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This paper aims to reveal the interdisciplinarity of information science (IS) from the perspective of the evolution of theory application.

Select eight representative IS journals as data sources, extract the theories mentioned in the full texts of the research papers and then measure annual interdisciplinarity of IS by conducting theory co-occurrence network analysis, diversity measure and evolution analysis.

As a young and vibrant discipline, IS has been continuously absorbing and internalizing external theoretical knowledge and thus formed a high degree of interdisciplinarity. With the continuous application of some kernel theories, the interdisciplinarity of IS appears to be decreasing and gradually converging into a few neighboring disciplines. Influenced by big data and artificial intelligence, the research paradigm of IS is shifting from a theory centered one to a technology centered one.

This study helps to understand the evolution of the interdisciplinarity of IS in the past 21 years. The main limitation is that the data were collected from eight journals indexed by the Social Sciences Citation Index and a small amount of theories might have been omitted.

This study identifies the kernel theories in IS research, measures the interdisciplinarity of IS based on the evolution of the co-occurrence network of theory source disciplines and reveals the paradigm shift being happening in IS.

This study aims to conduct a bibliometric analysis on knowledge management from journals in the Scopus database between 1988 and 2021. The paper covered the past three decades of publications and carried out performance analysis and science mapping analysis of articles.

The study uses bibliometrics, performance analysis and science mapping analysis of 1,016 articles extracted from the Scopus database. The study examined the scientific productivity of articles, productive authors, citable documents, most relevant institutions, cited countries, co-occurrence of keywords, thematic mapping, co-citations and collaboration of authors and countries. The study used Biblioshiny as a tool to carry out the performance analysis and science mapping analysis.

The results show that the number of publications has significantly increased in the past decade, 88.4% of authors contribute at least a single article, 8.3% of authors published two articles, 2% of the authors published three documents and 0.6% of the authors contribute four papers. The USA, China and Australia were the most productive countries in terms of the total number of citations and foreign collaborations. Journal of Knowledge Management, Knowledge Management Research and Practice, VINE Journal of Information and Knowledge Management and International Journal of Technology Management are the top outlets in the knowledge management literature.

Over the past decade, the research on knowledge management construct has exploded because of the growing interest of researchers and practitioners in the field. Despite being a well-developed field, few studies have applied bibliometric analysis in the knowledge management literature. The study is more comprehensive in terms of the actors and methods involved in analyzing the scientific production of articles in the area of knowledge management.

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 reviews scholarly work in sustainable green logistics and remanufacturing (SGLR) and their subdisciplines, in combination with bibliometric, thematic and content analyses that provide a viewpoint on categorization and a future research agenda. This paper provides insight into current research trends in the subjects of interest by examining the most essential and most referenced articles promoting sustainability and climate-neutral logistics.

For the literature review, the authors extracted and sifted 2180 research and review papers for the period 2008–2023 from the Scopus database. The authors performed bibliometric and content analyses using multiple software programs such as Gephi, VOSviewer and R programming.

The SGLR papers can be grouped into seven clusters: (1) The circular economy facets; (2) Decarbonization of operations to nurture a climate-neutral business; (3) Green sustainable supply chain management; (4) Drivers and barriers of reverse logistics and the circular economy; (5) Business models for sustainable logistics and the circular economy; (6) Transportation problems in sustainable green logistics and (7) Digitalization of logistics and supply chain management.

In this review, fundamental ideas are established, research gaps are identified and multiple future research subjects are proposed. These propositions are categorized into three main research streams, i.e. (1) Digitalization of SGLR, (2) Enhancing scopes, sectors and industries in the context of SGLR and (3) Developing more efficient and effective climate-neutral and climate change-related solutions and promoting more environmental-related and sustainability research concerning SGLR. In addition, two conceptual models concerning SGLR and climate-neutral strategies are developed and presented for managers and practitioners to consider when adopting green and sustainability principles in supply chains. This review also highlights the need for academics to go beyond frameworks and build new techniques and instruments for monitoring SGLR performance in the real world.

