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Factors Affecting the Adoption of IoT-Based Smart Campus: An Investigation Using Analytical Hierarchical Process (AHP)

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Listed:
  • Radhwan Sneesl

    (Department of Software Engineering and Information System, Faculty of Computer Science and Information Technology, Universiti Putra Malaysia (UPM), Serdang 43400, Malaysia
    College of Science, University of Basrah, Basrah 61001, Iraq
    These authors contributed equally to this work.)

  • Yusmadi Yah Jusoh

    (Department of Software Engineering and Information System, Faculty of Computer Science and Information Technology, Universiti Putra Malaysia (UPM), Serdang 43400, Malaysia
    These authors contributed equally to this work.)

  • Marzanah A. Jabar

    (Department of Software Engineering and Information System, Faculty of Computer Science and Information Technology, Universiti Putra Malaysia (UPM), Serdang 43400, Malaysia
    These authors contributed equally to this work.)

  • Salfarina Abdullah

    (Department of Software Engineering and Information System, Faculty of Computer Science and Information Technology, Universiti Putra Malaysia (UPM), Serdang 43400, Malaysia
    These authors contributed equally to this work.)

  • Umar Ali Bukar

    (Department of Software Engineering and Information System, Faculty of Computer Science and Information Technology, Universiti Putra Malaysia (UPM), Serdang 43400, Malaysia
    Computer Science Unit, Department of Mathematical Sciences, Taraba State University, Jalingo P.M.B. 1167, Nigeria
    These authors contributed equally to this work.)

Abstract

The advancement of technology is making university campuses smarter every single day. Despite the benefits of these advanced technologies, the literature concerning the adoption of smart campuses is significantly lacking increased knowledge to provide effective smart campus solutions. This study aims to prioritize the adoption factors of an IoT-based smart campus. The study applied an analytical hierarchical process (AHP) on 25 factors drawn from the literature. The factors were classified into technology specific factors (TSF), organizational specific factors (OSF), environmental specific factors (ESF), and end-user specific factors (USF). Based on the results obtained, the most significant contributing factors were government support, privacy concerns, social influence, facilitating conditions, and service collaboration, whereas the least significant contributing factors were enjoyment, availability, reliability, mobility, and compatibility. Moreover, based on the global ranking computation, 12 factors from the OSF, ESF, and USF categories appeared to be more significant than TSF. The findings of this study could help university administrators, manufacturers, and policy-makers to understand the critical factors of smart campuses in order to improve the adoption and utilization of these solutions effectively.

Suggested Citation

  • Radhwan Sneesl & Yusmadi Yah Jusoh & Marzanah A. Jabar & Salfarina Abdullah & Umar Ali Bukar, 2022. "Factors Affecting the Adoption of IoT-Based Smart Campus: An Investigation Using Analytical Hierarchical Process (AHP)," Sustainability, MDPI, vol. 14(14), pages 1-21, July.
    • Handle: RePEc:gam:jsusta:v:14:y:2022:i:14:p:8359-:d:858231
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    References listed on IDEAS

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