Smart Library Research: A Bibliometric Analysis of Publication Trends, Citation Impact, and Knowledge Structure
DOI:
https://doi.org/10.47134/jip.v3i1.5965Keywords:
Smart Library, Intelligent Library, Library 4.0, Internet Of Things, Bibliometric Analysis, ScientometricAbstract
The rapid integration of emerging technologies into library ecosystems has given rise to the smart library concept, a transformative paradigm leveraging artificial intelligence (AI), the Internet of Things (IoT), big data, and intelligent systems to enhance information services and operational efficiency. Despite growing scholarly interest, a comprehensive bibliometric mapping of this research landscape remains limited. This study addresses the gap by conducting a systematic bibliometric analysis of peer-reviewed articles and review papers indexed in Web of Science and Scopus, examining twelve dimensions including publication trends, citation impact, journal quartile distribution, source productivity, highly cited papers, authorship patterns, institutional and national contributions, and keyword co-occurrence structures. Data were retrieved using a structured keyword search, filtered to English-language articles and reviews, and deduplicated prior to analysis using BiblioSpy® as the primary analytical platform. The findings reveal a sustained upward publication trajectory from 2017 to 2026, with peak citation activity between 2019 and 2022 and Relative Citation Impact (RCI) values substantially above the global benchmark during this period. Library Hi Tech, Library Hi Tech News, and The Electronic Library dominated publication output, while China, India, and Pakistan led national productivity. Allama Iqbal Open University and Shahzad, Khurram were the most productive institution and author respectively. Rafique et al. (2020) was the most highly cited work with 412 total citations, with AI emerging as the field's dominant thematic strand. Keyword analysis revealed a coherent thematic core anchored by AI, IoT, machine learning, and library 4.0, with emerging terms pointing toward generative AI and large language model applications.
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Copyright (c) 2026 Mohamad Noorman Masrek, Hazila Timan, Fadhilnor Rahmad, Abdi Mubarak Syam, Setiawan

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