This study provides an overview of the evolution of SGLR; it also clarifies concepts, environmental concerns and climate change practices, particularly those directed to supply chain management.

This paper aims to analyze the research highlights, evolutionary process and future research directions in the field of tourism forecasting.

This study used CiteSpace to conduct a bibliometric analysis of 1,213 tourism forecasting articles.

The results show that tourism forecasting research has experienced three stages. The institutional collaboration includes transnational collaboration and domestic institutional collaboration. Collaboration between countries still needs to be strengthened. The authors’ collaboration is mainly based on on-campus collaboration. Articles with high co-citation are primarily published in core tourism journals and other relevant publications. The research content mainly pertains to tourism demand, revenue management, hotel demand and tourist volumes. Ex ante forecasting during the COVID-19 pandemic has broadened existing tourism forecasting research. The future forecasting research focuses on the rational use of big data, improving the accuracy of models and enhancing the credibility of forecasting results.

This paper uses CiteSpace to analyze tourism forecasting articles to obtain future research trends, which supplements existing research and provides directions for future research.

本文旨在分析旅游预测领域的研究重点、演化过程和未来的研究方向。

本研究使用 CiteSpace 软件对 1213 篇旅游预测文章进行了文 献计量学分析。

结果表明, 旅游预测研究经历三个阶段。机构合作包含国际机构合作和 国内机构合作, 需要持续加强国家之间的合作, 作者之间的合作多以校内合作为 主。高引用文章不仅发表在旅游领域的核心期刊还发表在其他专业的核心期刊上。 旅游预测研究的主要内容为旅游需求、收入管理、酒店需求和游客量。新冠疫情 期间的事前预测拓宽了现有的旅游预测研究。未来预测的研究重点在于合理利用 大数据, 提高模型的准确定以及提高预测结果的可信度。

本文使用 CiteSpace 分析旅游预测文章得到未来研究趋势, 既是对 现有研究的补充, 又为今后的研究提供方向。

Este artículo pretende analizar los aspectos más destacados de la investigación, el proceso evolutivo y las futuras orientaciones de la investigación en el campo de la previsión turística.

Este estudio utilizó CiteSpace para realizar un análisis bibliométrico de 1213 artículos sobre previsión turística.

Los resultados muestran que la investigación sobre previsión turística ha experimentado tres etapas. La colaboración institucional incluye la colaboración transnacional y la colaboración institucional nacional. La colaboración entre países aún debe reforzarse. La colaboración entre autores se basa principalmente en la colaboración dentro del campus. Los artículos con una alta cocitación se publican principalmente en las principales revistas de turismo y en otras publicaciones relevantes. El contenido de la investigación se refiere principalmente a la demanda turística, el revenue management, la demanda hotelera y los volúmenes turísticos. La previsión previa y durante la pandemia de la COVID-19 ha ampliado la investigación existente sobre previsión turística. La futura investigación sobre previsiones se centra en el uso racional de los big data, la mejora de la precisión de los modelos y el aumento de la credibilidad de los resultados de las previsiones.

Este artículo utiliza CiteSpace para analizar artículos de previsión turística con el fin de obtener futuras tendencias de investigación, lo que complementa la investigación existente y proporciona orientaciones para futuras investigaciones.

This study uses a bibliometric approach to analyze the overall status of e-government research by revealing patterns and trends that would help gain a broad understanding of global developments in the field and future directions.

All documents related to e-government published from 2000 to 2019 were extracted from the Scopus and the Digital Government Reference Library databases. Bibexcel, Biblioshiny, and VOSviewer were used to perform the analyses and visualize the science mapping.

The results showed that 21,320 documents related to e-government research were published and cited 263,179 times. The annual growth rate of e-government research has reached 21.50%. The regression analysis showed that the growth rate is expected to increase gradually over the coming years. Despite the significant role that conference papers play in the e-government literature, the impact of articles far exceeds conference papers. The University of Albany (SUNY) has played an important role in e-government research in terms of production and impact. Furthermore, the study revealed some countries that are expected to play a prominent role in e-government research, as well as several topics that may attract more attention soon.

