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The purpose of this paper is to measure the relationship of technology acceptance model (TAM) variables (PEOU and PU) with behavioral intention (BI) and attitude in mobile and digital libraries context. This study also examines the relationship of external variables (information quality and system quality) with TAM variables (PEOU and PU) in mobile and digital libraries context.

This meta-analysis was performed through PRISMA-P guidelines. Four databases (Google Scholar, Web of Science, Scopus and LISTA) were used for searching, and the search was conducted according to defined criteria.

Findings of this study revealed a large effect size of PU and PEOU with BI. There was also a large effect size of PU and PEOU with attitude. A medium effect size was found between SysQ → PU, InfoQ → PU and SysQ → PEOU. However, there was a small effect size between InfoQ and PEOU.

To the best of the authors’ knowledge, there was no study published till the time of conducting this meta-analysis. Hence, this study fills the literature gap. This study also confirms that TAM is a valid model in the acceptance and use of technology in mobile and digital libraries context. Thus, the findings of the present study are helpful for developers and designers in designing and developing mobile library apps. It will also be beneficial for library authorities and system librarians in designing and developing digital libraries in academic settings.

Although the challenges associated with big data are increasing, the question of the most suitable big data analytics (BDA) platform in libraries is always significant. The purpose of this study is to propose a solution to this problem.

The current study identifies relevant literature and provides a review of big data adoption in libraries. It also presents a step-by-step guide for the development of a BDA platform using the Apache Hadoop Ecosystem. To test the system, an analysis of library big data using Apache Pig, which is a tool from the Apache Hadoop Ecosystem, was performed. It establishes the effectiveness of Apache Hadoop Ecosystem as a powerful BDA solution in libraries.

It can be inferred from the literature that libraries and librarians have not taken the possibility of big data services in libraries very seriously. Also, the literature suggests that there is no significant effort made to establish any BDA architecture in libraries. This study establishes the Apache Hadoop Ecosystem as a possible solution for delivering BDA services in libraries.

The present work suggests adapting the idea of providing various big data services in a library by developing a BDA platform, for instance, providing assistance to the researchers in understanding the big data, cleaning and curation of big data by skilled and experienced data managers and providing the infrastructural support to store, process, manage, analyze and visualize the big data.

The study concludes that Apache Hadoops’ Hadoop Distributed File System and MapReduce components significantly reduce the complexities of big data storage and processing, respectively, and Apache Pig, using Pig Latin scripting language, is very efficient in processing big data and responding to queries with a quick response time.

According to the study, there are significantly fewer efforts made to analyze big data from libraries. Furthermore, it has been discovered that acceptance of the Apache Hadoop Ecosystem as a solution to big data problems in libraries are not widely discussed in the literature, although Apache Hadoop is regarded as one of the best frameworks for big data handling.

This paper aims to focus on academic library managers’ learning practices in the context of cooperative work supported by computational artefacts. Academic library managers’ everyday work is mainly cooperative. Their cooperation is supported predominantly by computational artefacts. Learning how to use the computational artefacts efficiently and effectively involves understanding the changes in everyday work that affect managers and, therefore, it requires deep understanding of their cooperative work practices.

Focused ethnography was conducted through participant observations, interviews and document analysis. Ten managers from a university library in Sweden participated in the research. A thematic method was used to analyse the empirical material. Computer supported cooperative work (CSCW) and work-integrated learning was used as the conceptual lens.

Five learning practices were identified: collaboration, communication, coordination, decision-making processes and computational artefacts’ use. The findings show that learning is embedded in managers’ cooperative work practices, which do not necessarily include sufficient training time. Furthermore, learning was intertwined with cooperating and was situational. Managers learned by reflecting together on their own experiences and through joint cooperation and information sharing while using the computational artefacts.

The main contribution lies in providing insights into how academic library managers learn and cooperate in their everyday work, emphasizing the role of computational artefacts, the importance of the work context and the collective nature of learning. It also highlights the need for continual workplace learning in contemporary knowledge work environments. Thus, the research generates contributions to the informatics field by extending the understanding of managers’ work-integrated learning in their everyday cooperative work practices supported by computational artefacts’ use. It also contributes to the intersection of CSCW and work-integrated learning.

