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This study aims to identify the trending topics, emerging themes and future research directions in supply chain management (SCM) through multiple source of data. The insights would be of use to academics, practitioners and policymakers to leverage latest developments in addressing current and future challenges.

This study uses a multiple source of data such as published literature and social media data including supply chain blogs and forums contents on business-to-business (B2B) firms to identify trending topics, emerging themes and future research directions in SCM. Topic modeling, a machine learning technique, is used to derive the topics and themes. Examining supply chain blogs and forums offer a valuable perspective on current issues and challenges faced by B2B firms. By analyzing the content of these online discussions, the study identifies emerging themes and topics of interest to practitioners and researchers.

The study synthesizes 1,648 published articles and more than 1.3 lakh tweets, discussions and expert views from social media, including various blogs and supply chain forums, and identifies six themes, of which three are trending, and the other three are emerging themes in the supply chain. Rather than aggregate implications, the study integrates findings from two databases and proposes a framework encompassing the drivers, processes and impacts on each theme and derives promising avenues for future research.

Prior literature has majorly used published research articles and reports as a primary source of information to identify the trending theme and emerging topics. To the best of the authors’ knowledge, this is the first study of its kind to examine the potential value of information from social media, such as blogs, websites, forums and published literature to discover new supply chain trends and themes related to B2B firms and derive encouraging possibilities for future research.

This study aims to reveal the topic structure and evolutionary trends of health informatics research in library and information science.

Using publications in Web of Science core collection, this study combines informetrics and content analysis to reveal the topic structure and evolutionary trends of health informatics research in library and information science. The analyses are conducted by Pajek, VOSviewer and Gephi.

The health informatics research in library and information science can be divided into five subcommunities: health information needs and seeking behavior, application of bibliometrics in medicine, health information literacy, health information in social media and electronic health records. Research on health information literacy and health information in social media is the core of research. Most topics had a clear and continuous evolutionary venation. In the future, health information literacy and health information in social media will tend to be the mainstream. There is room for systematic development of research on health information needs and seeking behavior.

To the best of the authors’ knowledge, this is the first study to analyze the topic structure and evolutionary trends of health informatics research based on the perspective of library and information science. This study helps identify the concerns and contributions of library and information science to health informatics research and provides compelling evidence for researchers to understand the current state of research.

Special education is the education segment that deals with the students facing hurdles in the traditional education system. Research data have evolved in the domain of special education due to scientific advances. The present study aims to employ text mining to extract the latent patterns from the scientific data.

This study examined the 12,781 Scopus-indexed titles, abstracts and keywords published from 1987 to 2021 through an integrated text-mining and topic modeling approach. It combines dynamic topic models with highly cited reviews of this domain. It facilitates the extraction of topic clusters and communities in the topic network.

This methodology discovered children’s communication and speech using gaming techniques, mental retardation, cost effect on infant birth, involvement of special education children and their families, assistive technology information for special education, syndrome epilepsy and the impact of group study on skill development peers or self as the hottest topic of research in this domain. In addition to finding research hotspots, it further explores annual topic proportion trends, topic correlations and intertopic research areas.

The results provide a comprehensive summary of the popularity of research topics in special education in the past 34 years, and the results can provide useful insights and implications, and it could be used as a guide for contributors in special education form a structured view of past research and plan future research directions.

The purpose of this study is to comprehensively review the human resource management (HRM) and employment relations (ERs) field and explore the knowledge map, knowledge evolution trends and paths and paradigm shifts within this field.

The Structural Topic Model in combination with Word2vec is proposed and applied in this work. First, this paper detects and interprets the research topics by reviewing 23,786 papers from 29 important journals in this field from 1990 to 2021. Then, this research explores popularity trends by aggregating topic proportions from a temporal perspective. Finally, this work explores the research topic evolution from the semantic perspective.

This paper obtains the following findings: (1) Sixteen research topics are identified, which provide the basic research overview of the whole field. (2) The changes in topic popularity over time map the tendency for employee benefits to be valued. (3) The evolutionary trajectories of temporal local topics are provided, which reflect the mechanisms of the paradigm and ideological migration and fusion.

