The purpose of this research is to identify the areas of interest, research topics, and application areas that reflect the research nature of digital transformation (DT), as well as the strategies, practices, and trends of DT. To accomplish this, the Latent Dirichlet allocation algorithm, a probabilistic topic modeling technique, was applied to 5350 peer-reviewed journal articles on DT published in the last ten years, from 2013 to 2022. The analysis resulted in the discovery of 34 topics. These topics were classified, and a systematic taxonomy for DT was presented, including four sub-categories: implementation, technology, process, and human. As a result of time-based trend analysis, “Sustainable Energy”, “DT in Health”, “E-Government”, “DT in Education”, and “Supply Chain” emerged as top topics with an increasing trend. Our findings indicate that research interests are focused on specific applications of digital transformation in industrial and public settings. Based on our findings, we anticipate that the next phase of DT research and practice will concentrate on specific DT applications in government, health, education, and economics. “Sustainable Energy” and “Supply Chain” have been identified as the most prominent topics in current DT processes and applications. This study can help researchers and practitioners in the field by providing insights and implications about the evolution and applications of DT. Our findings are intended to serve as a guide for DT in understanding current research gaps and potential future research topics.

The purpose of this study is to explore the factors influencing individuals’ intentions to adopt generative AI, particularly within the context of digital literacy. It examines the impact of human capabilities and the relationship with technology from a transhumanist perspective. The study utilises an integrated framework combining the Unified Theory of Acceptance and Use of Technology (UTAUT) and the information quality dimension of the Information Acceptance Model (IAM). The moderating effect of attitudes towards AI is also analysed. Survey data from 362 participants in Turkey were collected and analysed using partial least squares structural equation modelling (PLS-SEM), supported by multi-group analysis based on digital literacy levels determined through clustering. The findings indicate that information quality, performance expectancy, social influence and attitudes towards AI significantly influence AI adoption intention. However, effort expectancy does not have a significant effect. Multi-group analysis reveals that higher digital literacy strengthens the impact of attitudes towards AI on adoption, and the effect of social influence on attitudes towards AI. Conversely, lower digital literacy strengthens the effect of information quality on adoption intention. This research contributes to the understanding of the role of digital literacy in generative AI acceptance. It provides insights for improving digital competence to facilitate AI adoption, especially in the context of diverse digital literacy levels, highlighting that the moderating role of digital literacy varies across different predictor–outcome relationships, which has not been extensively explored in existing literature.

This bibliometric study aims to understand the impact of digital transformation on education, with a particular focus on distance education and its technology-supported forms such as e-learning, mobile learning, and open learning. Based on the analysis of 687 publications indexed in the Scopus database between 2017 and 2023, the study investigates the evolving role of digital transformation in distance education across three distinct timeframes: pre-COVID-19 (2017–2019), during COVID-19 (2020–2021), and post-COVID-19 (2022–2023). Employing bibliometric analysis techniques, the study identifies key themes such as inclusion, accessibility, digital tools, and adaptive learning systems. It also uncovers emerging trends like the integration of artificial intelligence, gamification, and virtual reality in education. The findings reveal a significant increase in research output during and after the COVID-19 pandemic, reflecting the intensified adoption of digital technologies in response to global disruptions. Key themes, such as “Smart Technologies in Education” and “Smart Campus and Digital University,” emerged prominently in the post-pandemic era, alongside new discussions on STEM education, digital competence, and personalized learning. The analysis highlights the transformative role of digital tools in bridging accessibility gaps and enhancing student engagement. By providing insights into current trends and persistent gaps, this study contributes to a deeper understanding of how digital transformation has reshaped education. These findings emphasize the importance of integrating emerging digital technologies and innovative strategies to address persistent challenges, enhance educational outcomes, and support the development of sustainable, technology-driven learning environments.

This research study aims to analyze the relation of technology based indicators (internet use, internet access, etc.) with educational attainment of people with disability in European Union countries. Statistics related with three different types of disabilities (seeing, hearing and walking) were used at this study. Educational attainment levels are: less than primary, primary and lower secondary education (levels 0-2), upper secondary and post-secondary non-tertiary education (levels 3 and 4), tertiary education (levels 5-8). Information society indicators which are digital inclusion (digital inc), E-government activities of individuals via websites (int act), households level of internet access (int acc), individuals - mobile internet access (mob acc), Internet use for interaction with public authorities (public services) were considered in this study. In addition to this, educational attainments were analyzed comparing with countries and a variety of disabilities. Data includes values of Disability Statistics and Information Society Indicators for 2019 at Eurostat Databases. Descriptive analysis was conducted. It was concluded that walking and digital participation had the highest correlation value. It has been revealed that the hearing variable has a negative and moderately significant relationship with the information society indicators. On the other hand, it was determined that there was a high level of correlation between the hearing variable and internet access.

Media accessibility in education is vital for inclusive learning. It ensures that all students can engage with educational content, regardless of their abilities. By offering accessible formats like closed captions, transcripts, and audio descriptions, barriers to learning are eliminated. Media accessibility benefits not only those with sensory impairments but also students with learning disabilities, language barriers, or different learning preferences. Legislation and scientific studies emphasize the importance of media accessibility in education. From a methodological point of view, we will use the bibliometric study and literature review. By applying criteria specific to the two methods of analysis (keywords, language of writing documents, type of journal, number of citations, etc.), we will select articles that correspond to the objectives of the research. From an empirical point of view, theories such as social-cognitive theory, social constructivism or media richness theory will guide us in analyzing the data and establishing relevant conclusions for this field. The results we obtained confirm the importance of the study of specialized literature through specific methods and techniques in the development of new perspectives in the field of media accessibility.