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This study aims to synthesize extant literature on the concept of reverse knowledge transfer (RKT) built up over the past two decades with the help of bibliometric analyssis and also to suggest promising new areas for research in this field.

The study adopts a literature review methodology combined with bibliometric and network analysis based on 117 papers identified from the Scopus database. In particular, this study has tried to identify and capture themes not previously fully captured or evaluated by other reviews on this topic.

The authors have identified research themes and research gaps in the area of RKT. Overall, the review shows the main outlets that have published papers on RKT and the theoretical background this research is built on. This study exhibits core themes in this area that have persisted and grown consistently such as the subsidiary’s role in RKT. In addition, the review highlights less researched themes such as role of boundary spanning in RKT, which open exciting avenues for new research opportunities.

This study finds that RKT research has experienced remarkable growth from a complete viewpoint in recent years. There was a surge in publications in the area from 2008 onwards, and many of its influential papers seemed to have been published between 2013 and 2018. Prominent themes in this body of research have been identified and potential for future studies has been explored.

To the best of the authors’ knowledge, this is the first study to map, synthesize and discuss the literature concerning RKT.

Equity, diversity, inclusion and accessibility (EDIA) are the core values of librarianship. This study aims to examine the EDIA literature in the library and information science (LIS) profession, focusing on publishing trends, authorship patterns, thematic evolution, co-occurrence network, international collaboration network and three-factor analysis.

A scientometrics analysis was performed, and data were retrieved from the Web of Science database following a four-phase data extraction and filtration process. Data analysis was performed using specialized scientometrics tools.

Most of the published work comes from the developed world. The thematic evolution identified that the initial period (1971–2010) was dedicated to the diversity of library resources, services and users. The second phase (2011–2015) concentrated on accessibility and information literacy. The recent period (2016–2021) is linked with social inclusion, diversity and accessibility. Furthermore, the co-cluster citation and content analysis identified five major interconnected streams in the EDIA literature in LIS: disability and accessibility; diversity, inclusion and recruitment; social justice and libraries; libraries and immigrants; and libraries and the lesbian, gay, bisexual, transgendered, queer community.

Theoretical, practical and implications for policy makers and curriculum developers were added to create awareness and better observe EDIA in LIS field.

The identification of research streams is one of the most important findings of this study, which shows that some areas of EDIA are maturing and others are emerging in the profession.

The development of project managers and leadership has been highlighted as crucial for improving project success and performance, resulting in a rise of interest in project leadership research over the last two decades. While several qualitative reviews have been conducted, there have been limited quantitative and systematic reviews on project leadership. This study fills this gap by portraying the knowledge landscape and tracking the evolution of project leadership research from 1998 to 2022 through bibliometric approaches.

Based on 816 records, including 793 articles extracted and selected from the Web of Science database and specific journals, and 23 articles selected from three non-SCI/SSCI indexed journals, the authors used CiteSpace and bibliometrix R-package to depict visualizations of the trajectory of co-cited references, the landscape of co-occurred keywords and emerging trends in project leadership via reference co-citation analysis, keyword co-occurrence analysis and thematic mapping.

The bibliometric analyses enabled the authors to understand the conceptual aspects of project leadership and its theoretical background. Three stages of the intellectual bases were identified and tracked: the infancy phase (1998–2007), the growth phase (2008–2014) and the new development phase (2015–2022). The results of keyword co-occurrence analysis indicated that the research focus evolved from investigating traits and competences to examining the effects of traditional leadership behaviors, and then considering context-specific leadership. The findings of thematic mapping and theoretical interpretation illustrate the potential directions of the competence comparison, new and appropriate leadership, and the interaction between leadership and context.

This study advanced the field by providing a systematic review of project leadership, developing potential future directions for project leadership research and providing practical implications for career development and training.

Artificial intelligence (AI) is increasingly applied by businesses to optimize their processes and decision-making, develop effective and efficient strategies, and positively influence customer behaviors. Businesses use AI to generate behaviors such as customer retention (CR). The existing literature on “AI and CR” is vastly scattered. The paper aims to review the present research on AI in CR systematically and suggest future research directions to further develop the field.

The Scopus database is used to collect the data for systematic review and bibliometric analysis using the VOSviewer tool. The paper performs the following analysis: (1) year-wise publications and citations, (2) co-authorship analysis of authors, countries, and affiliations, (3) citation analysis of articles and journals, (4) co-occurrence visualization of binding terms, and (5) bibliographic coupling of articles.