This work adopts state-of-the-art textual as well as semantic mining techniques to establish a comprehensive knowledge map for HRM and ER research. Furthermore, these results uniquely demonstrate the pluralistic ideological orientation at the social level is gradually integrated into more micro levels, such as enterprises and individuals. These are the contents that were mentioned from previous studies by scholars, but not meticulously verified and interpreted.

This study aims to expand tourism knowledge by analysing literature review articles published in English Web of Science (WOS) and Chinese China National Knowledge Infrastructure (CNKI) language journals and reviewing their influence, interconnection and trends.

A three-stage method was designed to understand the tourism research progress. Performance analysis identified the publication timeline, high-yielding journals and authors that published tourism literature reviews and frequently cited papers. Science mapping visualisation examined the intrinsic connections between co-authorship and co-institution. Finally, emerging trend analysis explored the topic modelling and evolution through Latent Dirichlet allocation (LDA) and regression.

The key statistics and collaborations relationships of tourism literature reviews were traced. LDA identified 45 and 22 topics, which narrowed the barriers in tourism studies. The regression analysis divided these topics into “hot”, “fresh”, “bell-shaped” and “stable” patterns. These modes represent the progress of tourism studies. The topic “new emerging technologies and the internet” is the focus of tourism literature reviews published in both databases. Future research could pay more attention to the topics in the “hot” and “fresh” patterns. The results enrich the progress of tourism literature reviews and provide a direction for future research.

To the best of the authors’ knowledge, this study is the first literature analysis for tourism literature reviews published in WOS versus CNKI journals. The proposed three-stage systematic method is used for the first time for the literature review and can guide future research.

本研究旨在通过分析英文WOS和中文CNKI语言期刊上发表的文献综述文章, 回顾其影响、相互联系和趋势, 来扩大旅游知识体系。

本研究设计了一个三阶段方法来了解旅游研究进展。绩效分析确定了出版时间线、发表的旅游文献综述的高产期刊和作者以及经常被引用的文章。科学地图可视化审视了合作作者和合作机构之间的内在联系。最后, 新兴趋势分析通过潜在狄利克雷分配和回归探讨了主题建模和演变。

本文追踪了旅游文献综述的关键统计数据和合作情况。潜在狄利克雷分配确定了45个和22个主题, 这缩小了旅游研究中的研究缺口。回归分析将这些主题分为“热门”、“新鲜”、“钟形”和“稳定”模式。这些模式代表了旅游研究的进展。主题“新兴技术和互联网”是不同数据库中发表的旅游文献综述的焦点。未来的研究可以更多地关注“热门”和“新鲜”模式中的主题。研究结果丰富了旅游文献综述的进展, 为今后的研究提供了方向。

这项研究是首次对WOS与CNKI期刊上发表的旅游文献评论进行文献分析。所提出的三阶段系统方法首次用于文献综述, 可以指导未来的研究。

El objetivo de este estudio es ampliar el conocimiento turístico analizando los artículos de revisión documental publicados en revistas, tanto en la versión WOS en inglés cómo en CNKI China, y revisando sus efectos, interconexiones y tendencias.

Se ha diseñado el método de tres etapas para comprender el progreso de la investigación turística. El análisis del desempeño determinó la línea de tiempo de publicación, las revistas de alto rendimiento y los comentarios de la literatura turística publicados por los autores, así como los artículos citados con frecuencia. La visualización de los mapas científicos, examina los vínculos intrínsecos entre los autores colaboradores y las instituciones colaboradoras. Finalmente, el análisis de tendencias emergentes explora el modelado temático y la evolución a través de posibles asignaciones y regresiones de dilick-ray.

Se han analizado las estadísticas clave y las relaciones de cooperación de la revisión de la literatura turística. La asignación potencial de dilich-ray identifica 45 y 22 temas, lo que reduce las barreras en la investigación turística. El análisis de regresión divide estos temas en patrones “populares”, “novedosos”, “en forma de campana” y “estables”. Estos modelos representan el avance de la investigación turística. El tema “tecnologías emergentes e internet” es el foco de la revisión de la literatura turística publicada en diferentes bases de datos. La investigación futura puede centrarse más en temas en modelos “populares” y “novedosos”. Los resultados de la investigación enriquecen el progreso de la revisión de la literatura turística y proporcionan una dirección para futuras investigaciones.

