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The evolution from emerging technologies to smart libraries is thoroughly analyzed thematically and bibliometrically in this research study, spanning 2013 through 2022. Finding and analyzing the significant changes, patterns and trends in the subject as they are represented in academic papers is the goal of this research.

Using bibliometric methodologies, this study gathered and examined a large corpus of research papers, conference papers and related material from several academic databases.

Starting with Artificial Intelligence (AI), the Internet of Things (IoT), Big Data (BD), Augmentation Reality/Virtual Reality and Blockchain Technology (BT), the study discusses the advent of new technologies and their effects on libraries. Using bibliometric analysis, this study looks at the evolution of publications over time, the geographic distribution of research and the most active institutions and writers in the area. A thematic analysis is also carried out to pinpoint the critical areas of study and trends in emerging technologies and smart libraries. Some emerging themes are information retrieval, personalized recommendations, intelligent data analytics, connected library spaces, real-time information access, augmented reality/virtual reality applications in libraries and strategies, digital literacy and inclusivity.

This study offers a thorough overview of the research environment by combining bibliometric and thematic analysis, illustrating the development of theories and concepts during the last ten years. The results of this study helps in understanding the trends and future research directions in emerging technologies and smart libraries. This study is an excellent source of information for academics, practitioners and policymakers involved in developing and applying cutting-edge technology in library environments.

This paper employs bibliometric analysis to explore transformative trends and emerging research patterns in the intersection of digital technology and tourism. The goal is to provide insights into the evolving landscape, identify key themes, influential authors and prominent journals, contributing to a nuanced understanding of this dynamic field.

This study rigorously employs bibliometric analysis from 2002 to 2023, using Scopus and Web of Science databases, yielding 2,040 Scopus and 1,389 Web of Science documents. After meticulous data selection, 575 articles were refined. Utilising VOSviewer and Biblioshiny, the analyses focus on publication trends, citations, authorship, collaborations and thematic clusters, addressing four research questions.

This bibliometric analysis reveals a significant growth in annual scientific production on digital technology and tourism, peaking at 100 articles in 2023. Key contributors include LAW R., CHUNG N. and KOO C. China leads in research output, and influential journals include “Current Issues in Tourism” and “Information Technology and Tourism.” Noteworthy trends emphasise the centrality of “smart tourism” and the interconnectedness of technology, hospitality and management in shaping future research directions.

Stakeholders should focus on integrating emerging technologies in tourism, emphasising areas with high research activity. Professionals must stay updated on evolving trends, adopt innovative digital solutions and collaborate to navigate the dynamic landscape.

This study pioneers the first bibliometric analysis on digital technology in the tourism industry, providing a unique and comprehensive exploration of the scholarly landscape from 1998 to 2023, shedding light on key contributors, influential journals and emerging trends.

In response to the growing interest in Internet of Things (IoT) technology and its profound implications for businesses and individuals, this bibliometric study focuses on a critical yet understudied aspect, i.e. cybersecurity. As IoT adoption grows, so do concerns regarding user privacy and data security. This study aims to provide a comprehensive understanding of the current research in this vital area, shedding light on research trends, gaps and emerging themes.

The study conducted a bibliometric analysis and systematic review of literature spanning over two decades (2013–2023). Bibliometric analysis is conducted using Biblioshiny which is R-software-based advanced analytical tool. Further, VOSviewer is used to conduct network analysis. The study highlights the evolving landscape of IoT cybersecurity, emphasizing interdisciplinary intersections and the ethical dimensions of IoT technologies.

The study uncovers crucial concerns related to IoT adoption, emphasizing the urgent need for comprehensive cybersecurity protocols. It identifies emerging themes such as artificial intelligence and blockchain integration, indicating a shift toward interdisciplinary solutions. Furthermore, the research highlights ethical gaps in current IoT discussions, emphasizing the importance of responsible innovation.

Businesses can bolster their cybersecurity strategies, policymakers can craft informed regulations and researchers are encouraged to explore IoT’s ethical dimensions.

This study pioneers a nuanced analysis of IoT cybersecurity, filling a crucial gap in the existing business and management literature. By synthesizing a decade of scholarly work, it provides foundational insights for researchers, businesses and policymakers. The research not only informs academic discourse but also offers practical guidance for enhancing IoT security measures and fostering ethical innovation.

The study aims to analyze the synergy of artificial intelligence (AI), with scientometrics, webometrics and bibliometrics to unlock and to emphasize the potential of the applications and benefits of AI algorithms in these fields.

