Purpose The purpose of the study is to analyse attributes and the growth of YouTube videos on two majorly popular Large Language Models (LLMs): ChatGPT and DeepSeek, in a selected period. The purpose is also to assess the users' sentiment on these LLMs from the viewers' comments, and to identify the most frequently appearing terms in these comments. Design/methodology/approach Data are extracted from the videos uploaded between December 2023 and March 2025 using Python, applying the YouTube API (Application programming interface) v3. Videos and comments in the English language are only included. Sentiment analysis is done using Valence Aware Dictionary and sEntiment Reasoner (VADER) and top term analysis is done using Python. Findings The study includes 74 videos and 33,577 comments on ChatGPT, and 93 videos and 85,154 comments on DeepSeek. The findings state that both the LLMs receive positive sentiments predominantly. DeepSeek shows a slightly higher proportion (49%) than ChatGPT (45%). DeepSeek comments are more strongly positive, due to its recent release and open-source nature. ChatGPT comments are mainly neutral and strongly positive. Negative sentiments were equal (24%) across both. The results of the top term analyses indicate that top terms are related to usability and performance in ChatGPT comments. Terms in comments on DeepSeek mostly focus on geopolitical context. Research limitations/implications The dataset is limited to videos with query terms “chatgpt” or “deepseek”. The videos and comments in languages other than English have been excluded from the scope of the study. Social implications This study will assist the large number of AI users by making them aware of the benefits, limitations, challenges and features of these LLMs. It will help to perform more informed and responsible use of these technologies. Originality/value This study is the first to compare users' sentiment on ChatGPT and DeepSeek using YouTube Comments.

Purpose This study aims to examine the flow experiences of individuals engaging in virtual reality (VR) based museum visits and their intentions to continue using such experiences by drawing on the Technology Acceptance Model and telepresence theory. Design/methodology/approach Data were collected in Türkiye from 342 participants between March 1 and August 15, 2023, using convenience and purposive sampling, and were analyzed with Smart PLS. Findings The results indicate that vividness and interactivity positively influence telepresence. In turn, telepresence, perceived usefulness, and perceived ease of use positively affect flow experience. Flow experience also has a significant positive effect on continued use, representing the strongest relationship in the model. Furthermore, flow experience acts as a mediator between the TAM constructs and continued use. Overall, the findings suggest that VR-based museum visits have a positive impact on individuals. Research limitations/implications This study focuses solely on VR-based museum visitors in Türkiye, which limits the generalizability of the findings. Moreover, constraints related to the data collection method and the relatively small sample size should be taken into consideration in future research. Originality/value This study examines the effects of vividness and interactivity on telepresence, and the impact of telepresence on the flow experience, within an integrated conceptual framework based on the TAM. It also explores the role of flow experience in the sustained use of VR-based museum visits. Overall, the study contributes to the literature by providing a more comprehensive understanding of user behavior in VR-based museum experiences.

Purpose This paper aims to explore the factors that enhance the digital literacy of EU citizens, identify the driving pathways influencing digital literacy and analyze how these pathways evolve over time. Design/methodology/approach This paper opts for qualitative comparative analysis (QCA) on panel data and multi-temporal QCA methods. It examined 25 European Union member states and utilized data from 2015 to 2023 obtained from reputable international organizations, including the EU, OECD, ITU, the World Bank and UNESCO. Findings This paper identifies indicators influencing digital literacy and formulates a theoretical model encompassing four dimensions: value, application, subject and support. The results reveal four pathways of citizens' digital literacy, refined into three main pathways: “Subject Type”, “Support Type” and “Application-Support Type”. A thorough examination of these pathways indicates that the application factor is pivotal in fostering digital literacy, while the influence of the support dimension is gradually replaced by the subject dimension. This finding underscores that complex interplays of factors are essential to achieving advanced levels of digital literacy. Originality/value This paper addresses a gap in existing research, which predominantly focuses on specific groups like teachers and students, by adopting a broader international perspective. It offers insights to foster digital literacy initiatives by exploring the impact of various factors on digital literacy and comparing paths and strengths across different countries.

