Business resilience has received much attention in this decade because it is an essential and effective means of overcoming various shocks, thereby increasing business desirability. However, it always experiences adjustments from time to time, because environmental changes are bound to occur. For this reason, resilience-forming features continue to develop over time. The main purpose of this paper is to present a map of the evolution of academic work and critical trends, as well as a snapshot of future research on business resilience. This study uses a bibliometric approach to process a total of 722 articles published between 1990 and early 2023 and indexed by SCOPUS. The results show increasing interest in business resilience research from year to year and 2022 it shown to have the highest number of published business resilience articles. The United States is the country that produces the most extensive business resilience research in the world. The authorship result also shows the influential authors within the field. Furthermore, based on the co-word analysis of the research results, the formation of five clusters goes towards describing the latest topics in business resilience research. Based on these five clusters, research trends are proposed to guide potential areas for further research related to research domains that are important to study, extreme situations that affect business, dynamic capabilities that must be possessed and various types of capital that companies must have in dealing with the various conditions. This research can ensure that researchers have inclusive insights on this topic.

Corporate borrowings being a significant driver of firm’s performance and value, have garnered the attention of scholars across the globe. Further, efforts have also been exerted by the scholar community to analyse its determinants as well as its effect on firm performance and value. In this context, this study aims to explore the key areas, most influential authors, widely used keywords, most studied countries and also suggests future research directions in the field of corporate borrowings. This study has used a systematic literature review methodology and bibliometric analysis with a sample of 708 studies taken from both Scopus and Web of Science database over the period from 1994 to 2022. Though these studies have been attempted throughout the world but majority of countries are the new participant in the field of corporate borrowings. The sluggish growth of literature in this field is due to lack of collaboration, focus on cross-country analysis, inter-industry comparison and focus on small firm. Further, the study reveals that though some areas like Capital structure, Debt maturity and Corporate debt have been amply addressed but areas like Cost of debt, Credit risk, Debt structure, Environmental, Social & Governance (ESG), Economic Policy Uncertainty (EPU), Information asymmetry, Corporate bonds and Ownership structure have been given very least attention which can be studied as a future research agenda.

Predictive analytics has gained significant attention in business as organizations seek to leverage data-driven insights for informed decision-making. The study uses rigorous bibliometric analysis to map the landscape of predictive analytics in business, revealing its evolution, trends, and research tendencies. A sizeable selection of academic publications from the Scopus database is chosen to identify key themes, notable authors, well-known journals, and emerging research areas in predictive analytics. The study extracts and analyses bibliographic data, including publication trends, citation patterns, and co-authorship networks, using cutting-edge tools like CiteSpace, VOSviewer, and Biblioshiny. The findings of this study provide important information regarding how predictive analytics are now being employed in the business sector. The most significant research findings, innovative breakthroughs, and major research clusters are highlighted, exposing the leading research paths and areas of interest. Additionally, emerging trends, cross-disciplinary collaborations, and potential research needs are identified in the study. The intellectual landscape of predictive analytics in business is mapped in this study to offer a comprehensive picture of the corpus of knowledge. This information will help scholars, practitioners, and policymakers navigate and contribute to this fast-developing area. The insights gained from this bibliometric analysis can guide future research endeavors, inform strategic decision-making, and foster stakeholder collaboration in leveraging predictive analytics for business success.

The rapid advancement of Artificial Intelligence (AI) in recent years has precipitated transformative changes across various industries, with Supply Chain (SC) management being no exception. Given the swift progression and the advent of innovations such as ChatGPT, it becomes imperative to delineate both the historical and recent academic contributions to this field, thereby facilitating a comprehensive understanding of future trajectories and the potential impact of these technologies. Consequently, we conducted a scientometric review utilizing the Scopus and Web of Science databases, with data preprocessing executed via R and Python. The resultant findings are bifurcated into two sections: the first encompasses a scientometric mapping of annual scientific production, country-specific contributions, journal publications and author collaboration analysis. The second section delineates the evolution of theoretical contributions, employing the metaphor of the Tree of Science for illustrative purposes. The conclusions underscore the paradigm-shifting impact of AI on SC management.

