This research examines how transactional leadership and organizational culture relate to knowledge-sharing behavior among librarians in Vietnamese academic libraries. Drawing on the competing values framework, the study develops an integrated model in which leadership and culture impact knowledge-sharing behavior. Data were collected from 420 librarians working in Vietnamese academic libraries. Confirmatory factor analysis and regression analysis were used to assess the measurement model and the proposed relationships among transactional leadership, organizational culture, and knowledge-sharing behavior. The findings indicate that organizational culture is a central driver of knowledge sharing. In particular, adhocracy and clan cultures show the strongest positive relationships with knowledge-sharing behavior, market culture has a more moderate effect, and hierarchy culture is not a significant predictor. Taken together, the study suggests that knowledge sharing in Vietnamese academic libraries depends not only on formal leadership control but also on cultural conditions, value alignment, and employees’ ability to preserve personal resources while performing knowledge-intensive library work.
The rapid advancement of artificial intelligence (AI) is transforming professional practices across library and information environments. This study aimed to identify the factors influencing the adoption of AI for librarians’ continuing professional development (CPD) through a systematic literature review (SLR) methodology. A total of 30 peer-reviewed articles retrieved from major global digital databases were systematically analyzed to synthesize the existing body of knowledge on AI adoption in librarianship. The findings revealed that attitudinal readiness, competency transformation, organizational readiness, experiential learning opportunities, and future-oriented professional identity significantly encourage the adoption of AI for librarians’ CPD. Conversely, insufficient structured CPD opportunities, resistance to technological change, limited technological infrastructure, and ethical concerns emerged as major barriers hindering effective AI integration in professional learning environments. Based on the findings, the study developed a comprehensive framework to support the efficient and sustainable adoption of AI for librarians’ CPD. The study contributes to the growing discourse on AI-enabled professional learning in library and information science by offering theoretical, practical, and strategic insights to enhance librarians’ readiness for AI-driven information environments.
Digital inclusion has emerged as a multidimensional socio-technical challenge that extends beyond providing access to information and communication technologies. While libraries are increasingly recognized as key institutions for promoting equitable digital participation, evidence on the determinants of digital inclusion within Indian library settings remains fragmented. This study systematically synthesizes the existing literature to map the research landscape, identify the key determinants of digital inclusion, and develop an integrative framework to advance research and practice in Indian libraries. A systematic literature review was conducted following the PRISMA 2020 guidelines. Relevant studies published between 2011 and 2025 were retrieved from the Scopus and Web of Science databases using predefined search strategies. Eligible studies were screened using explicit inclusion and exclusion criteria and analysed through descriptive and thematic synthesis. The review reveals that research on digital inclusion in Indian libraries has grown steadily but remains fragmented across library sectors and disciplines. Seven interrelated determinants were identified: socio-demographic, socio-economic, technological, digital literacy, institutional and policy, socio-cultural, and psychological and behavioural factors. The findings demonstrate that meaningful digital inclusion depends not only on digital infrastructure but also on users’ capabilities, institutional readiness, supportive policies, cultural responsiveness, and behavioural engagement. An integrative framework is proposed to explain the interaction of these determinants in shaping inclusive digital library services. Although the review is limited to English-language journal articles indexed in Scopus and Web of Science, it provides a robust foundation for future empirical research across diverse library contexts. The findings offer evidence-based guidance for librarians, policymakers, and educational institutions to strengthen digital literacy, improve ICT infrastructure, and formulate inclusive policies that reduce digital inequalities. This study presents the first comprehensive systematic synthesis of digital inclusion within Indian library settings and advances both theory and practice by proposing an integrative framework for developing equitable, accessible, and user-centred library services.
In the context of the digital era, libraries face competition from Internet search engines, online databases, and other digital information services. Only by innovating management modes and providing higher-quality, convenient, and personalized services can libraries remain competitive. In this study, “personalized service” specifically refers to (i) recommending book categories that match each reader’s interest profile (preference-fit recommendation) and (ii) prioritizing space-service suggestions (area ranking) based on readers’ recent borrowing frequency and recency signals, thereby improving service efficiency for both users and staff. Based on this, the study proposes a personalized recommendation system for book borrowing management by combining the K-means clustering algorithm and factor analysis. In addition, a temporal decay weighting function inspired by the Ebbinghaus forgetting curve is used to model borrowing recency and frequency when estimating short-term space-service demand. Experimental results show that the proposed method maintains stable time consumption as the bibliographic search scale increases, with a peak time of 20 s at 3,000 iterations and a minimum of 3 s at 1,600 iterations. The retrieval accuracy for users’ spatial management needs shows an overall increasing trend, reaching 91.09% at 2,500–3,000 searches, with the minimum accuracy of 78.89% observed at 1,000–1,500 retrievals. These results indicate that the proposed model can improve personalized recommendation effectiveness and spatial service efficiency, providing a practical reference for intelligent library management innovation.
The study aimed to identify the prospects of ambient intelligence (AmI) technology for smart library environments in academic settings, and to reveal the challenges for an effective adoption of AmI technology in libraries. Systematic literature review (SLR) methodology was applied to address the study’s objectives. 20 peer-reviewed papers published in 12 world’s renowned digital databases were selected to conduct the study. Findings of the study showed that technological advancements, personalization, context-awareness, human-centered services, integration of physical and digital resources, and lifelong learning are key factors that influence the adoption of ambient intelligence technology in libraries. Results of the study showed that financial and resource constraints, ethical, privacy, and security concerns, technical and infrastructural complexities, and human and organizational barriers caused challenges for the effective adoption of AmI technology in library settings. The study has provided pertinent theoretical, managerial, methodological, and social implications. It has offered practical recommendations for an effective adoption and sustainability of AmI technology for smart library environments in academic settings.
