شناسایی عوامل مؤثر بر طراحی و کاربست هوش مصنوعی در کتابخانه‌های دانشگاهی ایران: یک مطالعه کیفی مبتنی بر نظریه داده‌بنیاد

نوع مقاله : مقاله پژوهشی

نویسندگان

1 دانشجوی دکتری، گروه علم اطلاعات و دانش شناسی،واحد بابل، دانشگاه آزاد اسلامی، بابل، ایران

2 دانشیار، گروه علم اطلاعات و دانش‌شناسی، واحد بابل، دانشگاه آزاد اسلامی، بابل، ایران.

3 دانشیار، گروه علم اطلاعات و دانش‌شناسی، واحد بابل، دانشگاه آزاد اسلامی، بابل، ایران

10.30473/mrs.2026.79221.1711

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

موضوعات

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 Haddad 1
  • MItra Ghiasi 2
  • Seyed Ali Asghar Razavi 3
1 Ph.D Student, Department of Knowledge and Information Science, Bab.C, Islamic Azad University, Babol, Iran
2 Associate Professor, Department of Knowledge and Information Science, Bab.C, Islamic Azad University, Babol, Iran
3 Associate 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

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  • تاریخ دریافت: 05 تیر 1405
  • تاریخ بازنگری: 17 مرداد 1405
  • تاریخ پذیرش: 20 شهریور 1405
  • تاریخ اولین انتشار: 20 شهریور 1405

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