Five research themes are identified, namely, (1) AI and customer churn prediction in CR, (2) AI and customer service experience in CR, (3) AI and customer sentiment analysis in CR, (4) AI and customer (big data) analytics in CR, and (5) AI privacy and ethical concerns in CR. Based on the research themes, fifteen future research objectives and a future research framework are suggested.

The paper has important implications for researchers and managers as it reveals vital insights into the latest trends and paths in AI-CR research and practices. It focuses on privacy and ethical issues of AI; hence, it will help the government develop policies for sustainable AI adoption for CR.

To the author's best knowledge, this paper is the first attempt to comprehensively review the existing research on “AI and CR” using bibliometric analysis.

Given the magnitude of the literature, a researcher must be selective of research papers and publications in general. In other words, only papers that meet strict standards of academic integrity and adhere to reliable and credible sources should be referenced. The purpose of this paper is to approach this issue from the prism of scientometrics according to the following research questions: Is it necessary to judge the quality of scientific production? How do we evaluate scientific production? What are the tools to be used in evaluation?

This paper presents a comparative study of scientometric evaluation practices and tools. A systematic literature review is conducted based on articles published in the field of scientometrics between 1951 and 2022. To analyze data, the authors performed three different aspects of analysis: usage analysis based on classification and comparison between the different scientific evaluation practices, type and level analysis based on classifying different scientometric indicators according to their types and application levels and similarity analysis based on studying the correlation between different quantitative metrics to identify similarity between them.

This comparative study leads to classify different scientific evaluation practices into externalist and internalist approaches. The authors categorized the different quantitative metrics according to their types (impact, production and composite indicators), their levels of application (micro, meso and macro) and their use (internalist and externalist). Moreover, the similarity analysis has revealed a high correlation between several scientometric indicators such as author h-index, author publications, citations and journal citations.

The interest in this study lies deeply in identifying the strengths and weaknesses of research groups and guides their actions. This evaluation contributes to the advancement of scientific research and to the motivation of researchers. Moreover, this paper can be applied as a complete in-depth guide to help new researchers select appropriate measurements to evaluate scientific production. The selection of evaluation measures is made according to their types, usage and levels of application. Furthermore, our analysis shows the similarity between the different indicators which can limit the overuse of similar measures.

This paper aims to present a summary of the green consumer behaviour (GCB) research conducted during the 2001–2021 period using the bibliometric analysis and to carry out a thematic and content analysis on the three clusters which comprise 57 articles resulting from the co-citation analysis and identify the significant green purchasing factors.

The three-pronged methodology applied to this research analysis includes performance analysis of the literature using biblioshiny and R Studio; network mapping analysis using VOSviewer and Gephi; thematic analysis using word clouds generated with R Software and content analysis of each paper with the aid of within and between-study analyses.

Cluster one acted as a base for the theoretical foundations of GCB which aids in understanding the basic concepts of green marketing, its evolution and the methodologies, whereas cluster two determined the predictors of everyday green behaviour, which helps in gaining knowledge about the everyday sustainable activities the consumers indulge and the factors motivating to do so. Cluster three mainly focused on the psycho-socio demographic determinants of GCB, which assists in segmentation and predicting the purchase behaviour of the various consumer segments.

The significant variables and major gaps in each of the clusters were identified and authors have drawn the implications for future researchers and marketing managers.

This paper aims to explore the effect of teacher–student collaboration on academic innovation in universities in different stages of collaboration.

Based on collaboration life cycle, this paper divided teacher–student collaboration into initial, growth and mature stages to explore how teacher–student collaboration affects academic innovation.

Collecting data from National Science Foundation of China, the empirical analysis found that collaboration increases the publication of local (Chinese) papers at all stages. However, teacher–student collaboration did not significantly improve the publication of international (English) papers in the initial stage. In the growth stage, teacher–student collaboration has a U-shaped effect on publishing English papers, while its relationship is positive in the mature stage.

The results offer suggestions for teachers and students to choose suitable partners and also provide some implications for improving academic innovation.

This paper constructed a model in which the effect of teacher–student collaboration on academic innovation in universities was established.