Ongoing advancements are being made in mathematics education to meet the demands of modern pedagogy and student learning. Therefore, it is imperative to understand contemporary research trends in mathematics textbooks to align with contemporary pedagogical standards and accommodate diverse student learning needs. The current bibliometric review aims to analyse the publication trends of studies about mathematics textbooks. This review employed datasets from the Scopus and Web of Science (WoS) databases and analysed them using ScientoPy and VOSviewer. The examination of publication trends revealed a substantial surge in academic engagement in mathematics textbooks, particularly in recent times in both databases. The surge in publications signifies an expanding scholarly focus and commitment to advancing knowledge in mathematics education, with a particular emphasis on mathematics textbooks. An examination of source titles unveiled that Journal of Physics: Conference Series articles impact the discourse within the field. Some prevalent keywords, including “mathematics textbooks”, “problem-posing”, and “statistics education”, have surfaced in contemporary research, attesting to the field’s evolving trends. The growing emphasis on “design” and “cognitive demand” indicates an expanding aspiration to foster enhanced conceptual comprehension and cognitive involvement among students. Further investigation into the impact of instructional design and cognitive demand on fostering more profound understanding and active participation in mathematics is warranted, particularly emphasising the practical ramifications for curriculum designers and educators.

Virtual education began to emerge with the advent of the internet and digital technologies in the late 20^th and early 21^st centuries. It has been instrumental in overcoming geographical limitations, expanding educational access and reducing the gap between learners worldwide who have and have nots. Over the last few decades, a significant number of investments and initiatives (at both government and institutional levels) have been observed aiming to establish a sustainable online education system. The objective of the study is to provide an overview of the research trend on virtual teaching for online learning from the perspective of higher education across the globe in the 21^st century. The required publication data has been collected from Scopus and Web of Science databases and various bibliometrics tools and techniques have been employed to visualize publication growth. It is found that the highest contribution has been made by China (16.92%), followed by the United States (15.38%), Spain (12.05%) and the UK (6.15%). The study identifies three dominant trends: 1) the evolution of technology-driven learning and training systems; 2) the rise and impact of immersive learning in digital environments; and 3) a systematic review of e-learning methodologies. This research outlines the overall progression of scientific literature in virtual education and highlights the need for comparative and nuanced research among online learning modalities, essential for guiding educational policymakers and university administrations in the optimal combination of traditional and virtual learning methods. This integration promises to enhance the accessibility and effectiveness of education in an increasingly digital world.

This paper incorporates scholarly articles, conference papers, and published books, analyzing these sources to explore how topic modeling is used to uncover trends, identify research areas, and contribute to understanding the digital economy. The study utilizes bibliography data and Python libraries for topic modeling to examine 8,321 documents from the Scopus database. Through rigorous analysis, three distinct topics were identified, and their development trends were traced, providing insights into the shifting focus within the field. The study also validates the classification proposed by the coherence coefficient and contributes theoretically and methodologically by employing Latent Dirichlet Allocation (LDA) topic modeling technology within text analytics. The results of this study indicated that “Digital Transformation” emerged as the most popular, accounting for 56.6% of tokens. However, the “Digitalization” topic exhibited relatively lower popularity, representing only 21.2% of tokens. The findings help enhance the understanding of global research trends and offer a valuable framework for comprehending digital economy research. Furthermore, the study emphasizes the significance of analyzing digitalization, data governance, and digital transformation, highlighting the efficacy of LDA as a powerful tool for efficient and accurate text analytics. The research findings are especially pertinent for scholars in information science, data mining, econometrics, and bibliometrics. They offer a foundational understanding of topic modeling, facilitating further investigation and exploration in these fields. However, the study identifies two limitations, including the limited dataset extracted solely from Scopus and the restriction to abstracts rather than full texts. Future research should consider expanding data sources and incorporating full texts from authoritative articles in multiple languages to attain more comprehensive outcomes.

The R package ‘tosr’ enables the construction of the Tree of Science (ToS), a metaphorical representation of scientific papers on a specific topic. The ToS’s roots symbolize seminal works, the trunk stands for structural works, and the leaves depict the current literature. Traditionally, researchers have had to limit their ToS to data from a single database, such as Scopus or Web of Science (WoS). The ‘tosr’ package overcomes this limitation by allowing researchers to merge seed files from both Scopus and WoS, thereby facilitating a more comprehensive bibliometric analysis. This paper describes the development and application of the ‘tosr’ package, demonstrating its unique capabilities in creating a completer and more cohesive ToS and citation network for any scientific topic. By bridging the gap between these two major databases, ‘tosr’ offers researchers an unprecedented tool for scientometric research.

