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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 develop the alleviating bullwhip effects framework (ABEF) replenishment rules, and bullwhip, inventory fluctuations and customer service fulfilment rates were examined. In addition, automated smoothing and replenishment rules can alleviate supply chain bullwhip effects. This study aims to understand the current artificial intelligence (AI) implementation practice in alleviating bullwhip effects in supply chain management. This study aimed to develop a system for writing reviews using a systematic approach.

The methodology for the present study consists of three parts: Part 1 deals with the systematic review process. In Part 2, the study applies social network analysis (SNA) to the fourth phase of the systematic review process. In Part 3, the author discusses developing research clusters to analyse the research state more granularly. Systematic literature reviews synthesize scientific evidence through repeatable, transparent and rigorous procedures. By using this approach, you can better interpret and understand the data. The author used two databases (EBSCO and World of Science) for unbiased analysis. In addition, systematic reviews follow preferred reporting items for systematic reviews and meta-analyses.

The study uses UCINET6 software to analyse the data. The study found that specific topics received high centrality (more attention) from scholars when it came to the study topic. Contrary to this, others experienced low centrality scores when using NETDRAW visualization graphs and dynamic capability clusters. Comprehensive analyses are used for the study’s comparison of clusters.

This study used a journal publication as the only source of information. Peer-reviewed journal papers were eliminated for their lack of rigorousness in evaluating the state of practice. This paper discusses the bullwhip effect of digital technology on supply chain management. Considering the increasing use of “AI” in their publications, other publications dealing with sensor integration could also have been excluded. To discuss the top five and bottom five topics, the author used magazines and tables.

The study explores the practical implications of smoothing the bullwhip effect through AI systems, collaboration, leadership and digital skills. Artificial intelligence is rapidly becoming a preferred tool in the supply chain, so management must understand the opportunities and challenges associated with its implementation. Furthermore, managers should consider how AI can influence supply chain collaboration concerning trust and forecasting to smooth the bullwhip effect.

Digital leadership and addressing the digital skills gap are also essential for the success of AI systems. According to the framework, it is necessary to balance AI performance and accountability. As a result of the framework and structured management approach, the author can examine the implications of AI along the supply chain.

The study uses a systematic literature review based on SNA to analyse how AI can alleviate the bullwhip effects of supply chain disruption and identify the focused and the most important AI topics related to the bullwhip phenomena. SNA uses qualitative and quantitative methodologies to identify research trends, strengths, gaps and future directions for research. Salient topics for reviewing papers were identified. Centrality metrics were used to analyse the contemporary topic’s importance, including degree, betweenness and eigenvector centrality. ABEF is presented in the study.

There have been numerous publications on human monkeypox since it was reported. With the help of bibliometric analysis, this study examined research hotspots and future trends related to human monkeypox. Science mapping was used in this study to identify influential monkeypox researchers, institutions, articles, keywords, thematic structures, and clusters of articles.

Based on a validated search query, bibliometric analysis of data collected from Web of Science from 1989 to September 2022 was conducted. Using the “Title-Keyword-Abstract” search option, the search query consisted of keywords “Monkeypox” OR “Monkeypox virus” OR “monkeypox” OR “monkey pox” OR “MPXV.” With the state-of-the-art tools Bibliometrix package of R Studio and VOSviewer, performance analysis and science mapping, as a part of standard bibliometric research of monkeypox research were conducted.

Researchers published 708 monkeypox papers from 1989 to September 2022, with American researchers publishing 460 papers. Further, USA had the highest international cooperation in terms of collaborative research output. Centers for Disease Control and Prevention (CDC) is a global leader in monkeypox research since it is the most prolific and collaborative organization. There have been the most published papers on monkeypox in the Journal of Virology. Damon Inger K is also the most prolific and influential researcher in monkeypox research, with the highest number of publications and citations. In total, 1,679 keywords were identified in the study. From the cluster analysis four themes were identified in monkeypox research. They are (1) clinical features, (2) monkeypox virus epidemiology, (3) monkeypox virus vaccine defense, and (4) monkeypox virus-related treatment measures.

Analysis of collaboration, findings, networks of research, and visualization separates this study from traditional metrics analysis. Currently, there are no similar studies with similar objectives based on the authors' knowledge.

The aim of the study is to examine the role of crowdfunding in entrepreneurial development with the help of a systematic review of the literature and bibliometric analysis.

The present research employed bibliometric analysis to study collected data from the database. Using proper keywords, data was retrieved from Scopus. With the scaler and analytical method of bibliometric analysis, the research attempts to answer the following questions, including prominent journals, authors, keywords and cluster analysis based on keyword occurrence. The mapping/networking chart is created using the VOSviewer software.

The result of the study suggests that it is an attractive and emerging phenomenon for academicians. The most papers were published in 2021, Small Business Economics and California Management Review are the most prolific journals, while Vismara S is the most significant author with 4 publications and 488 citations. Short JC, School of Management, Royal Holland and USA collaborate most. Cluster analysis of the study will help the future researcher to broaden the existing literature utilising the distinct topics.

