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This study aims to assess the scholarly communication competence of Zambian library and information science (LIS) professionals by evaluating their awareness, knowledge and practices regarding scholarly publication.

Applying a quantitative research approach, the study used a specially designed questionnaire. Responses from 57 professionals across universities and colleges in Zambia were gathered using convenience sampling. Data analysis involved descriptive statistics, mean and standard deviation calculations and t-values and p-values to understand respondents’ perceptions and knowledge of scholarly communication and publication.

The findings revealed significant gaps in respondents’ knowledge and awareness, particularly regarding predatory journals, journal selection factors, open-access models, publication challenges, reference management software (RMS) usage and research obstacles. The study underscored the necessity for increased training and capacity-building initiatives among Zambian LIS professionals to enhance their scholarly communication competence.

This research contributed to the field by highlighting deficiencies in scholarly communication awareness among Zambian LIS professionals. It emphasised the need for targeted interventions, awareness programs and educational support to improve academic literacy and scholarly publication practices. Additionally, the study suggested future research avenues, such as longitudinal studies and strategies for enhancing RMS adoption, to advance scholarly practices among Zambian professionals further.

The purpose of this study is to examine the trends and developments of subscription business models (SBMs) over the past two decades.

The study extracted 469 documents (articles and reviews) from the Scopus database during 2000–2022 and analysed 132 documents (articles and reviews). A bibliometric methodology of scientific mapping was employed, including a cluster analysis based on the bibliographic coupling of documents. Content analysis was also conducted to reveal emerging trends in SBMs.

The study revealed six emerging themes in SBMs related to consumer behaviour, digital advertising, online news media, journal publications, circular economy and sustainability strategies.

The results of this study provide new and unique insights into the development and trends of SBMs over the past two decades and offer guidance for future researchers to investigate further the phenomenon of SBMs in emerging areas.

This paper focuses on image-to-text manuscript processing through Handwritten Text Recognition (HTR), a Machine Learning (ML) approach enabled by Artificial Intelligence (AI). With HTR now achieving high levels of accuracy, we consider its potential impact on our near-future information environment and knowledge of the past.

In undertaking a more constructivist analysis, we identified gaps in the current literature through a Grounded Theory Method (GTM). This guided an iterative process of concept mapping through writing sprints in workshop settings. We identified, explored and confirmed themes through group discussion and a further interrogation of relevant literature, until reaching saturation.

Catalogued as part of our GTM, 120 published texts underpin this paper. We found that HTR facilitates accurate transcription and dataset cleaning, while facilitating access to a variety of historical material. HTR contributes to a virtuous cycle of dataset production and can inform the development of online cataloguing. However, current limitations include dependency on digitisation pipelines, potential archival history omission and entrenchment of bias. We also cite near-future HTR considerations. These include encouraging open access, integrating advanced AI processes and metadata extraction; legal and moral issues surrounding copyright and data ethics; crediting individuals’ transcription contributions and HTR’s environmental costs.

Our research produces a set of best practice recommendations for researchers, data providers and memory institutions, surrounding HTR use. This forms an initial, though not comprehensive, blueprint for directing future HTR research. In pursuing this, the narrative that HTR’s speed and efficiency will simply transform scholarship in archives is deconstructed.

Websites, search engines, recommender systems, artificial intelligence and digital libraries have the potential to support serendipity for unexpected interaction with information and ideas which would lead to favored information discoveries. This paper aims to explore the current state of research into serendipity particularly related to information encountering.

This study provides bibliometric review of 166 studies on serendipity extracted from the Web of Science. Two bibliometric analysis tools HisCite and RStudio (Biblioshiny) are used on 30 years of data. Citation counts and bibliographic records of the papers are assessed using HisCite. Moreover, visualization of prominent sources, countries, keywords and the collaborative networks of authors and institutions are assessed using RStudio (Biblioshiny) software. A total of 166 papers on serendipity were found from the period 1989 to 2022, and the most influential authors, articles, journals, institutions and countries among these were determined.

