National digital transformation increasingly depends on governments’ ability to govern data as a strategic public resource across agencies, sectors, and administrative levels. This challenge is especially important in developing countries, where digital platforms, national databases, and online public services may expand faster than the institutional capability required to govern data coherently. Existing studies have examined open data, interoperability, metadata, stewardship, and public sector data governance, but these strands remain only partially connected in explaining how national digital data governance becomes workable under uneven institutional conditions. To address this gap, national digital data governance is conceptualized here as an institutional capability problem. The framework developed in the paper identifies five interrelated dimensions: strategic orientation and public value, implementation foundations, governance architecture, a national coordinating mechanism, and institutional conditions. Vietnam is used as an illustrative policy context, not as a formal empirical case study, because its recent digital reform agenda includes national digital transformation strategies, national databases, electronic identification, data sharing regulations, the National Data Center scheme, and the Law on Data 2024. The framework is used to examine how governance fragmentation may arise from weak alignment among strategic purpose, operational foundations, governance arrangements, coordinating mechanisms, and institutional conditions.
This study evaluates and forecasts the usage of the OECD (Organisation for Economic Co-operation and Development) iLibrary database, subscribed to by the Library of the Grand National Assembly of T & uuml;rkiye (GNAT). To capture dynamic and scale-dependent relationships between usage and external shocks we applied Morlet and Mexican hat wavelet coherence analysis, which are effective tools for continuous wavelet coherence analysis. The results of Morlet wavelet coherence revealed short- and medium-term co-movements driven by external factors, whereas Mexican hat coherence identified more persistent long-term relationships. Subsequently, the regression algorithms were applied on usage data decomposed by maximal overlap discrete wavelet transform (MODWT) and multiresolution analysis (MRA), providing a flexible framework for representing usage data at multiple resolution levels, while preserving temporal alignment and minimizing information loss. The findings revealed that usage patterns exhibited a multi-year synchronization with exogenous factors and regularized linear approaches such as ElasticNet, Lasso, and Ridge regression outperformed non-linear methods. SHapley Additive exPlanations-based interpretation, which quantified the contribution of each predictor of model outputs, showed that short-term fluctuations in usage data were the strongest predictors of future usage. The study demonstrates that e-resource usage should be understood and managed as a multi-scale, dynamically evolving process, and provides a framework that enables libraries to anticipate demand, align collections with institutional cycles, and respond to both short- and long-term changes.
This article develops an exploratory expert-based perceptual model of the perceived drivers of open development in Egypt using a convergent parallel mixed-methods design. Quantitative data from 203 expert respondents (Likert-scale survey) are integrated with 30 in-depth interviews across government, academic, private-sector, and civil-society organisations through an explicit joint display. Anchored in Sen's capability approach-extended through the critical capability lens and informed by data-justice and openwashing critiques, the study examines six dimensions of openness. Within-dimension regression analyses (R-2 = 0.707-0.810) identify community participation as the strongest perceptual predictor (beta = 0.377), while qualitative findings identify Arabic-content scarcity, civic-space constraints, and urban-rural divides as binding capability conversion factors. The study contributes a context-sensitive analytical template for openness research in politically mediated emerging economies.
This study aims to investigate the digital Information-Seeking Behavior (ISB) and digital confidence of university students in Bangladesh and to explore their association with demographic factors and institutional context. A cross-sectional quantitative survey was conducted with 450 students from two major public universities in Bangladesh. The study found a strong preference for digital resources (M = 4.08), with search engines (M = 3.85) and e-books/online journals (M = 3.85) being the most frequently used tools. University-specific digital resources were used less often (M = 3.67). Digital confidence was significantly correlated with gender (p < 0.05), academic level (p < 0.05) and university (p < 0.001). Male students and those at higher academic levels demonstrated higher levels of digital confidence. Multinomial logistic regression analysis indicated that university affiliation was a significant predictor of digital confidence, with students from DU exhibiting significantly higher digital engagement and digital confidence (Exp(B) = 4.332, p = 0.000). Additionally, older students and those in STEM fields showed greater digital engagement and confidence. This study highlights the role of institutional contexts in shaping students' digital engagement and suggests that demographic factors influence digital confidence. It emphasizes the need for targeted, context specific digital literacy programs to reduce digital divides and enhance critical digital competencies among different student subgroups in Bangladesh.