This research aids entrepreneurs, academia, crowdfunding practitioners and policymakers in identifying application areas for crowdfunding. In conclusion, crowdfunding will enhance the entrepreneurial ecosystem.

This study elaborates the significance of crowdfunding in the development of entrepreneurship, using SLR and bibliometric analysis. The study findings identified crowdfunding's usage, applications and potential future research areas, as well as evaluated, reviewed and assessed their significance in entrepreneurial development. The theme-based cluster was determined based on the frequency of occurrence of the keywords.

This paper undertakes an extensive and systematic review of the literature on earnings management (EM) over the past three decades (1992–2022). Furthermore, the study identifies emerging research themes and proposes future avenues for further investigation in the realm of EM.

For this study, a comprehensive collection of 2,775 articles on EM published between 1992 and 2022 was extracted from the Scopus database. The author employed various tools, including Microsoft Excel, R studio, Gephi and visualization of similarities viewer, to conduct bibliometric, content, thematic and cluster analyses. Additionally, the study examined the literature across three distinct periods: prior to the enactment of the Sarbanes-Oxley Act (1992–2001), subsequent to the implementation of the Sarbanes-Oxley Act (2002–2012), and after the adoption of International Financial Reporting Standards (2013–2022) to draw more inferences and insights on EM research.

The study identifies three major themes, namely the operationalization of EM constructs, the trade-off between EM tools (accrual EM, real EM and classification shifting) and the role of corporate governance in mitigating EM in emerging markets. Existing literature in these areas presents mixed and inconclusive findings, suggesting the need for further theoretical development. Further, the study findings observe a shift in research focus over time: initially, understanding manipulation techniques, then evaluating regulatory measures, and more recently, investigating the impact of global accounting standards. Several emerging research themes (technology advancements, cross-cultural and cross-national studies, sustainability, behavioral aspects and non-financial indicators of EM) have been identified. This study subsequent analysis reveals an evolving EM landscape, with researchers from disciplines like data science, computer science and engineering applying their analytical expertise to detect EM anomalies. Furthermore, this study offers significant insights into sophisticated EM techniques such as neural networks, machine learning techniques and hidden Markov models, among others, as well as relevant theories including dynamic capabilities theory, learning curve theory, psychological contract theory and normative institutional theory. These techniques and theories demonstrate the need for further advancement in the field of EM. Lastly, the findings shed light on prominent EM journals, authors and countries.

This study conducts quantitative bibliometric and thematic analyses of the existing literature on EM while identifying areas that require further development to advance EM research.

Purpose: The study’s objective is to look at the link between money laundering and economic and financial performance, emphasising the effectiveness of the literature and possible later research directions using science mapping, which allows for scientific knowledge analysis.

Need for the Study: This study is related to a better understanding of the field’s historical evolution in terms of publications.

Methodology: This study used bibliometric approaches to analyse a sample of 660 studies from the Web of Science between 1994 and 2022, concentrating on keywords, author, paper, journal, and subject analysis. This study focused on performance analysis and scientific mapping of articles using the R package.

Findings: The empirical results indicated that the research field’s primary issues include corporate governance, fraud, machine learning, fraud detection, financial fraud, financial statement, corruption, earnings management, ethics, governance, financial reporting, bankruptcy, internal control, or performance. M. S. Beasly, D. B. Farber, E. M. Fich, R. Romano, and A. Shivdasani are the most well-known authors on the issue of money laundering and financial and economic performance. At the same time, the most typical journals are the Journal of Business Ethics, Journal of Money Laundering Control, Accounting Review, Journal of Financial Economics, and Journal of Corporate Finance.

Practical Implications: This study will act as a guide for researchers of various fields to evaluate the development of scientific publications in a particular theme over time, especially for those who are in the field of money laundering and financial performance.

Mucormycosis has evolved as a post-COVID-19 complication globally, especially in India. The research on fungus has been very primitive, and many scientific publications have been discovered. The current COVID-19 pandemic needs further investigation into this unusual fungal infection. This review study aims to provide a pen-picture to researchers, science policymakers and scientists about different bibliometric indicators related to the research literature on mucormycosis.

The quantitative research was conducted using the established procedure of bibliometric investigation on data collected from Scopus from 2011 to 2020 using a validated search query. The search query consisted of keywords “Mucormycosis” or “Mucormycoses” or “Mucormycose” or “Mucorales Infection” or “Mucorales Infections” or “Black Fungus Infection” or “Black Fungus Infections” or “Zygomycosis” in the “Title-Keyword-Abstract” search option for data extraction. The analysis of data is performed using MS-Excel. Mapping was done with state-of-the-art visualization tools Biblioshiny and VOSviewer, using bibliometric indicators as units of analysis.

The analysis reveals that the first publication on this topic was reported from 1923 onwards. In total, 9,423 authors contributed 1,896 papers with 11,437 collaborated authors, documents per author are 0.201, authors per document are 4.97 and co-authors per document are 6.03. Total records were published in 779 journals in the English language from 75 countries globally. Mucormycosis literature is mostly open access, with 1,210 publications available via different open access routes. The highest number of articles (204) published in the journal “Mycoses” with 1,333 authors received 4,875 cited references, and the h-index has 24. The growth of publications is exponential, as depicted by the Price Law. The USA has recorded a maximum number of publications at both country and institutional levels compared to the other nations. There has been extensive research on mucormycosis before the outbreak as a post-COVID complication, as indicated by the highest number of publications in 2019.