This study aimed to predict and understand the academic libraries' probability of successful adoption of blockchain within the lens of integrated technology acceptance model (TAM) and technology organization and environment theory (TOE) framework.

A mixed approach was employed to gather data from librarians (292) and system analysts (46) totaling 338 respondents. The total enumeration sampling technique was considered. Qualitative data were analyzed thematically, while quantitative data were analyzed using structural equation model (SEM).

Perceived usefulness and policy are the important factors that influence academic libraries' blockchain adoption intentions. Unlimited access to both print and electronic resources, security of users' information and easy collaboration between users and library staff were found to be the benefits of blockchain application to academic libraries' operations. Major challenges to the adoption of blockchain in academic libraries include the cost of infrastructure related to blockchain applications, privacy issues and a lack of understanding of blockchain technology among librarians.

Future studies would need to include more relevant items to the observed variables of the independent variables that were found insignificant in this study.

The findings of this study will create a roadmap for government and polytechnic management on the factors that could strengthen the adoption of blockchain in the libraries.

The outcome of this study came at a crucial moment when the majority of academic libraries in developing nations like Nigeria were skeptical about the deployment of blockchain technology in their libraries.

The study identified new factors that influence blockchain adoption intention.

The purpose of this study is to examine approaches used by university libraries to enhance the visibility and utilization of research support services (RSSs) among doctoral students and to assess the competencies of library staff in delivering research support services.

This study used qualitative design approach, purposively sampled 40 librarians (8 university librarians and 32 librarians) in charge of RSSs and use of structured interview.

The findings of this study revealed three major themes: offline and online strategies, the need for upskilling and professional development programs and proactive empowerment.

This study focused on research support services in chartered public universities in Kenya; private universities were not included.

The need to enhance library staff's ongoing professional development programs, increasing funding to university libraries and proactivity by the libraries to improve the provision and promotion of RSSs to doctoral students in Kenya.

There are limited existing literature in the Kenyan context. This study will fill a knowledge gap and contribute to the literature on academic libraries support and doctoral students experience in Kenyan context.

This study aims to explore how libraries in the United Arab Emirates use technology to preserve and digitize cultural and historical documents. It examined how these institutions use different technology models to facilitate the dissemination of UAE’s cultural traditions, practices, historical experiences and expressions to the local and global populations interested in learning about the country.

This study relied heavily on a review of the relevant literature and case studies covering how UAE libraries use technology to preserve, document and share tangible and intangible cultural heritage. The methodology entailed gathering and synthesizing relevant information from scholarly journal articles, government and reputable institutional resources online and reports. Collectively, it led to a close analysis of the impact of technology on cultural preservation and an assessment of the specific technology models preferred for optimal outcomes in preserving and disseminating cultural heritage information of the UAE.

Multiple UAE libraries rely heavily on technology to collect, record, translate and store cultural heritage information, including releasing it to users when required. The National Archives of the United Arab Emirates, the Arabian Gulf Digital Archive, Mohammed Bin Rashid Library, the UAE National Library and Archives, New York University Abu Dhabi and Khalifa University of Science and Technology and Research libraries have leveraged different technological models and tools to make UAE’s cultural heritage information available and accessible globally. Artificial intelligence and machine learning algorithms, three-dimensional imaging and scanning, electronic archiving systems, document management systems and ICT storage systems have helped the UAE libraries to promote and disseminate the nation’s tangible and intangible cultural heritage.

By relying on scholarly and authoritative sources of information and evidence to draw conclusions, this study contributes to the existing literature by offering insights into the innovative strategies used by UAE libraries to leverage technology for cultural preservation and promotion. In underlining the value of digital approaches to safeguard tangible and intangible cultural heritage, the research highlights the instrumentalism of technology in preserving the UAE’s cultural heritage and identity.

As a part of doctoral study, this study aims to analyze research on library management models (LMMs) by conducting a systematic literature review (SLR).