The purpose of this study is to explore the effect of AI-powered chatbots on LIS professionals' job performance using Goal-Setting Theory (GST). AI-Powered Chatbots (AIPC) serve as an independent variable, and a relation was observed with Innovation Capability (IC), Soft Skills (SS), and Job Performance (JP). The study employs quantitative survey techniques. Online survey questionnaire was used as a data collection tool from 300 LIS professionals working in the academic universities of Islamabad and Lahore, Pakistan. Data was collected through non-probability sampling. Sample size was determined using literature. This study used SmartPLS to examine the relationship between independent and dependent variables. The results showed a significant relationship between AIPC, SS, IC, and JP. The findings indicate that AIPC can be used to enhance the SS, IC, and JP of LIS professionals. The findings also reveal that AIPC adoption not only improves efficiency in the work environment but fosters adaptability, creativity, and collaboration between LIS professionals to strengthen the positive organizational outcome. The mediating role of IC, and SS was also found significant on LIS professional's JP. In the context of Library and Information Sciences (LIS), this is the first study to explore the effect of AIPC on JP with the mediating role of SS and IC. This study can help in practical application of policy making and administrative decision making regarding the job performance of LIS professionals in an AI-driven technology-based environment.
Regional educational informatization (REI) is a key pathway to advancing educational equity and narrowing the digital divide, yet its actual impact on individual digital literacy lacks systematic empirical examination. This study empirically analyzes the impact of REI on digital literacy using quantitative regression approaches. Results show that REI significantly enhances individual digital literacy, with a more pronounced effect on digital acquisition and usage while exerting limited influence on digital awareness. Five core transmission mechanisms are identified: digital endowment empowerment, digital consumption driving, social capital accumulation, learning behavior promotion, and social interaction diffusion. Notably, REI exhibits a "disadvantaged support" effect, generating stronger positive impacts on individuals with lower educational attainment, women, and residents in economically, digitally or educationally underdeveloped regions, which aligns with the principles of educational equity and inclusiveness. Conversely, REI has a negative impact on residents in digitally advanced areas and fails to address the "digital outreach blind spots" faced by the elderly group, indicating the need to further optimize the educational informatization ecosystem for greater inclusiveness and age-friendliness. These findings deepen the understanding of REI's role in fostering digital literacy, provide empirical evidence for research on public education equity and educational ecology, and offer important theoretical and practical insights for optimizing REI development strategies and narrowing the digital literacy gap, particularly for digitally disadvantaged groups.
The study examines Open-Source Assistive Resources (OSAR) as viable accessibility solutions for patrons with visual impairments in selected academic libraries in Zimbabwe's Midlands Province. The study was guided by three research questions: (i) How are selected academic libraries in Zimbabwe's Midlands Province implementing OSAR for patrons with visual impairments? (ii) What factors influence the adoption of OSAR in these libraries? (iii) What institutional capacities are required to sustain OSAR for patrons with visual impairments in the selected academic libraries? The study population comprised 59 participants drawn from five academic libraries (AL1-AL5) in Zimbabwe's Midlands Province, including library staff (n = 12), student services staff (n = 4), academic staff/lecturers (n = 5), students with visual impairments (n = 16), staff members with visual impairments (n = 10), alumni with visual impairments (n = 6), and Zimbabwe Library Association members (n = 6). Data were generated through questerviews, semi-structured interviews, focus group discussions, observations, and document analysis, and analysed using thematic analysis with QDA Miner Lite version 5. Findings reveal that OSAR implementation remains fragmented and largely opportunistic across four of the five libraries studied, with only AL4's dedicated Disability Resource Centre demonstrating sustained, strategic deployment. Cost advantage was widely recognised; however, inadequate infrastructure (cited by 35.60% of participants), limited OSAR awareness (33.90%), technical complexity, and absent management support constrain systematic adoption. Sustaining OSAR requires comprehensive institutional capacities, including needs assessment capacity (59.30%), infrastructure upgrades (54.20%), staff training and development (45.80%), inter-institutional networking (42.40%), and strategic planning. The study concludes that OSAR adoption is shaped primarily by institutional capacity deficits rather than technological limitations, and that sustainability requires structural transformation extending beyond mere software acquisition.
