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شناسایی عوامل مؤثر بر طراحی و کاربست هوش مصنوعی در کتابخانههای دانشگاهی ایران: یک مطالعه کیفی مبتنی بر نظریه دادهبنیاد | ||
| پژوهش های کتابخانه های دیجیتالی و هوشمند | ||
| مقاله 4، دوره 12، شماره 4 (پیاپی 47)، بهمن 1404، صفحه 49-72 اصل مقاله (2.68 M) | ||
| نوع مقاله: مقاله پژوهشی | ||
| شناسه دیجیتال (DOI): 10.30473/mrs.2026.79221.1711 | ||
| نویسندگان | ||
| سیمن حداد عراقی1؛ میترا قیاسی* 2؛ سید علی اصغر رضوی3 | ||
| 1دانشجوی دکتری، گروه علم اطلاعات و دانش شناسی،واحد بابل، دانشگاه آزاد اسلامی، بابل، ایران | ||
| 2دانشیار، گروه علم اطلاعات و دانششناسی، واحد بابل، دانشگاه آزاد اسلامی، بابل، ایران. | ||
| 3دانشیار، گروه علم اطلاعات و دانششناسی، واحد بابل، دانشگاه آزاد اسلامی، بابل، ایران | ||
| چکیده | ||
| هوش مصنوعی ظرفیت گستردهای برای تحول در خدمات، فرایندها و تصمیمگیریهای کتابخانههای دانشگاهی فراهم کرده است. با این حال، بخش عمده پژوهشهای پیشین بر شناسایی کاربردها، بررسی نگرش کاربران و کتابداران یا سنجش آمادگی برای پذیرش این فناوری متمرکز بودهاند و هنوز تبیین جامعی از چگونگی تعامل عوامل مؤثر بر طراحی و کاربست هوش مصنوعی، بهویژه در بستر کتابخانههای دانشگاهی ایران، ارائه نشده است. ازاینرو، پژوهش حاضر با هدف تبیین مدل عوامل مؤثر بر طراحی و کاربست هوش مصنوعی در کتابخانههای دانشگاهی ایران انجام شد. این پژوهش از نظر هدف، کاربردی و از نظر رویکرد، کیفی است و با استفاده از روش نظریه دادهبنیاد انجام شد. دادهها از طریق مصاحبههای نیمهساختاریافته با ۳۵ مشارکتکننده که به صورت هدفمند انتخاب شدند، شامل ۱۲ متخصص نرمافزارهای کتابخانهای، ۱۴ عضو هیئت علمی علم اطلاعات و دانششناسی و ۹ مدیر کتابخانههای دانشگاهی گردآوری و با استفاده از کدگذاری باز، محوری و انتخابی تحلیل شدند. اشباع نظری همزمان با گردآوری و تحلیل دادهها و بر اساس روند تجمیع شده سه گروه مشارکتکننده ارزیابی شد؛ بهگونهای که از مشارکتکننده سیام به بعد، مفهوم یا رابطه نظری جدیدی به مدل افزوده نشد و مصاحبههای بعدی عمدتاً نقش تأییدی و تکمیلی داشتند. یافتهها نشان داد که آمادگی فناورانه، دادهای و معماری سامانههای کتابخانهای بهعنوان شرط علّی اصلی، بنیان طراحی و کاربست هوش مصنوعی را شکل میدهد. آمادگی انسانی و حرفهای کتابداران، حمایت سازمانی و مدیریت تغییر و پایداری اقتصادی بهعنوان شرایط زمینهای، بستر تحقق این فرایند را فراهم میکنند؛ درحالیکه مشروعیت علمی، اخلاق داده و حکمرانی هوش مصنوعی بهعنوان شرایط مداخلهگر، کیفیت، اعتبار و حدود استفاده از این فناوری را تنظیم میکنند. همچنین، راهبردهای تدریجی، دادهمحور و مسئولانه مسیر پیادهسازی را شکل داده و به کاربست عملی هوش مصنوعی در خدمات و فرایندهای کتابخانهای و بروز پیامدهای مثبت کارکردی، مدیریتی و تحولی منجر میشوند. مدل حاصل نشان میدهد که طراحی و کاربست هوش مصنوعی در کتابخانههای دانشگاهی صرفاً یک مسئله فناورانه نیست، بلکه فرایندی چندبعدی و اجتماعی ـ فناورانه است که تحقق اثربخش آن مستلزم هماهنگی میان زیرساخت و داده، منابع انسانی، ظرفیتهای سازمانی و اقتصادی و الزامات علمی و اخلاقی است. | ||
| کلیدواژهها | ||
| هوش مصنوعی؛ کتابخانههای دانشگاهی؛ نظریه دادهبنیاد؛ کتابداران؛ طراحی و کاربست هوش مصنوعی | ||
| عنوان مقاله [English] | ||
| Identifying the Factors Influencing the Design and Application of Artificial Intelligence in Academic Libraries in Iran: A Qualitative Grounded Theory Study | ||
| نویسندگان [English] | ||
| Simin Haddad1؛ MItra Ghiasi2؛ Seyed Ali Asghar Razavi3 | ||
| 1Ph.D Student, Department of Knowledge and Information Science, Bab.C, Islamic Azad University, Babol, Iran | ||
| 2Associate Professor, Department of Knowledge and Information Science, Bab.C, Islamic Azad University, Babol, Iran | ||
| 3Associate Professor, Department of Knowledge and Information Science, Bab.C, Islamic Azad University, Babol, Iran | ||
| چکیده [English] | ||