El estudio es el primer análisis documental de los comentarios de la literatura turística publicados en las revistas WOS y CNKI. El método sistemático de tres etapas propuesto se utiliza por primera vez en la revisión documental y puede guiar futuras investigaciones.

The primary aim of this study is to detail the use of soft computing techniques in business and management research. Its objectives are as follows: to conduct a comprehensive scientometric analysis of publications in the field of soft computing, to explore the evolution of keywords, to identify key research themes and latent topics and to map the intellectual structure of soft computing in the business literature.

This research offers a comprehensive overview of the field by synthesising 43 years (1980–2022) of soft computing research from the Scopus database. It employs descriptive analysis, topic modelling (TM) and scientometric analysis.

This study's co-citation analysis identifies three primary categories of research in the field: the components, the techniques and the benefits of soft computing. Additionally, this study identifies 16 key study themes in the soft computing literature using TM, including decision-making under uncertainty, multi-criteria decision-making (MCDM), the application of deep learning in object detection and fault diagnosis, circular economy and sustainable development and a few others.

This analysis offers a valuable understanding of soft computing for researchers and industry experts and highlights potential areas for future research.

This study uses scientific mapping and performance indicators to analyse a large corpus of 4,512 articles in the field of soft computing. It makes significant contributions to the intellectual and conceptual framework of soft computing research by providing a comprehensive overview of the literature on soft computing literature covering a period of four decades and identifying significant trends and topics to direct future research.

The study aims to analyze, realize and identify the extent of research on financial literacy (FL) and to reveal the study trends, growth and evolution in the Scopus database from a bibliometric analysis. Principally, the primary purpose of this study is to conduct a comprehensive bibliometric review of studies focusing on the use, identification, network structure and conceptual structure of FL.

The most relevant articles were found using an electronic search. The studies that would be reviewed were sourced from the Scopus database. A total of 1,211 articles were found and refined to 768 papers between 1997 and 2021. Every composition has been analyzed in different dimensions such as co-authorship, co-citation, conceptual structure, co-word occurrence, trend topics analysis, thematic map, topic dendrogram, three field plot diagram and visualization analysis with the help of R programming language and VOSviewer software.

Motor themes, basic transverse, niche, and emerging and declining themes were identified using (Callon, 1991) a strategic thematic map. The analysis’s results showed that, over the past 20 years, FL literature has advanced remarkably. It also acts as a reference means for future researchers. This study adopted relational techniques such as co-word, co-author, co-citation analysis, bibliographic coupling and thematic map analysis revealing the emerging topics for future research. The relational approach indicates that “FL” and “human” are two central parts that connect to other frequently used words in the studies examined.

The study deploys bibliometric analysis appropriate for deriving insights from the vast extant literature. However, a meta-analysis might offer deeper insights into specific dimensions of the research topic. It expands the previous literature and shows study topics that are more focused by examining the abstracts and contents of articles published in journals in different Scopus categories. For future researchers to derive a solid theoretical framework, a systematic review of the literature and meta-analysis would be helpful. Science mapping for this study is limited to the Scopus database owing to its more comprehensive coverage of good-quality journals.

For future researchers to derive a solid theoretical framework, a systematic review of literature and meta-analysis would be helpful. Science mapping for this study is limited to the Scopus database owing to its more comprehensive coverage of good-quality journals. The authors offer suggestions for promising directions for future research that could address some of the inconsistencies found from the bibliometric analysis study.

This study can help both budding and established researchers to find new research focus, relevant sources, and collaboration opportunities and make informed decisions. Findings related to evaluative and relational techniques can serve as helpful information for researchers who are new to the field.

It shows the indicators used to benchmark institutes, authors, journals or articles. The increase in researchers’ collaborative, multi-authored and interdisciplinary efforts also revealed an annual growth rate of 23.77%. Overall, this study enhanced the understanding of the FL phenomenon and provided an experience and interpret a wide range of publication- and citation-based statistics. This study contributes to understanding the collaborative networks of various researchers and institutions and the benefits/detriments of collaborating cross-disciplinary, internationally, or with industry or corporate institutions.