The research hot spots have altered from “Mucormycosis,” “fungi,” “Zygomycosis” and “Drug efficacy”, “Drug Safety” to “Microbiology,” “Pathology,” “nucleotide sequence,” “surgical debridement” which indicates that potential area of research in the near future will be concerned with more extensive research in mucormycosis to develop standard treatment procedures to fight this infection. The quantity of scientific publications has also increased over time. The research and health community are called upon to join forces to activate existing knowledge, generate new insights and develop decision-supporting tools for health authorities in different nations to leverage vaccination in its transformational role toward successfully attaining nil cases of COVID-19.

The analysis of collaboration, findings, the research networks and visualization makes this study novel and separates from traditional metrics analysis. To the best of the authors’ knowledge, this work is original, and no similar studies have been found with the objectives included here.

The literature on knowledge management in sustainable supply chain (KMSSC) has witnessed significant growth in the past two decades. However, a scientometric review that consolidates the primary trends and clusters within this topic has been notably absent. This paper aims to scrutinize recent advancements and identify the intellectual underpinnings of KMSSC research conducted between 2002 and 2022.

The present review employs a scientometric analysis approach via visualization maps of prolific contributions, co-citation, co-occurrence and thematic networks to examine a total of 114 articles and conference papers on KMSSC.

Emerging research frontiers and hotspots are revealed and a state-of-the-art framework of KMSSC research structure is developed.

The review provides significant implications that guide KMSSC research and better inform sustainability decisions in the supply chain context.

To the best of the authors' knowledge, this is the first review to thoroughly synthesize the intersected domain of KMSSC using scientometric analysis.

This paper aims to facilitate researchers, practitioners and policymakers in understanding and managing the impact of the black swan event – COVID-19 on work from home in the social science subject area through bibliometric analysis. For this purpose, the authors analyzed publications from the Scopus database.

In this paper, the authors conducted bibliometric analysis based on two major techniques: performance analysis and science mapping. The authors applied VOSviewer and Biblioshiny to address the research questions of present study. The study explored the hot trend topics and summarized them with discussions and implications.

Based on the analysis of 500 publications, the authors present an overview of performance and science mapping from the perspective of different aspects such as publication output and authors. Also, authors visualized the text mining by co-word analysis forming nine clusters as well as mapping trend topics. The existing publications were divided into ten clusters according to different keyword analyses: Leadership, Mental health, Technology, Crisis Management, Gender, Challenges, well-being and Work-life balance.

Sample from the Scopus database is not exhaustive, and the dataset may be skewed due to the adoption of the selection criteria. The authors’ concentration was on academic publications in English that excludes potentially intriguing and pioneering studies done in other languages. The study area was limited to social science only.

The paramount lesson is that the COVID-19 quandary is multifaceted, necessitating not simply adaptations to current strategies but also an understanding and analysis of advancements in the economy, commerce and society. According to the analysis presented above, to overcome the COVID-19 “black swan event”, managers must think ahead. The analysis gives leaders and decision-makers a range of useful information on work from home (WFH) difficulties in COVID-19, as well as initiatives and revisions that must be implemented at the economic, social and scientific aspects when dealing with such uncertainties. The findings also aid managers in forecasting the need for sophisticated technology, organizational agility and resilience to attain the desired direction of progress.

With a focus on addressing WFH during COVID-19 from social science perspective and to synthesize its future research directions systematically, the authors performed Bibliometric analysis both with VOSviewer and Biblioshiny, in order to enhance the overall analysis for higher accuracy and more reliable results that is unique value addition and contribution to the existing literature.

This study aims to conduct performance and clustering analyses with the help of Digital Government Reference Library (DGRL) v16.6 database examining the role of emerging technologies (ETs) in public services delivery.

VOSviewer and SciMAT techniques were used for clustering and mapping the use of ETs in the public services delivery. Collecting documents from the DGRL v16.6 database, the paper uses text mining analysis for identifying key terms and trends in e-Government research regarding ETs and public services.

The analysis indicates that all ETs are strongly linked to each other, except for blockchain technologies (due to its disruptive nature), which indicate that ETs can be, therefore, seen as accumulative knowledge. In addition, on the whole, findings identify four stages in the evolution of ETs and their application to public services: the “electronic administration” stage, the “technological baseline” stage, the “managerial” stage and the “disruptive technological” stage.

The output of the present research will help to orient policymakers in the implementation and use of ETs, evaluating the influence of these technologies on public services.

The research helps researchers to track research trends and uncover new paths on ETs and its implementation in public services.

Recent research has focused on the need of implementing ETs for improving public services, which could help cities to improve the citizens’ quality of life in urban areas. This paper contributes to expanding the knowledge about ETs and its implementation in public services, identifying trends and networks in the research about these issues.