Investigating the Smartness Status of Academic Libraries in Kermanshah Province from the Perspective of Library Staff

Introduction
Academic libraries are key infrastructures for supporting education and research, and the spread of digital technologies has pushed them toward smart transformation. Smart libraries use tools such as the Internet of Things (IoT), Artificial Intelligence (AI) and Radio Frequency Identification (RFID) to provide continuous, efficient and personalized services. In many developed countries, this transformation has advanced, but in developing countries such as Iran, it is slowed by limited budgets, lack of skilled staff and weak infrastructures. This study examines five components of smart libraries – smart technology, smart infrastructure, smart services, smart personnel and smart regulations to evaluate the smartness status of academic libraries in Kermanshah Province from the perspective of library staff.
 
Methodology
 This research is applied research and uses a descriptive–survey design. The statistical population consisted of 50 employees working in academic libraries of Kermanshah Province, all included by census. Data were collected through the questionnaire developed by Jadhav and Shenoy (2020), which measures the five smart components on a five point Likert scale. Descriptive statistics (frequency and percentage for demographic variables and mean and standard deviation for the components) were calculated in SPSS 26. In the inferential section, a one sample t test compared the mean of each component with the theoretical midpoint of 3. The Kolmogorov–Smirnov test checked normality, and according to the distribution of data, the Independent T Test, Mann–Whitney test, ANOVA, Kruskal–Wallis test and Pearson correlation examined relationships between smart components and demographic variables such as gender, age, education level, field of study and work experience.
 
Findings
 The results show that four of the five components are below the expected average level. The mean scores for smart technology, smart infrastructure, smart services and smart regulations are all significantly lower than 3, indicating weaknesses in technological equipment, physical conditions, service innovation and regulatory frameworks. Only the smart personnel component is at an average level, which suggests that staff competence and readiness are acceptable. Analysis of demographic variables reveals no significant differences in any smart component with respect to gender, field of study, education level or work experience. Age is the only distinguishing factor: employees aged 31–40 years obtain higher scores on the smart personnel component than those in the 20–30 و 41–50 age groups, while there is no significant difference between the youngest and oldest groups.
 
Discussion and Conclusion
Overall, academic libraries in Kermanshah Province are still far from the desired level of smartness. Technology, infrastructure, services and regulations are in an unfavorable state, whereas only the human resources dimension has reached a moderate level. This pattern shows that although librarians and staff have basic competencies, their potential is limited by outdated infrastructures and underdeveloped governance. The lack of significant differences across most demographic variables suggests that the shortcomings are systemic rather than individual. To move toward smart academic libraries, decision makers should design a roadmap for smart library development, secure funding, prioritize scalable digital and web based services, provide targeted training for different age groups and update regulations related to data security, privacy and smart service.