By conducting a systematic literature review, our aim is to explore the potential of AI in revolutionizing the methods used to measure and analyze scholarly communication, identify emerging research trends and evaluate the impact of scientific publications. To achieve this, we implemented a comprehensive search strategy across reputable databases such as ProQuest, IEEE Explore, EBSCO, Web of Science and Scopus. Our search encompassed articles published from January 1, 2000, to September 2022, resulting in a thorough review of 61 relevant articles.

(1) Regarding scientometrics, the application of AI yields various distinct advantages, such as conducting analyses of publications, citations, research impact prediction, collaboration, research trend analysis and knowledge mapping, in a more objective and reliable framework. (2) In terms of webometrics, AI algorithms are able to enhance web crawling and data collection, web link analysis, web content analysis, social media analysis, web impact analysis and recommender systems. (3) Moreover, automation of data collection, analysis of citations, disambiguation of authors, analysis of co-authorship networks, assessment of research impact, text mining and recommender systems are considered as the potential of AI integration in the field of bibliometrics.

This study covers the particularly new benefits and potential of AI-enhanced scientometrics, webometrics and bibliometrics to highlight the significant prospects of the synergy of this integration through AI.

This study evaluates the knowledge structure of building information modeling (BIM) in green buildings. Buildings are one of the main contributors to carbon emissions, and implementing BIM in green buildings is seen as an indispensable approach to mitigate environmental and climate change issues.

Through a bibliometric analysis, 297 publications retrieved from the Web of Science (WoS) were analyzed to explore their intellectual structure.

Bibliographic coupling analysis produced four clusters on current and emerging trends, while co-word analysis produced four clusters on future BIM and green building trends. Current and emerging trends revolve around BIM adoption in green and existing buildings, life cycle analysis (LCA) and sustainable rating tools. Future trends related to BIM and performance analysis and optimization, the BIM framework for green building design and construction, overcoming barriers and maximizing benefits in BIM adoption.

The implications of this study are relevant to all BIM and green building stakeholders, including developers, engineers, architects, occupants, tenants and the whole community.

This study examines the crucial integration of BIM and green building within the more extensive construction and building field scope.

This paper aims to understand the main challenges connected with accountability issues across multiple layers of the metaverse, to identify whether and how any techwashing is taking place and to discuss implications for accounting research.

To develop the research, the authors refer to a critical dialogic accountability framework, operationalized in the current paper by leveraging the perspectives of accountability as virtues and as mechanisms (Bovens, 2010). The authors discuss who is accountable to whom, for what and in what manner in a relatively unregulated and unaccountable world, through the layers of virtual reality introduced by MacKenzie et al. (2013) and Llewellyn (2007). Methodologically, the study concentrates on 32 start-ups working in the metaverse selected from the Crunchbase database and relies on interviews, direct observation in the field and white paper reports analyzed by means of NVivo coding.

The findings show how metaverse creators deal with accountability as a virtue and accountability as a mechanism. Companies who operate metaverses primarily consider accountability in the virtual-physical domain, which focuses on developing the necessary internal and external architecture to enable a particular metaverse to function. Metaverse companies also emphasize the virtual-agential dimension that concentrates on onboarding, engaging with and incentivizing individuals in virtual worlds. There is an emphasis on outlining the virtues or standards that metaverse companies aspire to, but there is very little detail provided. Similarly, there are uneven and limited discussions of the mechanisms that can support accountability in most layers of a virtual world.

The analysis raises significant questions about the purpose, scope and use of metaverses, which are still a relatively unregulated and unaccountable world. The paper advances the idea that the current creators of metaverses are “techwashing” their projects, providing a utopian ideal of what their universes will look like but obfuscating the realities of their ventures in tech jargon that few people are likely to understand. Therefore, meaning and truth at all levels of the real and virtual worlds remain unaddressed, with implications to be explored in terms of legitimacy and trust of metaverses and the interests that shape them.

This paper is one of the first to address the issue of accountability in metaverses. It advances an analytical framework to guide future accounting and accountability research into virtual worlds.

The global emphasis on sustainability is driving organizations to embrace financial technology (Fintech) solutions as a means of enhancing their sustainable performance. This study seeks to unveil the intermediary role played by green finance and competitiveness, along with the moderating impact of digital transformation (DT), in the intricate relationship between Fintech adoption and sustainable performance.

Drawing on existing literature, we construct a comprehensive conceptual framework to thoroughly analyse these interconnected variables. To empirical validate of our model, a dual structural equation modelling–artificial neural network) SEM–ANN approach was employed, adding a robust layer of validation to our study’s proposed framework. A sample of 438 banking employees in Pakistan was collected using a simple random sampling technique, with 411 samples deemed suitable for subsequent analysis. Initially, data scrutiny and hypothesis testing were carried out using Smart-PLS 4.0 and SPSS-23. Subsequently, the ANN technique was utilized to assess the importance of exogenous factors in forecasting endogenous factors.

