Measuring smart library maturity: evaluation methods and case studies of university libraries in China

Purpose Amid deepening digital transformation and intelligence advances, emerging technologies are reshaping libraries globally, yet regional disparities in priorities and insufficient theoretical development regarding core features and evaluative tools persist. This study aims to address these gaps by constructing a maturity evaluation indicator system and method to facilitate smart library development. Design/methodology/approach Content mining was first employed to delineate smart library connotation and components. Building on prior research, object-oriented analysis elicited initial indicators, subsequently refined through expert interviews. Analytic hierarchy process (AHP) and expert scoring determined indicator weights. A maturity model integrated with triangular fuzzy functions formulated the evaluation methodology. Empirical validation was conducted across five Chinese university libraries. Findings The developed indicator system encompasses 4 evaluation elements, 12 first-level indicators and 48 second-level indicators. Application to empirical cases confirmed the scientific validity and operational feasibility of the proposed evaluation model. Originality/value This study creatively integrates tools from information science, systems engineering and management science to design a validated research scheme. It proposes a systematic evaluation indicator system, establishes a maturity model with triangular fuzzy calculation and assesses five Chinese university libraries, offering a valuable methodological paradigm for smart library evaluation.