https://lib.journals.pnu.ac.ir/ Digital and Smart Libraries Research en daily 1 Sat, 06 Sep 2025 00:00:00 +0330 Sat, 06 Sep 2025 00:00:00 +0330 https://lib.journals.pnu.ac.ir/article_12196.html From the past until now, achieving organizational effectiveness has been the goal of all organizations. Achieving this requires the existence of several factors such as professional ethics in the organization, the establishment of organizational intelligence and knowledge management. The purpose of this study was to design and test a causal model of organizational effectiveness based on professional ethics and organizational intelligence with the mediating role of knowledge management in primary school teachers. This research is an applied research in terms of purpose and a descriptive correlation in terms of data collection method. The statistical population of this study includes all primary school teachers in Sahneh city with 199 teachers who were selected as a sample by simple random sampling method and Morgan table using 150 people. Data collection tools included: Parsons Organizational Effectiveness Questionnaire (1969); Qasemzadeh's professional ethics (2014); Albrecht (2003) Organizational Intelligence and Lawson (2003) Knowledge Management. Data analysis was performed using Smart PLS software. Findings showed that professional ethics, organizational intelligence and knowledge management have a direct effect on organizational effectiveness. Professional ethics and organizational intelligence also have a direct impact on knowledge management. The indirect effect of professional ethics and organizational intelligence with the mediating role of knowledge management on organizational effectiveness is significant. In general, it is concluded that the designing and testing of a causal model of organizational effectiveness based on professional ethics and organizational intelligence with the mediating role of knowledge management fits with the experimental model. https://lib.journals.pnu.ac.ir/article_12568.html The present study aimed to examine the various dimensions of artificial intelligence (AI) literacy among graduate students at Payame Noor University, Mashhad. The statistical population included 788 students, of whom 260 were selected through simple random sampling. Data were collected using a researcher-made 36-item questionnaire covering six components: "awareness and foundational knowledge," "practical skills," "interdisciplinary literacy," "ethics and challenges," "continuous learning," and "influence and emotion management," with a five-point Likert scale ranging from "very low" to "very high." The validity and reliability of the instrument were confirmed by experts and a Cronbach's alpha of 0.948.Findings indicated that the overall AI literacy level of students was in the "above average" range. The highest scores were observed in the "influence and emotion management" component, while the lowest were in "practical skills," highlighting a gap between theoretical knowledge and practical capabilities. Comparative analyses by gender and academic degree revealed that male and doctoral students scored higher in most components compared to female and master's students, although no significant difference was found in practical skills, emphasizing the need for targeted practical training programs.This study provides a comprehensive and multidimensional overview of AI literacy, identifies differences by gender and academic level, and underscores the importance of practical education and structured program planning to enhance students' applied competencies. These findings can inform educational policy-making and improve university training programs. https://lib.journals.pnu.ac.ir/article_13000.html Introduction Universal access to information and communication technologies (ICT) has become one of the principal responsibilities of public libraries in advancing sustainable development, lifelong learning, digital inclusion, and information justice. As public libraries increasingly expand their digital infrastructure and online services, ensuring equitable access to information resources for all members of society has become a strategic priority. Reliable evaluation frameworks are therefore essential for assessing service quality, identifying gaps in accessibility, and supporting evidence-based decision-making. Although international organizations such as IFLA and UNESCO have introduced general guidelines for inclusive library services, no comprehensive and validated framework has been specifically developed to evaluate the quality of universal access to information services and ICT in public libraries across the Middle East. This study addresses this gap by identifying and validating a comprehensive set of indicators and evaluation criteria tailored to the regional context.   Methodology This applied research employed a descriptive–exploratory design. Data collection began with a comprehensive review of printed and electronic literature, international standards, policy documents, professional guidelines, and previous empirical studies related to public libraries, universal access, digital inclusion, ICT accessibility, and information equity. The preliminary indicators extracted from the literature were subsequently evaluated using the Delphi technique. A panel of experts specializing in library and information science, public library management, and information systems participated in multiple Delphi rounds. During each round, participants assessed the relevance, clarity, applicability, and importance of the proposed indicators. The iterative Delphi process continued until a satisfactory level of consensus was achieved, resulting in the validation of a comprehensive framework for evaluating the quality of universal access in public libraries.   