| Introduction Artificial intelligence (AI) has created significant opportunities for transforming information services, operational processes, professional practices, and decision-making in academic libraries. However, the effective design and application of AI in library environments cannot be reduced to the adoption of isolated technological tools. Previous studies have largely focused on identifying AI applications, examining librarians’ or users’ attitudes, assessing technological readiness, or reviewing emerging trends. A comprehensive explanation of how technological, human, organizational, economic, scientific, and ethical factors interact in the design and implementation of AI in academic libraries remains limited, particularly in the Iranian context. Therefore, this study aimed to develop a model of factors influencing the design and application of artificial intelligence in academic libraries in Iran. Methodology This study was applied in terms of purpose and qualitative in terms of research approach, conducted using grounded theory methodology. Data were collected through in-depth, semi-structured interviews with 35 purposively selected participants from three professional and academic groups: 12 experts in library software and technological systems, 14 faculty members in Library and Information Science, and 9 academic library managers. This selection aimed to provide a multidimensional understanding by covering technological/data-related, scientific/professional, and managerial/organizational perspectives. Data were analyzed through open, axial, and selective coding. In open coding, initial concepts were extracted and consolidated. In axial coding, categories were organized according to the paradigmatic logic of grounded theory (causal, contextual, and intervening conditions, action/interaction strategies, the central phenomenon, and consequences). In selective coding, main categories were integrated around the core phenomenon to develop the final theoretical model. Theoretical saturation was assessed concurrently; by the 30th participant, no new fundamental concepts emerged, and subsequent interviews served a confirmatory function to stabilize the conceptual structure. Findings The findings showed that technological and data readiness, along with the architecture of library systems, constituted the primary causal condition for AI design and application. The availability of high-quality data, appropriate metadata structures, interoperability, open/connectable system architectures, and adequate technological infrastructure formed the foundation for AI-enabled services. Human and professional readiness of librarians, organizational support and change management, and economic sustainability emerged as major contextual conditions. Specifically, AI literacy, professional competencies, continuous training, acceptance of technological change, managerial commitment, strategic orientation, organizational coordination, and access to sufficient financial resources were identified as critical factors for creating an enabling environment. Scientific legitimacy, data ethics, and AI governance functioned as important intervening conditions, influencing the quality, credibility, and boundaries of AI use. Consequently, concerns regarding transparency, explainability, privacy, accountability, algorithmic bias, professional judgment, and human oversight were integral to the implementation process. Discussion and Conclusion The analysis indicated that gradual, data-driven, problem-oriented, and responsible implementation strategies provide the pathway for translating these conditions into the actual use of AI in library services. Practical applications include intelligent reference services, user behavior analysis, personalized recommendations, intelligent resource organization, metadata quality control, data-driven collection management, and decision support. When implemented under appropriate conditions, AI can generate positive functional, managerial, and transformational outcomes, including improved service quality, speed, accuracy, user experience, operational efficiency, and a redefined role for academic libraries in the broader scholarly ecosystem. The proposed model demonstrates that AI implementation in academic libraries is not merely a technological modernization project but a multidimensional socio-technical transformation process, relying on the alignment of data infrastructure, professional capabilities, organizational readiness, economic resources, and ethical governance. This context-sensitive framework can support managers, policymakers, developers, and professionals in planning responsible and sustainable AI-based library services. | ||
