Continuance intention to use the self-built e-reserve databases (SED) in Chinese academic libraries: An integrative model

The self-built e-reserve database (SED) has still been considered an essential e-reserve service in Chinese academic libraries to resolve the issue of insufficient library copies and to support the future digital learning model. This study aims to examine the factors influencing users’ continuance intention to use SED in university libraries based on an integrative model that includes the Information System Success Model (ISSM), the Technology Acceptance Model (TAM), the Post-Acceptance Model of Information System Continuance, and the Stimulus-Organism-Response (S-O-R) model. A total of 384 valid responses were collected through a questionnaire-based survey across Chinese colleges and universities. The findings confirmed the direct influence of perceived usefulness (PU), perceived ease of use (PEOU), and personal innovativeness in IT(PIIT) on continuance intention to use SED. Additionally, the study highlighted the different mediating roles of the organism (i.e. PEOU, PU, and PIIT) between the stimulus (i.e. information quality, system quality, service information quality, and social influence) and continuance intention. Specifically, information quality and social influence were identified as the two primary antecedent variables influencing continuance intention through the mediating effects of PU and PIIT. This study could help library administrators identify areas of improvement and explore ways to increase the use and relevance of e-reserve services.

Authors

Institutions

Publication Details

Journal
Journal of Librarianship and Information Science
Published
2025-04-21
DOI
https://doi.org/10.1177/09610006251330886
Primary Topic
Technology Adoption and User Behaviour
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Continuance intention to use the self-built e-reserve databases (SED) in Chinese academic libraries: An integrative model

Xia Peng, Zequan Xiong, Li Yang
Journal of Librarianship and Information Science
Technology Adoption and User Behaviour
article

Continuance intention to use the self-built e-reserve databases (SED) in Chinese academic libraries: An integrative model

Xia Peng, Zequan Xiong, Li Yang
article en

Abstract

The self-built e-reserve database (SED) has still been considered an essential e-reserve service in Chinese academic libraries to resolve the issue of insufficient library copies and to support the future digital learning model. This study aims to examine the factors influencing users’ continuance intention to use SED in university libraries based on an integrative model that includes the Information System Success Model (ISSM), the Technology Acceptance Model (TAM), the Post-Acceptance Model of Information System Continuance, and the Stimulus-Organism-Response (S-O-R) model. A total of 384 valid responses were collected through a questionnaire-based survey across Chinese colleges and universities. The findings confirmed the direct influence of perceived usefulness (PU), perceived ease of use (PEOU), and personal innovativeness in IT(PIIT) on continuance intention to use SED. Additionally, the study highlighted the different mediating roles of the organism (i.e. PEOU, PU, and PIIT) between the stimulus (i.e. information quality, system quality, service information quality, and social influence) and continuance intention. Specifically, information quality and social influence were identified as the two primary antecedent variables influencing continuance intention through the mediating effects of PU and PIIT. This study could help library administrators identify areas of improvement and explore ways to increase the use and relevance of e-reserve services.

Journal of Librarianship and Information Science
East China Normal University (CN)
National Social Science Fund of China
Openalex Percentile: Top 91%
Technology Adoption and User Behaviour
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.