A Comprehensive Bibliometrics Analysis and Service Model for Academic Libraries: Collaboration, Training, and Evidence-Based Decision-Making

Academic libraries have undergone significant transformations in recent years, expanding their service scope to include bibliometrics metrics and research impact services. In this article, we propose a comprehensive bibliometrics analysis and service model for academic libraries by conducting an extensive review of past studies and current international practices. The study aims to address three research questions: (1) What are the bibliometrics services practices offered by academic libraries around the world? (2) How do academic libraries and other units collaborate in offering bibliometrics services? (3) What model can be concluded from above for establishing or improving bibliometrics services in academic libraries with collaboration? The article begins with a literature review, followed by a methodology section detailing the search strategies and review process. The findings reveal the coverage, usage, and limitations of existing service models. Based on these findings, a recommended service model is proposed, addressing challenges and driving forces in its implementation. The recommended model includes a collaborative approach between academic libraries and other units, such as research offices and IT departments, to provide comprehensive bibliometrics services. The model also emphasizes the importance of training and support for librarians and researchers to effectively use bibliometrics tools and metrics to help academic libraries establish or improve their bibliometrics services, providing valuable insights into the impact of research and facilitating evidence-based decision-making. Collaboration between academic libraries and other internal and external stakeholders is crucial for the success of bibliometrics services, and ongoing training and support are essential to ensure that librarians and researchers can effectively use bibliometrics tools and metrics. Future research can further explore the effectiveness of the proposed model and identify areas for improvement.