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PurposeResearch on library smart reading promotion lacks the interpretation of the connotation and expression of readers’ willingness to participate deeply as well as in-depth research on the influencing factors of readers’ willingness to participate deeply. In this paper, we study the influence mechanism of multiple external factors on readers’ willingness to deeply participate in library smart reading promotion from the perspectives of technology, organization and environment, based on the TAM, SIPS model and TOE framework.Design/methodology/approachFirst, based on the review of relevant literature, this paper seeks the theoretical basis of the research with the guidance of the technology acceptance model, TOE framework and SIPS model. Then the grounded theory is used to dig out the five main categories of technical factors, environmental factors, organizational factors, readers’ perception and willingness to participate deeply, explore the constituent factors of the main categories and the mechanism of action between them, and we construct a model of factors affecting the readers’ willingness to participate deeply in the promotion of smart reading in libraries. In the quantitative research part, 466 valid questionnaires were collected and the structural equation model is used to verify the relationship between variables.FindingsThe study finds that: (1) in the process of readers’ deep participation in library smart reading promotion, technological factors (personalization, interactivity and integration), organizational factors (information quality and service quality) and environmental factors (interactive atmosphere) positively affect readers’ perceptions of smart reading promotion, with interactivity and interactive atmosphere having a more significant effect; (2) the degree of confirmation of expectations has a significant positive effect on readers’ perceived usefulness (3) Readers’ willingness to participate in depth includes three aspects: willingness to read, willingness to interact and willingness to share and readers’ perceived usefulness and perceived ease of use can significantly affect willingness to participate in depth.Research limitations/implications(1) In terms of research methodology, the questionnaire was distributed in a rather basic form, and there are limitations in the screening of the survey sample and the breadth of sample coverage. In order to understand the relationship between variables more comprehensively, future research could consider using longitudinal data and conducting longer-term observation and research on the same group of subjects to further validate the conclusions of this paper. (2) In terms of the survey subjects, this paper was selected as a group of library readers who have carried out smart reading promotion. Meanwhile, most of the respondents are young readers with higher education, and the sample range is limited.Practical implicationsThis paper explores the various factors that affect users’ deep participation in smart reading promotion and provides theoretical and practical guidance for the library’s smart reading promotion work. Its research results help libraries improve the effectiveness of smart reading promotion activities from multiple aspects, such as technology, organization and environment, so as to create a better reading environment for all users.Social implicationsThis paper’s discussion on readers’ willingness to participate deeply has great theoretical significance and practical value, which will help improve the overall quality of the nation, enhance the level of smart library services and promote the development of national reading.Originality/valueThis paper divides readers’ willingness to participate deeply in reading promotion into three variables: willingness to read, willingness to interact and willingness to share, expanding the connotation and extension of readers’ willingness to participate deeply in reading promotion. Secondly, based on the SIPS model and TOE framework, a model of influencing factors of readers’ willingness to participate deeply in library smart reading promotion is proposed, and the structural equation model method is used to test the hypothesis, verifying the feasibility of the model.

PurposeThis study aimed to explored the integration of Gardner’s Multiple Intelligences (MI) theory within a learning management system (LMS), focusing on the adaptability of technology-enhanced learning environments in accommodating diverse learning styles.Design/methodology/approachA comprehensive strategy utilising a sequential mixed methods approach was utilised to investigate the research enquiries. The survey was completed by 584 undergraduate students from a university in Malaysia. Subsequently, 20 interviews were examined using Braun and Clarke’s Thematic Analysis (Braun and Clarke, 2006).FindingsThe investigation reveals that SIM within the LMS aligns with all eight multiple intelligence indicators proposed by Gardner, showcasing a comprehensive integration compared to traditional textbooks. Student experiences related to multiple intelligences within the LMS are positively indicated, emphasising linguistic, visual/spatial, interpersonal, music, naturalistic, kinaesthetic, intrapersonal and mathematical intelligence.Practical implicationsPedagogical implications suggest educators customise SIM to accommodate diverse intelligences, incorporating varied assessment methods within the LMS. The study concludes with the importance of adaptability, diverse assessments, practical application and innovative tools to create a dynamic virtual learning environment, urging educators to explore strategies that cater to diverse student intelligences.Originality/valueThis paper introduces a novel approach by exploring the integration of Howard Gardner’s MI theory within an LMS. The focus on adapting technology-enhanced learning environments to accommodate diverse learning styles is an innovative perspective. While the application of MI theory in education is not new, the study’s emphasis on incorporating it into a digital platform like an LMS represents a unique and forward-thinking approach.

PurposeThe pivotal role of artificial intelligence (AI) technology in industrial upgrading has necessitated an understanding of its evolving competitive landscape and technological trends. This paper proposes a patent data analysis framework based on fine-grained knowledge units, which is applied to provide a landscape analysis of enterprises’ technological competitive advantage in the AI field.Design/methodology/approachAI patent data collected from the Derwent Innovation Index (DII) database. The competitive patterns of the AI industry are investigated through an analysis of patent applications, regional distributions and a social network analysis of the International Patent Classification (IPC) and Derwent Manual Code (MC).FindingsThe study found that China, Japan and the United States are leading in AI technologies in terms of technological prowess and market potential. Emerging sectors include intelligent education, biological identification, intelligence servers, intelligent terminals, big data analysis and information security. Companies like IBM, Panasonic, Microsoft and Google demonstrate unique strategic orientations, with IBM notable for having the highest number of patents and citations. The analysis indicates a growing, concentrated and multi-path development profile for AI patenting, with interorganizational technical flows primarily.Research limitations/implicationsThe research is limited by the scope of patent data and the methodologies employed, which may not capture the full spectrum of AI technological advancements and competitive dynamics. Future studies should consider incorporating additional data sources for a more comprehensive analysis. Based on the particularity of AI technology, elements like open resources should be paid special attention.Practical implicationsThe study provides actionable strategic recommendations for AI industry stakeholders, emphasizing the importance of focused technological development, international collaboration and strategically designed patent portfolio management. These insights can help stakeholders navigate the complexities of the AI industry and adapt their strategies to fit evolving technological trends.Originality/valueMost previous studies on AI patent data analysis have used a macro (whole) perspective at the country level. However, this study narrows its focus to research from a micro perspective, that is, at the enterprise level. This paper studies the technological competition pattern of enterprises in the AI industry from the perspectives of competitive environment and competitive strength.