The highest numbers of 11 papers were published in the year 2019. Makri and Erdelez are the most influential authors for contributing studies on serendipity. “Journal of Documentation” is the top-ranking journal. University College London is the prominent affiliation contributing highest number of studies on serendipity. The UK and the USA are the prominent nations contributing highest number of research. Authorship pattern for research on serendipity reveals involvement of single author in majority of the studies. OA Green model is the most preferred model for archiving of research articles by the authors who worked on serendipity. In addition, majority of the research outputs have received a citation ranging from 0 to 50.

To the best of the authors’ knowledge, this paper may be the first bibliometric analysis on serendipity research using bibliometric tools in library and information science studies. The paper would definitely open new avenues for other serendipity researchers.

Knowledge graphs (KGs) are structured knowledge bases that represent real-world entities and are used in a variety of applications. Many of them are created and curated from a combination of automated and manual processes. Microdata embedded in Web pages for purposes of facilitating indexing and search engine optimization are a potential source to augment KGs under some assumptions of complementarity and quality that have not been thoroughly explored to date. In that direction, this paper aims to report results on a study that evaluates the potential of using microdata extracted from the Web to augment the large, open and manually curated Wikidata KG for the domain of touristic information. As large corpora of Web text is currently being leveraged via large language models (LLMs), these are used to compare the effectiveness of the microdata enhancement method.

The Schema.org taxonomy was used as the source to determine the annotation types to be collected. Here, the authors focused on tourism-related pages as a case study, selecting the relevant Schema.org concepts as point of departure. The large CommonCrawl resource was used to select those annotations from a large recent sample of the World Wide Web. The extracted annotations were processed and matched with Wikidata to estimate the degree to which microdata produced for SEO might become a valuable resource to complement KGs or vice versa. The Web pages themselves can also serve as a context to produce additional metadata elements using them as context in pipelines of an existing LLMs. That way, both the annotations and the contents itself can be used as sources.

The samples extracted revealed a concentration of metadata annotations in only a few of the relevant Schema.org attributes and also revealed the possible influence of authoring tools in a significant fraction of microdata produced. The analysis of the overlapping of attributes in the sample with those of Wikidata showed the potential of the technique, limited by the disbalance of the presence of attributes. The combination of those with the use of LLMs to produce additional annotations demonstrates the feasibility of the approach in the population of existing Wikidata locations. However, in both cases, the effectiveness appears to be lower in the cases of less content in the KG, which are arguably the most relevant when considering the scenario of an automated population approach.

The research reports novel empirical findings on the way touristic annotations with a SEO orientation are being produced in the wild and provides an assessment of their potential to complement KGs, or reuse information from those graphs. It also provides insights on the potential of using LLMs for the task.

Data sharing is increasingly being recognized as an essential component of scholarly research and publishing. Sharing data improves results and propels research and discovery forward. Given the importance of data sharing, the purpose of the study is to unveil the present scenario of research data repositories (RDR) and sheds light on strategies and tactics followed by different countries for efficient organization and optimal use of scientific literature.

The data for the study is collected from registry of RDR (re3data registry) (re3data.org), which covers RDR from different academic disciplines and provides filtration options “Search” and “Browse” to access the repositories. Using these filtration options, the researchers collected metadata of repositories i.e. country wise contribution, content-type data, repository language interface, software usage, metadata standards and data access type. Furthermore, the data was exported to Google Sheets for analysis and visualization.

The re3data registry holds a rich and diverse collection of data repositories from the majority of countries all over the world. It is revealed that English is the dominant language, and the most widely used software for the creation of data repositories are “DataVerse”, followed by “Dspace” and “MySQL”. The most frequently used metadata standards are “Dublin Core” and “Datacite metadata schema”. The majority of repositories are open, with more than half of the repositories being “disciplinary” in nature, and the most significant data sources include “scientific and statistical data” followed by “standard office documents”.

The main limitation of the study is that the findings are based on the data collected through a single registry of repositories, and only a few characteristic features were investigated.

The study will benefit all countries with a small number of data repositories or no repositories at all, with tools and techniques used by the top repositories to ensure long-term storage and accessibility to research data. In addition to this, the study provides a global overview of RDR and its characteristic features.