As in many other fields, the use of AI tools in scientific research has attracted great interest among scholars. However, evidence regarding the factors that influence the use of AI tools by scholars in scientific research is fragmented and context dependent. Moreover, it is also underexamined to what extent these factors are necessary for the use of AI tools in academic research. Therefore, this study investigates the factors influencing scholars' behavioral intention, use behavior and purchase behavior regarding AI tools, and assesses the degree to which each factor is necessary. For this purpose, data were collected from 557 scholars to investigate their intentions to use AI tools, use behavior, and purchase behavior from the perspectives of UTAUT2, personal innovativeness, and perceived ethics. PLS-SEM results revealed that performance expectancy and habit had the strongest positive impact on behavioral intention. Facilitating conditions and behavioral intention impact use behavior, while use behavior and price value positively affect purchase behavior. Furthermore, the Necessary Condition Analysis (NCA) was conducted by using the findings obtained from PLS-SEM, and the level of necessity of each factor with a significant effect on scholars' intentions to use AI tools, use behavior, and purchase behavior was revealed.
Parent involvement is a major factor in the initiation of a child's reading skills and challenges. However, the education level of parents and the social and economic status of the community may hinder such responsive behaviors. This research examines the contributions of continuous parental engagement on the reading habits and cognitive development of preschoolers via the home literacy environment and socio-economic status as a mediator. The research design was quasi-experimental, and the participants were 312 parents and their preschoolers from Xi'an, China. Data were obtained from various pre-tests, an eight-week reading intervention program, post-test questionnaires, parent interviews, and focus groups. The results demonstrated that parental participation caused changes in children's reading habits, the home literacy environment, and their cognitive development. For instance, the mediation evaluation provided an indication that the availability of home literacy resources partially mediated the relationship between early reading in the preschool stage and academic development of preschoolers, and parental education and socio-economic status were the main factors. The different educational chances leading to the varying results have been brought to the forefront. The research indicates that elementary education projects that guarantee that families of low socio-economic and educational backgrounds have access to reading programs should mainly concentrate on the promotion of reading, the adoption of inclusive literacy practices, and the progress towards societal equity. The research is limited as summarized by the non-randomized design, self-reported data sources, and a short intervention time frame, limiting possible longitudinal generalizability, but still adds new empirical knowledge regarding the complex overlap between parental involvement, home literacy environments, and socio-economic aspects on early child development that describes a valuable insight for policy innovation and further research.
Open Government Data (OGD) can help generate economic and social value. While previous studies have explored the factors influencing OGD use, they typically focus on either governmental internal or external aspects of OGD, seldom investigating both aspects and their combined impact simultaneously. This paper aims to analyze how combinations of government internal supply and external institutional pressure factors jointly shape the degree of OGD use by applying fuzzy-set Qualitative Comparative Analysis (fsQCA) across 278 cities. Our findings reveal that high OGD use is associated with configurations that blend strong technological capabilities, clear institutional frameworks, active leadership, and adequate financial support with external pressures from higher authorities and competitive environments. In contrast, low OGD use emerges in contexts marked by technological, financial, and data resource shortages, alongside a lack of leadership engagement. These insights highlight the pivotal role of balanced internal resource management and proactive engagement with external pressures in driving effective OGD use.
This study examines how social barriers and digital inequality constrain low-income coastal youth in South Sulawesi, Indonesia, from accessing post-secondary learning. Integrating human capital theory, social capital theory, and the technology acceptance model, we propose a context-sensitive framework for digital skills training in resource-constrained ecosystems. Using an exploratory multi-site qualitative design (semi-structured interviews and focus group discussions (FGDs) across three coastal settings), we identify intertwined constraints-device scarcity, high data costs, low digital readiness, and weak curricular relevance. We advance three design pillars: (1) locally contextualized curricula aligned with livelihood niches; (2) community-anchored co/peer learning with legitimate bridging actors; and (3) low-bandwidth, offline-first microlearning with lightweight assessments. These elements are likely to strengthen bonding, bridging, and linking social capital, which may improve participation, retention, and sustainability. We provide a logic model and SDG-aligned indicators (e.g., device-loan uptake, learning hours, data cost per learner) to guide information and communication technologies for development (ICT4D) stakeholders.