PurposeThe rapid development of information technology, epitomized by AIGC and the metaverse, presents unprecedented challenges to techno-ethics, exposing society to significant risks and uncertainties. A systematic investigation and discussion of the construction of techno-ethical order become crucial under the paradigm of risk society theory. The selection of conditions and pathways for constructing a techno-ethical order under the risk society theory paradigm becomes an unavoidable and vital issue.Design/methodology/approachDrawing on risk society theory, this study employs scientometrics and qualitative comparative analysis (QCA) to empirically analyze the key factors and conditional pathways in the construction of techno-ethical order. Initially, a quantitative analysis is conducted on 1,490 thematic literature retrieved from CNKI and WoS to identify the hot topics and core concepts in techno-ethical research. Subsequently, QCA configuration analysis is applied to calculate eight evaluation indicators and their weights from the perspectives of government, society and individuals. Finally, the study explores the mechanisms of the impact of these indicators’ weights on the construction of techno-ethical order.FindingsThe analysis of factor weights and pathways indicates that the selection of pathways for constructing techno-ethical order is influenced both by the inherent development patterns of technology and societal systems and cultural values. Literature metrics analysis reveals an overall trend of sustained growth in techno-ethical research, indicating an unprecedented prosperity in this field. Alongside technological advancements, keywords related to “artificial intelligence” play a crucial role in current techno-ethical research. Configuration analysis demonstrates that conditional variables from the dimensions of government, society and individuals form a configuration pathway, influencing and synergistically impacting the overall level of techno-ethical order construction. Attention should be given to the mutual constraints and synergistic effects of factors related to technological development, societal systems and cultural values.Originality/valueThis study, grounded in the risk society theory paradigm, quantitatively explores the key factors and pathways of techno-ethical order construction in academic texts, expanding new perspectives, providing novel insights, establishing innovative methodologies and extending new boundaries in the field. Further enrichment of the dataset and in-depth discussions are warranted for continued advancement.

PurposeThis article aims to elaborate on the current relevant policies, research literature and technical applications of administrative intelligent decision-making in major countries in the world, to summarize the current focus areas of international competition in administrative intelligent decision-making and to provide references and insights for other countries.Design/methodology/approachThe knowledge graph tool CiteSpace was used to conduct a quantitative analysis of the field of administrative intelligent decision-making, using the two dimensions of research literature and technology patents to analyze the basic status and evolution process of artificial intelligence applied to administrative decision-making.FindingsOver the past 30 years, theoretical research on administrative intelligent decision-making has primarily centered on countries like the United States of America, China and Japan. The main themes include leveraging artificial intelligence (AI) technology to enable digital government transformation, enhance administrative efficiency and promote public value through service-oriented initiatives. Countries like South Korea, China and the United States of America have demonstrated significant advantages in technology development and patent applications, focusing on e-government systems, intelligent government auditing, addressing policy mismatches between supply and demand and integrating online and offline administrative services. The international competitive landscape in this field is shaped by three key factors: foundational theories, technological advancements and practical scenario applications.Originality/valueDespite the rapid advancements in AI technology and the acceleration of enterprise digital transformation, discussions on the intelligent transformation of administrative decision-making leveraging next-generation information technology remain limited. This study summarizes the development trajectory of administrative intelligent decision-making in major countries worldwide, analyzes the international competitive landscape of its theoretical and application research and highlights key focus areas. These findings offer valuable insights for advancing the construction of administrative intelligent decision-making systems in other nations.

PurposeThe study aims to explicate how Metaverse boosts learners’ cognition, decision confidence and active participation in Metaverse-based learning (MBL).Design/methodology/approachA survey is designed with 523 respondents. Structural equation modeling (SEM) is conducted using online data to verify a research model.FindingsResults demonstrate that Metaverse-related characteristics, namely interactivity, corporeity, persistence, immersion and personalized experience, aid in strengthening learners’ cognitive processing and decision confidence, whilst escapism does not influence decision confidence in MBL. Furthermore, user-related dimensions, including personal innovativeness and perceived trendiness, are the underlying motivations for decision confidence. Additionally, cognitive processing is positively associated with decision confidence, which considerably fosters learners’ active participation in MBL.Originality/valueLimited studies have been conducted to illuminate a mechanism of cognitive processing, decision confidence and active participation among learners toward MBL in light of the Stimulus-Organism-Response (S-O-R) paradigm. Therefore, a substantial amount of knowledge is supplemented to enlighten whether learners in a developing country may generate their engagement with MBL.