Adoption of IoT-Based Smart Campuses Based on an Extended Technology Acceptance Model: The Mediating Role of Behavior Intention

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Abstract

As the digital transformation of higher education continues to deepen, Internet of Things (IoT) technology provides crucial support for the development of smart campus and service innovation.However, the level of actual adoption of smart campus among students in higher educational institutions remains heterogeneous.This study introduces a compatibility construct to extend the Technology Acceptance Model (TAM), focusing on examining the influence mechanisms of perceived usefulness, perceived ease of use, and compatibility on behavioral intention and the adoption of smart campus.This study adopted a questionnairebased approach to collect data, distributing 783 questionnaires to students in Nantong City, Jiangsu Province.A total of 753 valid responses were collected, with a response rate of 96%.Employing SPSS 26.0 and AMOS 24.0, the research conducted reliability and validity tests with structural equation modeling analysis.Research findings indicate that perceived usefulness, perceived ease of use, and compatibility all significantly promote behavioral intention.Furthermore, behavioral intention has a significant positive impact on the adoption of smart campus.Additionally, mediation analysis reveals that behavior intention plays a mediating role in the adoption of IoT-Based smart campus.This study contributes in two key areas: Theoretically, it extends the application of TAM research to the context of IoT-Based smart campus, providing new empirical evidence for understanding technology adoption mechanisms in educational digitization.Practically, it offers valuable insights for the development, functional optimization, and user adoption of smart campus initiatives in higher education institutions.

Fields of Study & Subjects

Technology Adoption and User Behaviour Smart Cities and Technologies Educational Management and Quality

Publication details

Journal / source
Journal of Logistics Informatics and Service Science
Publication date
6 February 2026