From Digital Readiness to Faculty Adaptation: A TOE Based Information Systems Model of Smart Campus Capability
Year: 2026
Type: article
Study design: Observational Study
Abstract: Digital resources are widely used in universities, but their availability does not explain how they contribute to academic practice. This study examines whether campus capability helps connect institutional readiness with perceived support for digital teaching. The model groups technological, organizational, and environmental circumstances as TOE Conditions and defines Smart Campus Capability through Technology Application, Learning Environment Optimization, and Data-Driven Decision Making. An online survey yielded 1,285 usable responses from university personnel familiar with institutional digital systems. CFA and covariance-based SEM were used to examine the measurement structure and hypothesized paths. Reliability and validity assessments supported the measures, with χ²/df = 2.60, RMSEA = 0.035, CFI = 0.982, TLI = 0.974, and SRMR = 0.023. The standardized TOE–capability path was 0.62. The capability–performance path was 0.68, while the direct TOE performance path was 0.29; each had p<0.001. The two-path product was approximately 0.42. A positive indirect estimate alongside the remaining direct association was compatible with partial mediation, although the product was not independently significance-tested. The findings support examining how universities organize technology use, learning support, and institutional information alongside the conditions enabling digital activity. They provide an institutional explanation for variation in perceived teaching support, with cross-sectional, self-reported evidence limiting causal interpretation.
Source: Journal of Computer Science
Authors: Yu Han, Charuay Savithi, Manirath Wongsim
Institution: Mahasarakham University
Language: English
Subfield: Information Systems
Field: Computer Science
Domain: Physical Sciences
SDG: Quality education
Open Access status: hybrid
Funder: Mahasarakham University
OpenAlex ID: W7225009792
