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A multi-criteria analysis for an internet of things application recommendation system

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  • Mashal, Ibrahim
  • Alsaryrah, Osama
  • Chung, Tein-Yaw
  • Yuan, Fong-Ching

Abstract

Various internet of things applications are available that cover every aspect of daily life and users can subscribe to numerous IoT applications. Selecting the most suitable IoT applications for individual users is a critical challenge. This study aims to solve this challenge by proposing recommendation system using a hybrid multicriteria decision-making approach based on the analytical hierarchy process and simple additive weight methods. Based on the opinions and preferences of experts, the model and the hierarchy were designed to assess and compare three crucial criteria, namely smart objects, applications, and providers. The results show that applications criterion is more important for users than the other two criteria. In specific, privacy, reliability, and availability are crucial criteria for IoT applications.

Suggested Citation

  • Mashal, Ibrahim & Alsaryrah, Osama & Chung, Tein-Yaw & Yuan, Fong-Ching, 2020. "A multi-criteria analysis for an internet of things application recommendation system," Technology in Society, Elsevier, vol. 60(C).
    • Handle: RePEc:eee:teinso:v:60:y:2020:i:c:s0160791x18302860
    DOI: 10.1016/j.techsoc.2019.101216
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    References listed on IDEAS

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    Cited by:

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    9. Liao, Shu-Hsien & Widowati, Retno & Hsieh, Yu-Chieh, 2021. "Investigating online social media users’ behaviors for social commerce recommendations," Technology in Society, Elsevier, vol. 66(C).

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