This study examines cross-country differences in Artificial Intelligence (AI) development, emphasizing the role of the digital divide. First, countries are classified into advanced, emerging, and lagging groups using cluster analysis. Then, a probabilistic model assesses how socio-economic factors such as GDP, Human Development Index (HDI), business density, and skilled labor unemployment, influence the likelihood of countries belonging to the AI emerging/advanced cluster. Results show that higher GDP per capita, skilled labor unemployment and HDI increase the likelihood of belonging to the AI emerging/advanced group. AI tends to deepen the pre-existing digital or connectivity divide. The findings underscore the need for policies and coordinated strategies that promote AI adoption and address ICT appropriation disparities, addressing structural socio-economic constraints. Advancing from lagging to an emerging/advanced position requires deep transformations in digital infrastructure, human capital and access to quality data.
Despite the emerging needs for research data management (RDM) practices in Tanzania, the efforts have remained underutilised, fragmented, and insufficiently coordinated. This has highlighted the need for a national RDM framework to guide, harmonise, and standardise RDM practices in Tanzania. To propose this framework, the study employed three models: the Community Capability Model (CCM) framework, the Data Maturity Model (DMM), and the Unified Theory of Acceptance and Use of Technology (UTAUT). The literature review and the empirical findings informed the development of the proposed model. For empirical findings, data were collected from ten selected government agencies and research institutions in Tanzania. The study's population comprises institutional leaders, researchers, and RDM experts. The study employed a mixed-methods research approach to collect data from 272 researchers, 23 institutional leaders, and 17 RDM experts. Findings have shown that RDM collaboration, along with the RDM infrastructural ecosystems, were the most influential components of RDM practices. Other influential components were policy and regulatory frameworks, RDM competence, and contextual factors. These findings served as the foundation for designing the proposed national RDM framework in Tanzania. The proposed framework was then shared with the selected RDM experts, who provided perspectives that led to further refinement. The study offers contributions to research institutions in Tanzania, policymakers, and government agencies seeking to adopt, institutionalise, and sustain RDM practices at both national and institutional levels.
Diamond Open Access (OA) is a publishing model that eliminates fees for both authors and readers, promoting diversity and fairness in academic publishing. This model holds particular importance in Africa, where limited research funding makes it more challenging for scholars to be visible. This paper examines strategies for sustaining Diamond OA in Africa, using the Regional Journal of Information and Knowledge Management (RJIKM) as a case study. The study draws on insights from a July 2025 stakeholder event, focus groups, and panel discussions to highlight ongoing challenges, including financial instability, volunteer burnout, prestige bias, and limited inclusion in global indexes. It also highlights opportunities such as building regional partnerships, enhancing institutional support, adopting new technologies, and modifying citation practices. To address the core challenges of Diamond OA, the paper proposes a comprehensive framework comprising four components: ensuring financial stability, advancing knowledge equity, strengthening community involvement, and leveraging technology. By focusing on knowledge equity and shared decision-making, Diamond OA provides Africa with a means to shape its own academic future. The study concludes that maintaining Diamond OA in Africa requires a collective commitment to financial innovation, technological progress, institutional backing, and community participation to achieve a more equitable scholarly future. To accomplish these goals, we suggest policy reforms, regional collaboration, professionalisation of editorial work, and the incorporation of Diamond OA into Africa's broader development strategies.