This paper deals with a new stochastic method to solve Lotka’s Law with higher degree of Newton-Cotes Quadrature Rule as an alternate method to existing solution of the value determination of the constant part of the power law; so far, M.L. Pao gave a solution with an equation to determine the area under the curve with numerical integration rule with degree=1 which is also known as Trapezoidal Rule. Here, next higher degree 2, popularly known as Simpson’s 1/3 rule at closed interval [x] has been used to establish a deterministic equation form to solve authors’ productivity realized through Lotka’s Law. Re-estimating the value of C with higher degree quadrature rule is very crucial as the probability of inclusion of more area and exclusion of unnecessary area under the curve is more precise. Another area of investigation is the determination of p value (Pao determined p=20), i.e. whether p=20 can be altered? Or equation derived through Simpson’s 1/3 rule, whether it can give a minimal residual error beyond p=20. This paper is dedicated to build up a mathematical equation to solve the constant value(C) of the Lotka’s law equation as well as enlighten all these investigating points.

The study investigated the effects of microplastics on marine life through scientometric analysis and visualization of research publications. A total of 8,397 scientific documents were collected from the Scopus database covering the years 2013 to 2022 using bibliometric tools. The analysis includes annual scientific production, prolific authors, influential journals, productive institutions, keyword co-occurrences, thematic structures, factorial maps, globally cited publications, research trends, country-wise contributions, international collaborations and funding agencies’ roles. The findings revealed that 2022 was the most productive year for publishing, with 3,239 documents. Y Zhang emerged as the most prolific author in this field, while the Journal of Science of the Total Environment had the highest number of publications. East China Normal University is the most productive institution that contributed the maximum number of publications. The word microplastic is the most frequently used keyword by researchers. The study ‘The Physical Impact of Microplastics on Marine Organisms: A Review’ by Wright, S. L. et al. was a highly cited paper, indicating its significance in the field. The analysis also highlighted the National Natural Science Foundation of China was the major funding agency and China exhibited the strongest international collaboration with the USA. This study provides crucial insights for addressing knowledge gaps, promoting collaboration and guiding evidence-based policies to mitigate the impacts of microplastics on marine ecosystems.

Mine safety/Mining Safety (MS) is gaining significant attention in underground mine worldwide. Therefore, studies of MS have gained huge interest all over the world. However, little studies of MS reveal the map of the research field by big data from the perspective of a comparative vision over the past 23-year timespan. To this end, this study used big data and visualization tool (Vosviewer) to comparatively provide a comprehensive systematic mapping of MS studies in the WOSCC and Scopus. A total of 415 (WOSCC) and 691 (Scopus) articles were finally included. The number of articles shows a growth trend during 2000-2022, especially in the last five years. The most prolific authors are mainly from China which has published the highest number of articles. China is also the leading country in MS study, followed by USA. Safety Science is the top-publishing journal in the WOSCC (37, 8.92%) and Scopus (37, 5.35%), with the highest number of citations (1290 in the WOSCC and 1519 in the Scopus). Of Top10 most cited articles, 6 articles are published by Chinese authors in the WOSCC, and 4 articles from Chinese authors in the Scopus. China Univ Min and Technol had the most articles (60 in the WOSCC and 72 in the Scopus), but the average number of their citations per article (17.15) was somewhat low, though its total citations ranked first. In the WOSCC, Shandong Univ Sci and Technol has the highest number of citations per article (29.00), while in the Scopus, Univ Queensland ranks first in the average number of their citations (31.58). The main findings provide insights for MS researchers and policy-makers on the trends, progress, and future direction of the MS study.

Enzymes are responsible for any biochemical reactions including the transformation of toxic pollutants by microbes. Identification, isolation and application of enzymes for biodegradation of environmental pollutants have become one of the research hotspots. Whether it is due to the constant seeking of a better enzyme, advances in techniques, or increases in some pollutants, there have been exponential increases in the number of research on enzymatic bioremediation. A Scientometrics study was undertaken to capture the holistic view of enzymatic bioremediation. 14,952 research papers were identified from a topic search covering the period 1983 to 2023 from the ‘web-of-science’ database. The social network analysis approach was used for understanding the structure and dynamics of the research. The study identifies that among the enzymes, research activity is most intense in laccase followed by peroxidase and dioxygenase whereas, in microbes, Pseudomonas sp., Bacillus sp. and Phanerochaete sp. are areas show maximum research. In contrast to fungus and fungal enzymes, there has been gradual increases in research on bacteria and bacterial enzymes. Dye, Polyaromatic hydrocarbons (PAHs) along with other emerging pollutants like plastics and pesticides are the most studied substrates. The study also draws attention to research increasingly being undertaken to identify, isolate and manipulate new enzymes using various emerging techniques such as metagenomics, genetic engineering, molecular docking and simulations. The results and implications of the study are discussed.