A Preferred Reporting Items for Systematic Review and Mata-Analysis approach was used to search four databases. The search criteria included studies published in English until 2022, resulting 9,125 records. Out of these records, a total of 36 studies were selected for final analysis

The results show a positive attitude among researchers toward the development of LMM for libraries globally. The results depict that more than one-third (39%) of the target population was comprised of academic staff and students. The majority (91.76%) of studies were conducted using survey. Quantitative methods were predominant (89%) for LMMs. There were a significant number of studies conducted in 2016. The country-wise distribution shows the USA and China each contribute (20%) of the studies.

The findings of this research could assist policymakers and authorities in reconciling the LMMs applied in libraries for providing efficient access to information resources and services to end users.

To the best of the authors’ knowledge, this study is unique as no comprehensive study has been conducted on LMMs using the SLR method.

This study aims to examine Big Data and the management of libraries in the era of the Fourth Industrial Revolution and its implications for policymakers in Nigeria.

A qualitative methodology was used, involving the administration of open-ended questionnaires to librarians from six selected federal universities located in Southwest Nigeria.

The findings of this research highlight that a significant proportion of librarians are well-acquainted with the relevance of big data and its potential to positively revolutionize library services. Librarians generally express favorable opinions concerning the relevance of big data, acknowledging its capacity to enhance decision-making, optimize services and deliver personalized user experiences.

This study exclusively focuses on the Nigerian context, overlooking insights from other African countries. As a result, it may not be possible to generalize the study’s findings to the broader African library community.

To the best of the authors’ knowledge, this study is unique because the paper reported that librarians generally express favorable opinions concerning the relevance of big data, acknowledging its capacity to enhance decision-making, optimize services and deliver personalized user experiences.

The objectives of the study were to identify the effects of blockchain technology (BT) on the university librarians, the impact of BT on the university library services and to reveal the challenges to adopt BT in the university libraries.

A systematic literature review was applied to address the objectives of the study. Around 25 studies published in peer-reviewed journals were selected to conduct the study.

The findings of the study revealed that blockchain technology (BT) has positive effects on the university librarians as it assists them in digital resources management, provision of integrated library services, effective records management and continued professional development. The study also displayed that BT has a positive impact on the university libraries through effective information management, user privacy, collaboration, technological innovation and access control. Results also revealed that technical issues, financial constraints, security problems, skill issues and sociocultural issues created challenges to adopt BT in the university libraries.

The study has offered theoretical implications for future investigators through the provision of innovative literature on the prospectus and challenges associated with blockchain in the context of librarianship. The study has also provided practical implications for management bodies by offering recommendations for the successful adoption of blockchain in the university libraries. Additionally, a framework has been developed to adopt BT successfully in the university libraries for the delivery of smart library services to library patrons.

This bibliometric study aims to analyze the latest trends and patterns of big data applications in librarianship from 2000 to 2022. By conducting a comprehensive examination of the existing literature, this study aims to provide valuable insights into the emerging field of big data in librarianship and its potential impact on the future of libraries.

This study employed a rigorous four-stage process of identification, screening, eligibility and inclusion to filter and select the most relevant documents for analysis. The Scopus database was utilized to retrieve pertinent data related to big data applications in librarianship. The dataset comprised 430 documents, including journal articles, conference papers, book chapters, reviews and books. Through bibliometric analysis, the study examined the effectiveness of different publication types and identified the main topics and themes within the field.

The study found that the field of big data in librarianship is growing rapidly, with a significant increase in publications and citations over the past few years. China is the leading country in terms of publication output, followed by the United States of America. The most influential journals in the field are Library Hi Tech and the ACM International Conference Proceeding Series. The top authors in the field are Minami T, Wu J, Fox EA and Giles CL. The most common keywords in the literature are big data, librarianship, data mining, information retrieval, machine learning and webometrics.

This bibliometric study contributes to the existing body of literature by comprehensively analyzing the latest trends and patterns in big data applications within librarianship. It offers a systematic approach to understanding the state of the field and highlights the unique contributions made by various types of publications. The study’s findings and insights contribute to the originality of this research, providing a foundation for further exploration and advancement in the field of big data in librarianship.