Accounting information systems are mainly rule-based, and data are usually available and well-structured. However, many accounting systems are yet to catch up with current technological developments. Thus, artificial intelligence (AI) in financial accounting is often applied only in pilot projects. Using AI-based forecasts in accounting enables proactive management and detailed analysis. However, thus far, there is little knowledge about which prediction models have already been evaluated for accounting problems. Given this lack of research, our study aims to summarize existing findings on how AI is used for forecasting purposes in financial accounting. Therefore, the authors aim to provide a comprehensive overview and agenda for future researchers to gain more generalizable knowledge.

The authors identify existing research on AI-based forecasting in financial accounting by conducting a systematic literature review. For this purpose, the authors used Scopus and Web of Science as scientific databases. The data collection resulted in a final sample size of 47 studies. These studies were analyzed regarding their forecasting purpose, sample size, period and applied machine learning algorithms.

The authors identified three application areas and presented details regarding the accuracy and AI methods used. Our findings show that sociotechnical and generalizable knowledge is still missing. Therefore, the authors also develop an open research agenda that future researchers can address to enable the more frequent and efficient use of AI-based forecasts in financial accounting.

Owing to the rapid development of AI algorithms, our results can only provide an overview of the current state of research. Therefore, it is likely that new AI algorithms will be applied, which have not yet been covered in existing research. However, interested researchers can use our findings and future research agenda to develop this field further.

Given the high relevance of AI in financial accounting, our results have several implications and potential benefits for practitioners. First, the authors provide an overview of AI algorithms used in different accounting use cases. Based on this overview, companies can evaluate the AI algorithms that are most suitable for their practical needs. Second, practitioners can use our results as a benchmark of what prediction accuracy is achievable and should strive for. Finally, our study identified several blind spots in the research, such as ensuring employee acceptance of machine learning algorithms in companies. However, companies should consider this to implement AI in financial accounting successfully.

To the best of our knowledge, no study has yet been conducted that provided a comprehensive overview of AI-based forecasting in financial accounting. Given the high potential of AI in accounting, the authors aimed to bridge this research gap. Moreover, our cross-application view provides general insights into the superiority of specific algorithms.

Over the past few decades, university reforms in line with management and enterprise ideals have been well documented. Changes in the ideals underlying the missions of universities have led to changes in their modes of governing and organizing, which in turn drive further transformation of their missions. One set of reforms in Swedish higher education has been the dissolution of collegial bodies and procedures. At the same time, in recent years, we have witnessed an increased interest in collegiality and a reintroduction of collegial bodies and procedures. New translations of collegiality appear not only in how universities are organized, but also in other core aspects of research and higher education. We review examples of peer reviewing, research assessment, and direct recruitment of professors and ask: Can these new translations of collegiality be understood as a revitalization of collegiality, or is it – to draw a parallel with greenwashing – rather a matter of collegiality-washing?

Engaging with digital heritage requires understanding not only to comprehend what is simulated but also the reasons leading to its creation and curation, and how to ensure both the digital media and the significance of the cultural heritage it portrays are passed on effectively, meaningfully, and appropriately. The United Nations Educational, Scientific, and Cultural Organization defines ‘digital heritage’ to comprise of computer-based materials of enduring value some of which require active preservation strategies to maintain them for years to come.

With the proliferation of digital technologies and digital media, computer games have increasingly been seen as not only depicters of cultural heritage and platforms for virtual heritage scholarship and dissemination but also as digital cultural artefacts worthy of preservation. In this chapter, we examine how games (both digital and non-digital) can communicate cultural heritage in a galleries, libraries, archives, and museums [GLAM] setting. We also consider how they can and have been used to explore, communicate, and preserve heritage and, in particular, Indigenous heritage. Despite their apparently transient and ephemeral nature, especially compared to conventional media such as books, we argue computer games can be incorporated into active preservation approaches to digital heritage. Indeed, they may be of value to cultural heritage that needs to be not only viewed but also viscerally experienced or otherwise performed.