Food Labeling is a critical communication mechanism to support consumers in making informed choices during purchase and to secure good health. The food safety standard authorities around the globe are working very hard to make food labeling world-class and user-friendly. In the present study, scientometric analysis is performed on the publication data extracted from the Web of Science (ClarivateTM) database on food labeling. The publications are analyzed by the years, keywords, prolific authors and evolution of the research field is traced. The analysis of publication data in the realm of food labeling shows that the food labeling research got attention of researchers during the first decade of 21^st century as many new laws and regulations were formed in US and Europe during this time. It is observed that the researchers of developed countries are publishing majorly on different aspects of food labeling followed by developing countries.

Food security is a multidisciplinary field with evolving definitions, causes, consequences and solutions. In this paper, using tools of scientometrics and bibliometrics-publication performance analysis and science/network mapping, we try to gain an aggregated macro view of food security literature conducted in or closely related to India. We use VOSviewer and bibliometrix/ biblioshiny in the R programme to generate network maps and publication trends. We find that the quantum of publications in the field of food security has increased over the last 30 years (1980-2021). India collaborates most with the USA and more recently with Belgium, Israel, Japan and Hungary. ‘Field Crops Research’ and ‘Food Security’ are the most impactful journals. The authors and publications exploring the mitigation of climate change, genetic trait improvement of crops and sustainable agricultural practices are of much relevance and influence. Climate change, agriculture, rice, wheat, yield and productivity are the most prominently used keywords for food security research in India. Research on food security now focuses on nutrition, gender, climate change and diet structure rather than yield and supply. For further research, building climate resilient food consumption patterns, exploring indigenous food diversity and links between gender and food/nutrition security and other micro-level intra-household dynamics can be explored. Evidence-based decision-making, intellectual collaboration and the creation of successful policies and interventions will all be made possible by scientometrics’ insightful understanding of the dynamics and structure of food security research

Underwater sensing has a wide range of applications including the location and monitoring of subsurface infrastructures such as cables and pipelines, mapping undersea terrain, the study of marine life, pollution and salinity monitoring and detection of seismic activities. Underwater sensing technologies are also essential to maritime surveillance, detection and tracking of submarines and other underwater objects. Using natural language processing and machine learning, we mined scientific publications to gain insight into underwater sensing research evolution during the 21^st century, in terms of technology development and applications. This study offers a comprehensive analysis of the underwater sensing research landscape as well as the temporal evolution of its main research topics. We identified 18 key research topics that offer comprehensive and logical coverage of the research field. Nearly half of them are on a decreasing trend, despite an overall increase in the number of scientific publications. These findings and the extracted patterns can provide researchers and decision-makers with new insights into the field, its characteristics and its development. Our proposed algorithmic approach can also be applied to other areas for technologies of a disruptive nature.

This paper’s bibliometric investigation aims to provide the formula for effective sports training. Finding patterns and trends in the literature is important to help coaches and athletes enhance their training plans. The Scopus database and 4276 articles were used for the analysis. According to the findings, the Journal of Strength and Conditioning Research has the highest H-Index of 50. With 199 documents, the University of Copenhagen in Denmark is the leading affiliate. With a total of 595 times, the term “exercise” is used by the authors the most. Additionally, “dyspnea” has the biggest relative growth, while “exercise training” is a trending issue with the largest absolute increase. The terms “power,” “speed,” and “strength” all have definitions that are very relevant to coaching athletes. The findings demonstrate that effective sports training necessitates a multidisciplinary strategy that considers each athlete’s particular requirements and skills. This study sheds important new light on the literature on exercise training and emphasises the significance of evidence-based training in sports. The findings can be utilised to help create training plans that maximise performance, stop injuries and enhance athlete wellbeing.

The purpose of this study is to draw a scientific map of the field of marketing and identify its historical origins with spectroscopic approach. The research is applied in terms of purpose and survey-analytical in terms of methodology with a bibliometrics approach. Web of Science database was used to collect data. A review of 113,500 marketing documents was conducted between 1920 and 2020. The collected data were categorized based on bibliometrics indicators and analyzed using VOS-Viewer, CiteSpace and CRExplorer softwares. Findings showed that the growth trend of articles in the field of marketing has been upward. The citations received by marketing articles by year (Over a hundred years), with the help of CRExplorer software, showed 5 historical mutations in 1969, 1976, 1989, 2000 and 2004. The largest mutation was in 2000, with more than 18,000 citations. The results of co-authorship analysis also showed; at the countries level, the United States, the United Kingdom and Australia; at the university and scientific institute level, the universities of Michigan, Wisconsin, Minnesota, and Ohio have had the most scholarly collaboration at the level of authors, Kumar, Ocass, and Sargent. Regarding influential and highly cited and quality magazines in the field of marketing, Journal of marketing, Journal of marketing research and Journal of Consumer Research attract attention. In general, by looking at the various bibliometrics indicators as well as reflecting on the illustrated results of the research data; the most important point was the existence of differences in the quantity and quality of factors involved in the production of scientific articles (including authors, journals, etc.). Therefore, it can be said that by using each of the bibliometrics indicators, the results can be analyzed from a new perspective.