The findings from this research underscore the direct and significant influence of Fintech adoption and DT on the sustainable performance of banks. Notably, green finance and competitiveness emerge as pivotal mediators, bridging the gap between Fintech adoption and sustainable performance. Moreover, DT emerges as a critical moderator, shaping the relationships between Fintech adoption and both green finance and competitiveness. The integration of the ANN approach enhances the SEM analysis, providing deeper insights and a more comprehensive understanding of the subject matter.

This study contributes to the enhanced comprehension of Fintech, green finance, competitiveness, DT and the sustainable performance of banks. Recognizing the importance of amalgamating Fintech adoption, green finance and transformational leadership becomes essential for elevating the sustainable performance of banks. The insights garnered from this study hold valuable implications for policymakers, practitioners and scholars aiming to enhance the sustainable performance of banks within the competitive business landscape.

Emotional labour (EL) is a complex phenomenon that has received increasing attention in recent years due to its impact on employee’s well-being and job satisfaction. For a comprehensive understanding of the evolving field of EL, it is important to extract different research trends, new developments and research directions in this domain. The study aims to reveal 13 prominent research topics based on the topic modelling analysis.

Using latent Dirichlet allocation (LDA) method, topic modelling is done on 1,462 journal research papers published between 1999 and 2023, extracted from the Scopus database using the keyword “EL”.

The analysis identifies several emerging trends in EL research, including emotional regulation training and job redesign. Similarly, the topics like EL strategies, cultural differences and EL, EL in hospitality, organizational support and EL, EL and gender and psychological well-being of nursing workers are popular research topics in this domain.

The findings provide valuable insights into the current state of EL research and can provide a direction for future research as well as assist organizations to design practices aimed at improving working conditions for employees in various industries.

Topic modelling on emotional labor is done. The paper identifies specific topics or clusters related to emotional labor, quantifies these topics using topic modeling, adds empirical rigor, and allows for comparisons across different contexts.

The increasing urgency to address climate change in construction has made green construction (GC) and sustainability critical topics for academia and industry professionals. However, the volume of literature in this field has made it impractical to rely solely on traditional systematic evidence mapping methodologies.

This study employs machine learning (ML) techniques to analyze the extensive evidence-base on GC. Using both supervised and unsupervised ML, 5,462 relevant papers were filtered from 10,739 studies published from 2010 to 2022, retrieved from the Scopus and Web of Science databases.

Key themes in GC encompass green building materials, construction techniques, assessment methodologies and management practices. GC assessment and techniques were prominent, while management requires more research. The results from prevalence of topics and heatmaps revealed important patterns and interconnections, emphasizing the prominent role of materials as major contributors to the construction sector. Consistency of the results with VOSviewer analysis further validated the findings, demonstrating the robustness of the review approach.

Unlike other reviews focusing only on specific aspects of GC, use of ML techniques to review a large pool of literature provided a holistic understanding of the research landscape. It sets a precedent by demonstrating the effectiveness of ML techniques in addressing the challenge of analyzing a large body of literature. By showcasing the connections between various facets of GC and identifying research gaps, this research aids in guiding future initiatives in the field.

Following the recent rise in generative artificial intelligence (GenAI) tools, fundamental questions about their wider impacts have started to reverberate around various disciplines. This study aims to track the unfolding landscape of general issues surrounding GenAI tools and to elucidate the specific opportunities and limitations of these tools as part of the technology-assisted enhancement of mechanical engineering education and professional practices.

As part of the investigation, the authors conduct and present a brief scientometric analysis of recently published studies to unravel the emerging trend on the subject matter. Furthermore, experimentation was done with selected GenAI tools (Bard, ChatGPT, DALL.E and 3DGPT) for mechanical engineering-related tasks.

The study identified several pedagogical and professional opportunities and guidelines for deploying GenAI tools in mechanical engineering. Besides, the study highlights some pitfalls of GenAI tools for analytical reasoning tasks (e.g., subtle errors in computation involving unit conversions) and sketching/image generation tasks (e.g., poor demonstration of symmetry).

To the best of the authors’ knowledge, this study presents the first thorough assessment of the potential of GenAI from the lens of the mechanical engineering field. Combining scientometric analysis, experimentation and pedagogical insights, the study provides a unique focus on the implications of GenAI tools for material selection/discovery in product design, manufacturing troubleshooting, technical documentation and product positioning, among others.