Evaluating the implementations of big data analytics in academic libraries: a structural equation model-based approach

Purpose The rapid evolution of technological infrastructure and analytical capabilities has facilitated the integration of big data analytics (BDA) across various sectors. This study aims to investigate the suitability of implementing BDA within academic libraries, addressing the demanding need for effective data utilization in contemporary educational environments. Design/methodology/approach The research is grounded in five critical components: data-driven culture, organizational infrastructure, employee responsibilities, management capabilities and the successful deployment of technology for BDA. An extensive literature review led to the development of a Likert scale-based questionnaire distributed on social media to collect data from university librarians in Pakistan. The authors were able to collect the data from 211 librarians. Descriptive statistics were employed to analyze the variables, while confirmatory factor analysis (CFA) was conducted using the AMOS to validate the research model. Findings The findings from the measurement model reveal significant positive correlations among all five components, underscoring their collective importance in facilitating the implementation of BDA. This formation is essential for addressing the evolving needs and academic requirements of users in the context of big data in a digital environment. Research limitations/implications The study acknowledges limitations about its focus on a single country's perspective, which may affect the generalizability of the findings regarding the implementation process of BDA in academic libraries. Originality/value This research contributes to the existing body of knowledge by highlighting the practices and capabilities of librarians in the era of big data as well as the requisite organizational infrastructure for the effective implementation of analytics in academic libraries.