| کلیدواژهها [English] | ||
| Artificial Intelligence, Academic Libraries, Grounded Theory, Librarians, AI Design and Application | ||
| مراجع | ||
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Abayomi, O. K., Adenekan, F. N., Abayomi, A. O., Ajayi, T. A., & Aderonke, A. O. (2021). Awareness and perception of artificial intelligence in the management of university libraries in Nigeria. Journal of Interlibrary Loan, Document Delivery & Electronic Reserve, 29(1–2), 13–28. https://doi.org/10.1080/1072303X.2021.1918602 Ajani, Y. A., Tella, A., Salawu, K. Y., & Abdullahi, F. (2022). Perspectives of librarians on awareness and readiness of academic libraries to integrate artificial intelligence for library operations and services in Nigeria. Internet Reference Services Quarterly, 26(4), 213–230. https://doi.org/10.1080/10875301.2022.2086196 Asemi, A., Ko, A., & Nowkarizi, M. (2020). Intelligent libraries: a review on expert systems, artificial intelligence, and robot. Library Hi Tech, 39(2), 412–434. https://doi.org/10.1108/lht-02-2020-0038 Asemi, A., Ko, A., & Nowkarizi, M. (2021). Intelligent libraries: a review on expert systems, artificial intelligence, and robot. Library Hi Tech, 39(2), 412-434. https://doi.org/10.1108/LHT-02-2020-0038 Association of College and Research Libraries. (2025, October). AI competencies for academic library workers. American Library Association. Ayinde, L., Ebiefung, R., & Oladokun, B. D. (2026). Adoption of artificial intelligence in academic libraries: A systematic review of current practices, challenges, and research opportunities. The Journal of Academic Librarianship, 52(1), 103185. DOI: 10.1016/j.acalib.2025.103185 Azimi, M. H., Hosseinizadeh, F. (2022). Studying the capabilities of domestic companies with artificial intelligence-based products with usability in librarianship activities. Science and Technology Information Management, 8(2), 405–426. (In Persian) Doi: 10.22091/stim.2021.7040.1597 Azimi, M. H., Mohammadi, Z., & Rafieinasab, F. (2022). A Survey of Academic Librarians' Perceptions of Artificial Intelligence Technology: A Case Study (Librarians of Shahid Chamran University of Ahvaz and Jundishapur University of Medical Sciences). Library and Information Science, 24(4), 154–177. (In Persian) Doi: 10.30481/lis.2021.286969.1831 Azimi, M. H., Nematollahi, Z., & Dakhesh, S. (2022). Identifying and categorizing the dimensions and applications of artificial intelligence in library services using a meta-synthesis method. Library and Information Science, 25(3), 5–35. (In Persian) Doi: 10.30481/lis.2021.292701.1847 Barney, J. (1991). Firm resources and sustained competitive advantage. Journal of Management, 17(1), 99–120. https://doi.org/10.1177/014920639101700108 Bogonko, B. M., Nyakweba, I., Makanda, N. N., & Makori, V. N. (2025). A framework for AI-driven data governance in academic libraries. Edulib, 15(2), 199-218. https://doi.org/10.17509/edulib.v15i2.87417.g34547 Borgohain, D. J., Bhardwaj, R. K., & Verma, M. K. (2024). Mapping the literature on the application of artificial intelligence in libraries: A scientometric analysis. Library Hi Tech, 42(1), 149–179. https://doi.org/10.1108/LHT-07-2022-0331 Çakmak, T., & Eroğlu, Ş. (2024). The use of artificial intelligence in university libraries in Türkiye: Practices, and perspectives of library directors. Information Development, 41(3), 642–655. https://doi.org/10.1177/02666669241264743 Concha, K. M., Zenteno, F. P., & Alfaro, J. T. (2024). Use of artificial intelligence in libraries a systematic review, 2019-2023. South African Journal of Library and Information Science. https://doi.org/10.7553/90-2-2387 Cox, A. M. (2023). How artificial intelligence might change academic library work: Applying the competencies literature and the theory of the professions. Journal of the Association for Information Science and Technology, 74(3), 367–380. https://doi.org/10.1002/asi.24635 Cox, A. M., Pinfield, S., & Rutter, S. (2019). The intelligent library: Thought leaders’ views on the likely impact of artificial intelligence on academic libraries. Library