This study aims to provide a more complete picture of blockchain development by combining numerous methodologies with diverse data sources, such as academic papers and news articles. This study displays the developmental status of each subject based on the interrelationships of each topic cluster by analyzing high-frequency keywords extracted from the collected data. Moreover, applying above methodologies will help understanding top research topics, authors, venues, institutes and countries. The differences of blockchain research and new are identified.

To identify and find blockchain development linkages, researchers have used search terms such as co-occurrence, bibliographic coupling, co-citation and co-authorship to help us understand the top research topics, authors, venues, institutes and countries. This study also used text mining analysis to identify blockchain articles' primary concepts and semantic structures.

The findings show the fundamental topics based on each topic cluster's links. While “technology”, “transaction”, “privacy and security”, “environment” and “consensus” were most strongly associated with blockchain in research, “platform”, “big data and cloud”, “network”, “healthcare and business” and “authentication” were closely tied to blockchain news. This article classifies blockchain principles into five patterns: hardware and infrastructure, data, networking, applications and consensus. These statistics helped the authors comprehend the top research topics, authors, venues, publication institutes and countries.

Since Web of Science (WoS) and LexisNexis Academic data are used, the study has few sources. Others advise merging foreign datasets. WoS is one of the world's largest and most-used databases for assessing scientific papers.

This study has several uses and benefits. First, key concept discoveries can help academics understand blockchain research trends so they can prioritize research initiatives. Second, bibliographic coupling links academic papers on blockchain. It helps information seekers search and classify the material. Co-citation analysis results can help researchers identify potential partners and leaders in their field. The network's key organizations or countries should be proactive in discovering, proposing and creating new relationships with other organizations or countries, especially those from the journal network's border, to make the overall network more integrated and linked. Prominent members help recruit new authors to organizations or countries and link them to the co-authorship network. This study also used concept-linking analysis to identify blockchain articles' primary concepts and semantic structures. This may lead to new authors developing research ideas or subjects in primary disciplines of inquiry.

Previous research has explored the link between sustainability disclosure and reputation but produced contradictory results. This study aims to clarify the sustainability disclosure–reputation relationship through a quantitative analysis of the correlations between these variables reported in empirical research papers. The second objective was to determine how various moderators affect the sustainability disclosure–reputation link.

The meta-analysis was based on a systematic review of the literature covering empirical research on the corporate sustainability disclosure and reputation relationship. A total of 92 articles were meta-analyzed to compile their findings on four extrinsic moderators: company size, ownership, stock listing status and activity sector.

The findings confirm that a significant positive correlation exists between corporate sustainability disclosure and reputation. The moderator analysis also revealed that companies’ different characteristics can explain researchers’ divergent results.

The results have considerable practical relevance for organizational management. First, they can motivate managers to improve and disclose their company’s social and environmental impacts to strengthen their reputation, which in turn will help accelerate the achievement of the Sustainable Development Goals. Second, the findings can ensure organizations develop disclosure and reputation management strategies adapted for each firm’s size, ownership, stock listing status and activity sector.

The results have considerable practical relevance for organizational management. First, they can motivate managers to improve and disclose their company’s social and environmental impacts to strengthen their reputation, which in turn will help accelerate the achievement of the Sustainable Development Goals. Second, the findings can ensure organizations develop disclosure and reputation management strategies adapted for each firm’s size, ownership, stock listing status and activity sector.

To the best of the authors’ knowledge, this meta-analysis is the first to clarify the link between disclosure and reputation, which makes a unique contribution to the field of social and environmental accounting. A larger sample of primary research was collected, and key extrinsic moderators were examined to explain prior studies’ contradictory findings.

The purpose of this study is to examine and identify the predominant themes in the literature on economic freedom. The paper also highlights the key journals, leading authors, top countries and organisations in the literature on economic freedom.

This paper uses the Scopus database to examine 1,512 articles covering the disciplines of economics, finance, business and social sciences from 1942 to 2022. Vosviewer software is used for creating bibliometric networks.

The findings suggest that significant growth in the economic freedom literature has occurred in the last ten years. Considerable attention has been devoted to examining the relationship between economic freedom and growth. The paper also finds that most of the research on economic freedom has been undertaken in the context of developed countries.

This study is one of the first attempts to undertake a bibliometric analysis of economic freedom. The article also highlights the less-researched areas in the literature and thus provides directions for future research.

The peer review history for this article is available at: https://publons.com/publon/10.1108/IJSE-09-2023-0690.