Findings The Delphi process confirmed that the quality of universal access to information services and ICT in public libraries is represented by four interrelated dimensions: user empowerment, access to information resources, reduction of the digital divide, and information equity. Within the user empowerment dimension, information literacy, digital literacy, lifelong learning, artificial intelligence literacy, and digital skills development were identified as the most influential indicators for strengthening users' capabilities and enhancing their effective participation in the digital society. The access to information resources dimension emphasized unrestricted and equitable access to scientific, educational, governmental, agricultural, health-related, and specialized information resources, alongside digital collections, electronic databases, online reference services, and remote information services that support informed decision-making and community development. The reduction of the digital divide dimension highlighted the importance of strengthening digital infrastructure through reliable high-speed Internet connectivity, modern computer facilities, assistive technologies, accessible digital platforms, continuous technological innovation, and user-centered digital services. These indicators contribute to minimizing disparities in access to information technologies among different population groups. The fourth dimension, information equity, focused on ensuring inclusive and equitable services for disadvantaged and vulnerable populations, including people with disabilities, older adults, women, children, immigrants, rural communities, and economically marginalized groups. Equal opportunities to access information regardless of demographic, social, economic, or physical characteristics were identified as essential indicators of high-quality public library services. Collectively, these validated indicators provide a multidimensional perspective for evaluating universal access and demonstrate the close relationship between digital inclusion, information justice, technological accessibility, and sustainable public library development.   Discussion and Conclusion The validated framework developed in this study offers a comprehensive and evidence-based model for evaluating the quality of universal access to information services and ICT in public libraries throughout the Middle East. By integrating internationally recognized principles with the specific cultural, social, and technological characteristics of the region, the framework addresses an important gap in the existing literature and provides a practical instrument for systematic library assessment. The proposed indicators enable policymakers, public library administrators, and decision-makers to evaluate current services, identify strengths and weaknesses, prioritize strategic investments, improve technological infrastructure, and formulate evidence-based policies that promote equitable access to information. Furthermore, the framework supports digital inclusion initiatives, strengthens information equity, and contributes to achieving broader sustainable development goals through more inclusive public library services. From a theoretical perspective, this research expands the literature on universal access by presenting a regionally validated evaluation model that combines concepts of digital inclusion, information justice, ICT accessibility, and user empowerment. The framework also provides a foundation for future comparative studies, benchmarking initiatives, and the development of standardized assessment instruments applicable to public library systems in the Middle East and other developing regions.   https://lib.journals.pnu.ac.ir/article_13010.html With the rapid growth of digital resources and the increasing volume of information in digital libraries, users face significant challenges in locating relevant materials quickly, accurately, and in a personalized manner. Traditional search and filtering approaches, which primarily rely on keyword matching and limited user preference analysis, often fail to fully satisfy users’ information needs. Consequently, intelligent recommender systems have gained considerable attention as an effective solution for improving access to resources and enhancing user experience. This study proposes a hybrid recommender system based on behavioral and content-based data, consisting of data preprocessing, two recommendation engines (content-based and collaborative filtering), and an intelligent aggregation layer for combining recommendation outputs. Behavioral data were extracted from the Book-Crossing dataset, while content-based information was obtained from both Book-Crossing and CiteULike datasets to model user preferences and resource characteristics. The performance of the proposed model was evaluated using precision, recall, coverage, diversity, and an intelligent recommendation quality score. Experimental results demonstrated that the hybrid model outperformed single-strategy recommenders, achieving a precision of 0.75, recall of 0.72, and coverage of 0.68. Furthermore, the proposed approach reduced common recommender system challenges such as the cold-start problem and popularity bias while increasing recommendation diversity and improving user experience. The findings indicate that integrating data mining techniques with semantic content analysis provides an effective framework for developing advanced recommender systems in digital library environments.