Hi Tech, 37(3), 418–435. https://doi.org/10.1108/LHT-08-2018-0105 Das, R. K., & Islam, M. S. (2021). Application of artificial intelligence and machine learning in libraries: A systematic review. arXiv. https://doi.org/10.48550/arXiv.2112.04573 Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319–340. https://doi.org/10.2307/249008 Esh, M., & Ghosh, S. (2024). AI in Libraries: Subject Mapping and Interpreting Bibliometric Laws with Contemporary Metrics. The Serials Librarian, 85(5-6), 99–116. https://doi.org/10.1080/0361526x.2024.2444288 Farkhari, F., Cheshmeh Sohrabi, M., Karshenas, H., & Azimi, M. H. (2024). Exploring the main dimensions and components in designing and implementing smart libraries. Information Research and Library Science, 14(1), 5–28. (In Persian) Floridi, L. (2023). The ethics of artificial intelligence: Principles, challenges, and opportunities. Oxford University Press. Floridi, L., & Cowls, J. (2022). A unified framework of five principles for AI in society. Machine learning and the city: Applications in architecture and urban design. Machine Learning and the City, 535–545. https://doi.org/10.1002/9781119815075.ch45 Fu, H., Cao, F., Li, Y., & Ghosh, S. (2025). Readiness in Libraries: A Technology–organization–environment framework for Action. Proceedings of the Association for Information Science and Technology, 62(1), 1448–1450. Portico. https://doi.org/10.1002/pra2.1431 Gholamhosseinnejad, S. (2024). Implementation of artificial intelligence in library services: A review of current perspectives and challenges in developing countries. New Information and Information Literacy Skills, 24(53), 2–8. (In Persian) Goodhue, D. L., & Thompson, R. L. (1995). Task-technology fit and individual performance. MIS Quarterly, 19(2), 213–236. https://doi.org/10.2307/249689 Harisanty, D., Anna, N. E. V., Putri, T. E., Firdaus, A. A., & Noor Azizi, N. A. (2022). Leaders, practitioners and scientists’ awareness of artificial intelligence in libraries: a pilot study. Library Hi Tech, 42(3), 809–825. https://doi.org/10.1108/lht-10-2021-0356 Huang, Y., Cox, A. M., & Cox, J. (2023). Artificial intelligence in academic library strategy in the United Kingdom and the Mainland of China. The Journal of Academic Librarianship, 49(6), 102772. https://doi.org/10.1016/j.acalib.2023.102772 Islam, M. N., Ahmad, S., Aqil, M., Hu, G., Ashiq, M., Abusharhah, M. M., & Saky, S. A. T. M. (2025). Application of artificial intelligence in academic libraries: A bibliometric analysis and knowledge mapping. Discover Artificial Intelligence, 5(1), Article 59. https://doi.org/10.1007/s44163-025-00248-4 Kalbande, D., Yuvaraj, M., Verma, M. K., A., S., Suradkar, P., & Chavan, S. (2024). Exploring the Integration of Artificial Intelligence in Academic Libraries: A Study on Librarians’ Perspectives in India. Open Information Science, 8(1). https://doi.org/10.1515/opis-2024-0006 Khademizadeh, S., & Shekari, M. R. (2025). Artificial intelligence literacy: The necessity of curriculum transformation and the role of librarians in its education. Information Processing and Management Research, 40(3), 825–864. https://doi.org/10.22034/jipm.2025.2047608.1869 (In Persian) Li, L. (2024). Application of Artificial Intelligence-Driven Federated Learning Based on Machine Learning and Deep Learning in Medicine . Federated Learning - A Systematic Review. https://doi.org/10.5772/intechopen.1008185 Li, L., & Coates, K. (2024). Academic library online chat services under the impact of artificial intelligence. Information Discovery and Delivery, 53(2), 192–205. https://doi.org/10.1108/idd-11-2023-0143 Lin, X., Sun, Y., Zhang, Y., & MR, K. (2023, February). Application of ai in library digital reading promotion service. In 2023 IEEE International Conference on Integrated Circuits and Communication Systems (ICICACS) (pp. 1-6). IEEE. Lo, L. S. (2024). Transforming academic librarianship through AI reskilling: Insights from the GPT-4 exploration program. The Journal of Academic Librarianship, 50(3), 102883. https://doi.org/10.1016/j.acalib.2024.102883 Lo, L. S. (2024a). Evaluating AI literacy