The purpose of the paper is to present an integrated methodology for identifying trends in a particular subject area based on a combination of advanced text mining and expert methods. The authors aim to test it in an area of clinical psychology and psychotherapy in 2010–2019.

The authors demonstrate the way of applying text-mining and the Word2Vec model to identify hot topics (HT) and emerging trends (ET) in clinical psychology and psychotherapy. The analysis of 11.3 million scientific publications in the Microsoft Academic Graph database revealed the most rapidly growing clinical psychology and psychotherapy terms – those with the largest increase in the number of publications reflecting real or potential trends.

The proposed approach allows one to identify HT and ET for the six thematic clusters related to mental disorders, symptoms, pharmacology, psychotherapy, treatment techniques and important psychological skills.

The developed methodology allows one to see the broad picture of the most dynamic research areas in the field of clinical psychology and psychotherapy in 2010–2019. For clinicians, who are often overwhelmed by practical work, this map of the current research can help identify the areas worthy of further attention to improve the effectiveness of their clinical work. This methodology might be applied for the identification of trends in any other subject area by taking into account its specificity.

The paper demonstrates the value of the advanced text-mining approach for understanding trends in a subject area. To the best of the authors’ knowledge, for the first time, text-mining and the Word2Vec model have been applied to identifying trends in the field of clinical psychology and psychotherapy.

This research addresses the pressing need for comprehensive studies in the rapidly evolving field of city tourism. This study aims to understand the overall performance of the International Journal of Tourism Cities (IJTC), the structure of knowledge in city tourism research and the prevalent themes and trends arising from IJTC.

A bibliometric analysis was conducted to scrutinize the publication patterns in IJTC. This involved examining parameters such as the annual count of published articles, the keywords used in them and their respective authors.

The findings reveal that IJTC has a growing and diverse publication output, establishing itself as a reputable and influential publication within urban tourism research. The results reflect various aspects and themes in city tourism research.

The study has certain limitations. The data used for analysis was obtained exclusively from the Scopus database. The analysis was conducted using only one software package, Bibliometrix. Other software packages may offer different features for bibliometric analysis. The study relied exclusively on quantitative methods for data analysis. Qualitative methods could have provided more nuanced interpretations of the data.

Comparative analyses could be conducted between IJTC and other journals within urban tourism or related disciplines. Such research would yield valuable insights into the current state of the field and aid in identifying areas warranting further investigation.

The findings from this study can inform the decisions and actions of various stakeholders involved in urban tourism. Practitioners and policymakers can draw from this research to make informed decisions. Existing and emerging authors can identify relevant topics for their research. Readers can access pertinent information for their needs.

This study offers a unique contribution by thoroughly comprehending the performance of IJTC between 2015 and 2023. It progresses the existing body of knowledge on city tourism research by examining its current status and future trends.

This study systematically reviews the current state of research on the application of high technology in supply chain management (SCM). It identifies key topics, trends and influential scholars in this field, providing a knowledge structure for future research. This study contributes to advancing the understanding of how high technology can be leveraged to enhance SCM, guiding and informing future research endeavors.

A comprehensive bibliometric analysis was conducted on 1,523 published articles retrieved from Web of Science. Through co-occurrence analysis of the titles, abstracts and keywords, the authors investigated popular research trends and topics. Through co-citation and co-authorship analyses, the authors identified leading research clusters, productive researchers and countries of the research.

There is a significant increase in publications by scholars from the USA, China and India on the impact of high technology on supply chains, particularly on food supply chains. Most articles examine the barriers and challenges of applying blockchain technology to different aspects of supply chains. Active contributions predominantly originate from scholars in the USA and China. The top five largest clusters are “supply chain management,” “scoping review,” “blockchain technology”, “food supply chains” and “management perception.”

This study represents the first systematic review establishing a comprehensive framework of knowledge on high technology and supply chains. Highlighting key research areas, tracing the evolution of research and explaining the knowledge structures pertaining to the role of high technology in supply chains, this study contributes to the existing literature and its findings hold practical implications for scholars and practitioners.