantly, while financially constrained firms exhibit short-term gains but worse long-term performance following dividend increases, larger stock dividends send stronger market signals in China.

This study significantly contributes to the bibliometric and content analysis literature by analyzing the sample documents based on the sample examined. To the best of the authors’ knowledge, no previous bibliometric study in this domain has been conducted to explore the markets (developed and emerging) to which the samples examined belong and the quality of publications from developed and emerging markets.

This study aims to examine the literature from the Web of Science database published on board committees between 2002 and 2023 and outline the quantitative summary, journey of board committees’ research and suggest future research directions.

This study examines bibliometric-content analysis combined with a systematic literature review of articles on board committees to document the summary of the field. The authors used co-citation, co-occurrence and cluster analysis under bibliometric-content analysis to present the field summary.

Board committee composition, such as their gender, independence and expertise, as well as factors affecting corporate governance, such as reporting quality, earnings management and board monitoring, all have a significant impact on board committee literature. The field is getting growing attention from authors, journals and countries. Nevertheless, there is a need for further exploration in areas like expertise, member age and tenure, the economic crisis and the nomination and remuneration committee, which have not yet received sufficient attention.

This paper has both theoretical and practical contributions. From a theoretical perspective, this study substantiates the prevalence of agency theory within board committee literature, reinforcing the foundational role of agency theory in shaping discussions about board committees. On practical ground, the comprehensive overview of board committee literature offers scholars a road map for navigating this field and directing their future research journey. The identification of research gaps in certain areas serves as a catalyst for scholars to explore untapped dimensions, enabling them to strengthen the essence of the committees’ performance.

This study presents a systematic review of the literature on monetary policy and corporate investment together with bibliometric analysis.

This study selected 455 articles from databases, Scopus and Web of science and the papers are reviewed systematically to identify their theoretical and empirical contributions.

The results reveal that monetary policy can influence corporate investment. Post to the economic crisis (2008), there is an exponential growth in the number of publications. Berger, A., and Hubbard are the two prominent authors based on the highest citation score, whereas Marquez, R., and Vermuelen, P. are the two prolific authors, subject to their highest h-index. Journal of Banking & Finance was the top journal (total citations = 1482) and 5 publications.

This study positively contributes to the comprehensive understanding of corporate investment, monetary policy transmission and firm capital structure choices.

To the best of the author’s knowledge, this is the first study that conducts a systematic review of the influence of monetary policy on corporate investment.