in academic libraries: A survey study with a focus on U.S. employees. College & Research Libraries, 85(5), 635–668. https://doi.org/10.5860/crl.85.5.635 Mannheimer, S., Rossmann, D., Clark, J., Shorish, Y., Bond, N., Scates Kettler, H., Sheehey, B., & Young, S. W. (2024). Introduction to the special issue: Responsible AI in libraries and archives. Journal of eScience Librarianship, 13(1), e860. https://doi.org/10.7191/jeslib.860 Mcknight, D. H., Carter, M., Thatcher, J. B., & Clay, P. F. (2011). Trust in a specific technology. ACM Transactions on Management Information Systems, 2(2), 1–25. https://doi.org/10.1145/1985347.1985353 Mitha, S. B., & Omarsaib, M. (2024). RETRACTED: Emerging technologies and higher education libraries: a bibliometric analysis of the global literature. Library Hi Tech, 43(2-3), 1248–1270. https://doi.org/10.1108/lht-02-2024-0105 Molaudzi, A. I., & Marutha, N. (2024). Contributory factors to attitudes towards the adoption of artificial intelligence technology in public academic libraries in South Africa. Information Development, 41(3), 615–625. https://doi.org/10.1177/02666669241304704 Molaudzi, A. I., & Ngulube, P. (2025). Use of artificial intelligence innovations in public academic libraries. IFLA Journal, 51(3), 660–670. https://doi.org/10.1177/03400352241301780 Murillo, A., & Yuan, X. (2021). Perceptions of artificial intelligence: A survey of academic librarians in Canada and the United States. The Journal of Academic Librarianship, 47(1), 102270. https://doi.org/10.1016/j.acalib.2020.102270 Ngulube, P., & Vincent Mosha, N. F. (2024). Integrating artificial intelligence-based technologies ‘safely’ in academic libraries: An overview through a scoping review. Technical Services Quarterly, 42(1), 46–67. https://doi.org/10.1080/07317131.2024.2432093 Okunlaya, R. O., Syed Abdullah, N., & Alias, R. A. (2022). Artificial intelligence (AI) library services innovative conceptual framework for the digital transformation of university education. Library Hi Tech, 40(6), 1869–1892. https://doi.org/10.1108/LHT-07-2021-0242 Palaska, A. (2025). Enhancing metadata management in digital libraries using artificial intelligence: A systematic literature review (Master’s thesis). University of Borås. Panda, S., & Chakravarty, R. (2022). Adapting intelligent information services in libraries: A case of smart AI chatbots. Library Hi Tech News, 39(1), 12–15. https://doi.org/10.1108/LHTN-11-2021-0081 Rezaeinour, J., Karimian, R., & Norouzi, Y. (2025). Identifying challenges and opportunities facing special libraries in adopting artificial intelligence. Digital and Smart Libraries Research, 11(1), 52–64. (In Persian) Shahzad, K., Khan, S. A., Iqbal, A., & Javeed, A. M. D. (2024). Identifying university librarians’ readiness to adopt artificial intelligence (AI) for innovative learning experiences and smart library services: an empirical investigation. Global Knowledge, Memory and Communication, 75(1-2), 646–668. https://doi.org/10.1108/gkmc-12-2023-0496 Subaveerapandiyan, A., & Gozali, A. A. (2024). AI in Indian Libraries: Prospects and Perceptions from Library Professionals. Open Information Science, 8(1). https://doi.org/10.1515/opis-2022-0164 Teece, D. J. (2007). Explicating dynamic capabilities: the nature and microfoundations of (sustainable) enterprise performance. Strategic Management Journal, 28(13), 1319–1350. https://doi.org/10.1002/smj.640 Tornatzky, L. G., & Fleischer, M. (1990). The processes of technological innovation. Lexington Books. Vasishta, P., Dhingra, N., & Vasishta, S. (2024). RETRACTED: Application of artificial intelligence in libraries: a bibliometric analysis and visualisation of research activities. Library Hi Tech, 43(2-3), 693–710. https://doi.org/10.1108/lht-12-2023-0589 Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User acceptance of information technology: Toward a unified view. MIS Quarterly, 27(3), 425–478. Weiner, B. J. (2009). A theory of organizational readiness for change. Implementation Science, 4(1). https://doi.org/10.1186/1748-5908-4-67 | ||
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