Identifying influential nodes in an article network is crucial for understanding the dynamics of information propagation and its impact on various applications. Traditional methods often rely on citation-based analysis or network structure, overlooking the intricate dynamics of diffusion and node linkages. In this research, we propose a novel scoring model, named “Epigraphiology,” which combines these aspects to compute and analyze the elements contributing to the spread of influence in article networks. To evaluate the effectiveness of our approach, we employ real published article networks with around 904 articles downloaded from the WOS (Web of Science) with total cited references of 32084 in the field of cloud computing from 2010 to 2015. By leveraging the SIR (Susceptible-Infected-Removed) model, we compare the dynamics of articles in the network with the transition of states, highlighting the diffusion process. Additionally, we derive the Reproduction number (R0) for our model, serving as an indicator of the potential spread of influence. Our findings showcase the following key contributions: (a) Epigraphiology introduces a novel methodology for measuring the diffusion capacity of an article’s influence in a hybrid manner, combining diffusion dynamics and node linkages. (b) Contrary to traditional approaches that primarily consider the number of citations (in degree), our results reveal that articles with lower citation counts can still act as super-spreaders, reflecting the ground-truth influence scores. Cross-validation of an article’s influence diffusion score is performed, shedding light on the significant factors contributing to its spread within the network. By bridging the gap between diffusion dynamics, node linkages, and influence measurement, Epigraphiology offers a comprehensive approach to understanding and quantifying the spread of influence in article networks. This research holds implications for various fields and applications where the identification of influential spreaders is paramount in leveraging information dissemination and impact assessment.

Throughout history, the planning of ancient civilizations, such as the Indus Valley, Greek, Roman and Egyptian, placed a significant emphasis on health as a key factor for the well-being of their inhabitants. Today, the relationship between environment, health and place remains a widely explored topic in literature. This study aims to provide a comprehensive exploration of the literature to identify key thematic areas, temporal focus, shifts in ideologies and gaps and overlaps in existing knowledge by employing a bibliometric analysis including 2775 relevant articles. The most prominent authors, publications and institutions were identified using a keyword analysis, a co-citation analysis and a social network analysis. The research also included a content analysis of the articles to identify important thematic areas and time frames. Key findings indicate that the role of place and planning for health has been thoroughly discussed, with an emphasis on urban strategies to improve health conditions. However, the literature also highlights a gap in research on the impact of land-use distribution in a city on environmental health. A model of primary links between urban planning, health and the environment has been generated, visualizing their interconnectedness. By mapping the existing knowledge on environmental health in the context of city planning, this research provides a comprehensive understanding of the topic and identifies areas for future research and policy development. The study’s contributions include a visual portrayal of the interdependence of urban planning, health and the environment, as well as a thorough investigation of the literature on environmental health in relation to city design.

The study compared the bibliometric parameters of scholarly communications published in COLLNET Journal of Scientometrics & Information Management (CJSIM) and Journal of Scientometric Research (JSR) from 2012 to 2021. Different bibliometric parameters examined in the study are pattern of output during 2012 to 2021, identification of most prolific countries and their citation impact in terms of Citation Per Paper (CPP), i-10 index and Papers not Cited (PnC). Study also identified prolific institutions and authors and their citation impact besides examining pattern of citation. The study also examined the pattern of domestic and international collaboration. Findings of the study indicate that the pattern of output is inconsistent in both the journals. The output is scattered among 39 countries in CJSIM and 50 countries in JSR. India followed by Iran contributed the highest number of papers in both the journals. Most of the prolific institutions and authors were from India in both the journals. More number of papers remained uncited in CJSIM as compared to JSR. More number of papers were published in domestic collaboration in JSR as compared to CJSIM. However, papers published in international collaboration in both the journals was almost equal. Among all the countries, China published the highest number of papers in international collaboration in CJSIM, but no such trend was observed in JSR.