Cross-border data flows (CBDFs) are increasingly central to the global digital economy, yet governance, institutional, and technological challenges continue to shape their trajectory. This study investigates the determinants of CBDFs by examining the role of cybersecurity readiness, data monetization capacity, and digital infrastructure across 27 economies between 2015 and 2023. Using panel econometric methods, Feasible Generalized Least Squares (FGLS), Panel-Corrected Standard Errors (PCSE), and Granger causality tests, we found that stronger cybersecurity performance and higher levels of software spending significantly promote international data mobility. Conversely, digital infrastructure, proxied by broadband penetration, shows a negative association, reflecting regulatory tightening and localization measures in digitally advanced economies. A cluster-based analysis highlights differences across emerging and mature economies, underscoring the need for context-specific policies. The findings contribute to debates on digital governance and offer practical guidance for policymakers seeking to balance trust, value creation, and openness in the data economy.
In knowledge and information management, solidarity economy organisations appear to be under-explored, despite their economic importance in countries like Brazil, showing a literature gap regarding their sociocultural context, which has specific management practices and needs. For this research, a case study of the Multidisciplinary and Integrated Nucleus for Studies, Formation and Intervention in Solidarity Economy (NuMI-EcoSol) was conducted using a descriptive-exploratory qualitative approach, with direct observation, document analysis and semi-structured interviews. Twenty-five observation sessions, three documents and five interviews were analysed with a focus on knowledge and information flow, information policy, information culture and decision-making spaces. The results showed that the Nucleus is a knowledge intensive, multidisciplinary, dialogical and self-managed organisation. Its information culture and policy reflect solidarity economy characteristics that establish advantageous knowledge-creating dynamics for social innovation, mainly within networks, but it also faces challenges regarding knowledge loss and drain. Therefore, the organisation and its nature has particularities for knowledge use still not fully explored and comprehended. Competitive intelligence, structuration of self-managed repositories and mediation in networks are important actions to further promote knowledge use for social innovation. Lastly, suggestions are made for further research on aspects arising from this case study.
As library information systems become increasingly intelligent, they generate vast amounts of information. This study identifies the key factors shaping user experience in such systems. Using grounded theory, we extracted variables from interviews (N = 14) and developed a framework based on the Stimulus–Organism–Response model. A survey (N = 320) tested the hypothesized relationships through structural equation modelling, while artificial neural networks captured non-linear effects and ranked factor importance. Results show that information validity is the strongest predictor of interaction fluency. While aesthetic interface design improves Interaction Fluency, it does not significantly affect perceptions of System Support Level. These findings highlight the need to balance efficient information provision with human-centred design. Overemphasis on functionality risks diminishing engagement. Future designs should prioritize information validity for guidance tasks while also enhancing cultural and emotional experiences in both human and AI-driven library services.
The study explored the reality and benefits of the use of AI-powered academic search systems from the perspective of Egyptian academics in Library and Information Science (LIS). It also provided a comprehensive view of this category of systems. The study used a self-administered questionnaire as a survey instrument to gather data from the study population, which consisted of faculty staff and assistants belonging to the LIS departments (22 departments) in Egypt. The sample included 164 participants who responded to the questionnaire. SPSS was used to perform the statistical analyses. The results showed that 42.7% of participants used AI-powered academic search systems, while the majority (57.3%) did not. The most prominent reason for not using AI-powered academic search systems was the preference of most participants for alternative search systems, such as library catalogs, online databases, and search engines. Overall, Semantic Scholar (41.43%), Scite (37.14%), and Research Rabbit (32.86%) were the most commonly used systems. Moreover, the study demonstrated a positive level of participant satisfaction with these systems, with means from 3.614 to 4.257 and standard deviations from 0.700 to 1.067. It revealed the most significant concerns that users face when interacting with this category of systems. Finally, these concerns were discussed in detail and some solutions were presented to address them.
As digitization progresses, many industries are moving online, yet e-commerce companies often struggle to deliver satisfying shopping experiences. This study aims to analyze how people flip through books in offline environments and, based on these findings, experimentally explore ways to enhance UX by implementing book-flipping behaviors that were previously impossible in online bookstores. In the first experiment, we observed offline book-flipping behavior and analyzed it through affinity mapping. Based on these findings, the second experiment tested three preview types-front, table of contents, and random-across seven dependent variables related to user perceptions and behavioral intentions. ANOVA results showed significant differences between the offline-based methods and the control group, suggesting that replicating offline behavior online can meaningfully enhance the user experience in e-commerce.