The results presented in this study and the comprehensive picture obtained about the e-government field make it an effective supplement to the expert evaluation. Thus, researchers, research managers, policymakers, institutions, funding agencies, and governments can rely on it.

This study aims to provide an insight into research related to Muslim travellers in the past 42 years.

Using 342 articles collected from the Scopus database from 1981 to 2023, this study adopted the Bibliometrix in RStudio package and Biblioshiny Web application to analyse the research on Muslim travellers in two main categories: overview and intellectual structures.

The first publication related to Muslim travellers occurred in 1981 and number of publications remained few in the first three decades. Starting 2015, publications on Muslim travellers experienced a growing development of discussions and publications. Four prominent research clusters were identified: “halal tourism”, “hajj”, “Islamic tourism” and “tourist post-purchase”. Themes within the research on Muslim travellers have evolved from the “pilgrimage” to “Islamic tourism” theme. Then, the “Islamic tourism” theme has been expanded to a variety of topics that were primarily relevant to Muslim tourist behaviour. Themes related to “climate change” and “Syria” have been identified as the niche themes that need further study.

Scopus database is regularly updated as the number of papers and journals may increase or decrease from time to time. This may impact on the fluctuation of the theme analysis from the article search at that time.

This study reviews publications related to Muslim travellers over the past four decades. Accordingly, it can aid interested researchers and stakeholders in gaining a more thorough understanding of Muslim traveller research.

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

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

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

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

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

The study aims to identify and discuss influential aspects of corporate environmental disclosure (CED) literature, including key streams, themes, authors, keywords, journals, affiliations and countries. This review also constructs agendas for future CED research.

Using a bibliometric review approach, the authors reviewed 560 articles on CED from 215 journals published between 1982 and 2020.

The authors' insights are three-fold. First, the authors identified three core streams of CED research: “legitimization of environmental hazards via environmental disclosures,” “the role of environmental accounting in achieving corporate environmental sustainability” and “integrating environmental social and governance (ESG) reporting into the global reporting initiatives (GRI) guidelines”. Second, the authors also deployed a thematic map that classifies CED research into four themes: niche themes (e.g. institutional theory and environmental management system), motor themes (e.g. stakeholder engagement), emerging/declining themes (e.g. legitimacy theory) and basic/transversal themes (e.g. voluntary CED, environmental reporting and corporate social responsibility). Third, the authors highlighted important CED authors, keywords, journals, articles, affiliations and countries.

This study assists researchers, journal editors and consultants in the corporate sector to comprehensively understand various dimensions of CED research and practices and suggests potential emerging research areas. Although this paper appears to have been thoroughly conducted, using authors' keywords to identify themes was a key limitation. Thus, the authors call upon using a more comprehensive data mining technique that uses keywords in abstracts, titles and the whole body of papers and then identifies inclusive trends in CED literature.

The authors contribute to the extant accounting literature by investigating the organizational-level CED, both mandatory and voluntary, using a systematic and bibliometric literature review model to summarize the key research streams, themes, authors, journals, affiliations and countries. By doing so, the authors construct a future research agenda for CED literature.

This paper aims to systematically analyse the publications in the field of integrated reporting (IR) and to present an overview of the current publication trends in IR based on the data obtained from the Scopus database.

Selected bibliometric indicators and bibliometrix R-packages are used in examining metrics like annual publication trends, authors with the most produced work, papers that are often cited, top productive countries, top productive affiliations, frequently mentioned journals, frequently mentioned keywords, analysis of co-citation, analysis of collaboration and analysis of co-word.

The findings from the bibliometric review indicated that the trend of IR literature had increased from 2017 to 2020, specifically from 2017 to 2019. The findings also indicated that several publications on IR entailed several authors’ collaboration and were published in various languages. Moreover, around 148 institution-affiliated researchers from 40 institutions in 20 countries contributed to the IR publication.

This paper offers a comprehensive overview of the current development in IR. It is useful to help emerging scholars identify and understand current trends in IR based on different countries, authors and languages.

This paper contributes to the literature on IR by highlighting the trends of IR publications from the Scopus database using bibliometric analysis.